Proteomic Profiling of Paclitaxel Treated Cells Identifies a Novel

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Proteomic profiling of paclitaxel treated cells identifies a novel mechanism of drug resistance mediated by PDCD4 Hui Xu, Noah Dephoure, Huiying Sun, Haiyuan Zhang, Fangfang Fan, Jiawei Liu, Xuelian Ning, Shaochun Dai, Baogang Liu, Min Gao, Songbin Fu, Steven P. Gygi, and Chunshui Zhou J. Proteome Res., Just Accepted Manuscript • Publication Date (Web): 30 Apr 2015 Downloaded from http://pubs.acs.org on May 1, 2015

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Journal of Proteome Research is published by the American Chemical Society. 1155 Sixteenth Street N.W., Washington, DC 20036 Published by American Chemical Society. Copyright © American Chemical Society. However, no copyright claim is made to original U.S. Government works, or works produced by employees of any Commonwealth realm Crown government in the course of their duties.

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Journal of Proteome Research

82x31mm (300 x 300 DPI)

ACS Paragon Plus Environment


Heavy medium Arg Lys

Light medium

13C 15N 6 2 13C 15N 6 4

Arg 12C614N2 Lys 12C614N4

Thymidine block

H & L cell lysate 1:1 mixture

Thymidine block Arg 13C615N2 PTX

Noco

Shake-off

P N S 4-12 % gradient SDS-PAGE

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1 2

Gel cutting & In-gel digestion

3 4

LC-MS/MS

5 6 7

8

PTX response


Validation datasets

Fig. 1

PDCD4 - APQLVGQFIAR

UBE2S - DWTAELGIR 7

Light (PTX)

6

3

0

0 28.35

Time (min)

28.95

1 43.89 43.95 44.02 44.08 44.14 44.2 44.26 44.33 44.39 44.45 44.51 44.57

1

28.7

2

28.65

2

4

28.59

3

Heavy (CTL)

28.54

4

5

28.47

Intensity (x105)

Light (PTX)

5

28.41

6

28.89

Heavy (CTL)

28.82

7 Intensity (x105)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42


28.76

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Time (min)

Protein ID

Peptide ID

Control MS1 Area

PTX MS1 Area

Peptide numbers

Log2 PTX/Control

Normalized Log2

PDCD4

APQLVGQFIAR

57.65

13.82

3

-2.01

-2.25

UBE2S

DWTAELGIR

8.48

41.61

2

2.62

2.38

Fig. 2 ACS Paragon Plus Environment


A

C pcDNA3.1 PDCD4

B

0

4

8

UBE2S

KIFC1

MCM3

KIF23

Histone 3 pS10

GAPDH

12

16

pcDNA3.1PDCD4

TPX2

D 60

20

24

release hrs PDCD4 UBE2S GAPDH

Proportion of cells

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42

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50 40

*

*

pcDNA3.1 pcDNA3.1PDCD4

30 20 10 0


Fig. 3

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B 100 80 60 40

PDCD4

20

GAPDH

0

UACC1598 80 70 60 50

Hela

HT29

U2OS

D

sh-FF2 sh-PDCD4-2

sh-PDCD4-3

**

40 30

PDCD4

**

GAPDH

20 10 0

F PTX concentration (nmol/L)

E PDCD4

Inhibition of cell grwth (%)

C

Inhibition of cell growth (%)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42

Inhibition of cell growth (%)

A

90 80 70 60 50 40 30 20 10 0

pcDNA3.1 pcDNA3.1-pdcd4

*

* *

GAPDH PTX concentration (nmol/L)


Fig. 4


A

-Actin Control IP PDCD4 IP Total RNA No template

GAPDH

+

p53

+ +

+ 4

+ +

+ 2 3

+ +

+ 1

UBE2S

+ +

+ M 1

2 3 4

+ +

1 2 3

4

+ 1

2

3 4

100 bp 250 bp

B Relative mRNA level

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42

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35 30 25 20 15 10 5 0

Control IP

C IP (1/10)

Input (1/100)

PDCD4 IP

PDCD4


Fig. 5

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B

High expression

Medium expression

GAPDH

Low expression

PDCD4

1.2 1 0.8 0.6 0.4 0.2 0

Normal

Normalized PDCD4 level

A 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42

C


Fig. 6


1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42

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S G1 G2

PDCD4 phosphorylation

PDCD4 phosphorylation

Cell Cycle M

Stabilized PDCD4

Ubiquitinylated PDCD4

RRM

polyA mRNAs (UBE2S,etc.) Imbalance in cancer

polyA mRNAs (UBE2S,etc.) De-repression of translation

Suppression of translation

Altered sensitivity to anti-mitotics


Fig. 7

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Proteomic profiling of paclitaxel treated cells identifies a novel mechanism of drug resistance mediated by PDCD4 Hui Xu 1#, Noah Dephoure2#, Huiying Sun 1#, Haiyuan Zhang1, Fangfang Fan1, Jiawei Liu1, Xuelian Ning1, Shaochun Dai3, Baogang Liu3，Min Gao4, Songbin Fu1, Steven P. Gygi2* and Chunshui Zhou 1* 1

The Laboratory of Medical Genetics, Harbin Medical University, Harbin, China,

150081 2

Department of Cell Biology, Harvard Medical School, Boston, MA 02115

3

The Tumor Hospital, Harbin Medical University, Harbin, China, 150081

4

The Fourth Affiliated Hospital, Harbin Medical University, Harbin, China, 150001

#

These three authors contributed to this work equally

*

To whom correspondence should be addressed:

E-mail: [email protected], [email protected]

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ABSTRACT：： Paclitaxel (PTX) is a widely used chemotherapeutic drug effective against numerous cancers. To elucidate cellular pathways targeted by PTX and identify novel mechanisms of PTX resistance, we used a SILAC based quantitative proteomic approach to evaluate global changes of cellular protein abundance in Hela cells. We identified 347 proteins involved in a number of biological processes including spindle assembly, mitotic exit, and extracellular adhesion whose abundance changes upon PTX treatment. Notably, the tumor suppressor PDCD4 involved in translation suppression was down-regulated by PTX. We demonstrated that PDCD4 is a cell-cycle regulated protein and that changes in its abundance are sufficient to alter PTX sensitivity in multiple human cancer cell lines. Immunoprecipitation of PDCD4-RNA complexes and RT-PCR revealed that PDCD4 mediated PTX sensitivity acts through its interaction with mRNA of UBE2S, a ubiquitin K11 linkage conjugating enzyme critical for mitotic exit. Lastly, high levels of PDCD4 in lung cancer tissues are positively correlated with the longer overall survival time of the examined lung cancer patients with PTX involved adjuvant therapy. Therefore, our proteomic screen for paclitaxel targets not only provided novel insight into the cellular resistance to paclitaxel via the PDCD4-mitotic exit regulation axis, but also offered a predictive biomarker for paclitaxel-based personalized chemotherapy in the treatment of lung cancer.

KEYWORDS：quantitative proteomics, paclitaxel, drug sensitivity, personalized chemotherapy, lung cancer, cell cycle, PDCD4, UBE2S

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INTRUDUCTION Paclitaxel (PTX) is one of the most commonly used anti-mitotic drugs for treatment of human malignancies such as breast cancer, ovarian cancer, and lung cancer. Originally, PTX was discovered from the bark of taxus brevifolia (pacific yew tree). It binds to β-tubulin, stabilizes microtubules and prevents normal formation of mitotic spindles, this causes chronic activation of the spindle assembly checkpoint, leads to mitotic arrest and cell death 1-3. There are a couple of factors affecting PTX use in the clinic. First, little is known about how cancer cells respond to the prolonged mitotic arrest caused by PTX 4, thus, patient responses remain highly unpredictable. Secondly, acquired resistance during the course of treatment, is commonly observed and patients usually relapse and become less sensitive to further PTX administration 5. It is well established that both tubulin gene (including β-tubulin and α- tubulin ) mutations and up-regulation of the multiple drug resistance genes (MDR) are involved in PTX resistance

6-8

. However,

more studies indicate there are other mechanisms involved in PTX resistance

9, 10

.

Lastly, severe side effects such as neurological toxicity often hinder the PTX application 5. Therefore, to elucidate the global potential targets and the response signaling components of PTX is essential for better understanding its efficacy, resistance and side effects, and directing its application to the personalized and effective treatment of cancer in clinics.

Programmed cell death 4 (PDCD4) is a tumor suppressor gene that acts as a translational suppressor via direct interaction with target mRNAs. Though originally identified as a gene activated during apoptosis 11, subsequent work showed that it is able to suppress tumor development in a mouse skin tumor model

12, 13

. Further

analysis indicated that PDCD4 expression is reduced in human tumors of lung, colon, liver, and breast, and contributes to their disease progression 14-17. In addition, the expression of PDCD4 itself is regulated at various levels. On the mRNA level, over-expression of microRNA miR-21 in certain cancer cells leads to down-regulation of PDCD4 expression

18-20

. On the protein level, p70S6K kinase

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mediated phosphorylation of PDCD4 triggers its ubiquitinylation by the E3 ubiquitin ligase complex SCF-β-TRCP and subsequent proteasomal degradation

21, 22

. While

most studies have concentrated on the tumorigenesis of altered PDCD4 expression, little is known about how this tumor suppressor may affect the outcomes of chemotherapy. There is increasing evidence indicating that the level of Pdcd4 protein may affect the efficacy of an anticancer drug on cultured cancer cells as well as in clinical patients. A previous report suggests PDCD4 protein expression significantly correlated and contributed to the antitumor activities of tamoxifen and geldanamycin, though the underlying molecular mechanism is not understood23.

To globally elucidate the responsive molecules and signaling pathways targeted by PTX, we employed a quantitative proteomic technique, based on stable isotope labeling by amino acids in cell culture (SILAC)24 in combination with LC-MS/MS, to assess changes in protein abundance in human cervical epithelial cancer cell line Hela. We found that PTX triggers more extensive cellular effects than had been previously reported10. We identified 347 proteins whose levels were changed upon PTX treatment, including the down-regulated tumor suppressor PDCD4. We demonstrate that PDCD4 protein abundance is cell cycle regulated, that it influences PTX sensitivity in a number of human cancer cell lines, and that high levels of PDCD4 protein correlate with longer survival time in Chinese lung cancer patients treated with PTX. Immunoprecipitation of PDCD4-RNA complexes revealed that PDCD4 binds the mRNAs of the mitotic ubiquitin conjugating enzyme UBE2S. Therefore, our proteomic profiling established a global profile of PTX response in Hela cells, highlighted the role of tumor suppressor PDCD4 in regulating PTX sensitivity in cancer cells, and offered a new predictive biomarker for PTX based personalized chemotherapy in the treatment of cancer.

MATERIALS AND METHODS Cell culture and metabolic labeling 4 / 25


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Human cancer cell lines Hela, A549, HT29, U2OS were purchased from ATCC (Manassas, VA). Hela, HT29, U2OS cells were cultured in Dulbecco's Modified Eagle's Medium (DMEM) supplemented with 10% fetal bovine serum (FBS, Invitrogen, Carlsbad, CA), 100 IU/mL of penicillin and streptomycin in a humidified incubator with 5% CO2 at 37°C. A549 cells were cultured in F12K medium (Invitrogen) supplemented with the same recipe under the same conditions. For stable isotope labeling by amino acids in cell culture (SILAC) experiments, the DMEM medium without L-lysine or L-arginine was purchased from Cambridge Isotope Laboratories (Andover, MA). The complete light and heavy DMEM media were prepared by the addition of light (regular) or heavy lysine (13C6-15N4-L-lysine) and arginine (13C6-15N2-L-arginine) at 80 mg/L and 50 mg/L, respectively, supplemented with dialyzed fetal bovine serum (FBS, Invitrogen, Carlsbad, CA). The Hela cells were cultured in heavy DMEM medium for at least one month in order to achieve complete stable isotope incorporation. Paclitaxel treatment, peptide preparation and LC-MS/MS Equal numbers of heavy or light Hela cells were cultured in 15 cm cell culture dishes with either heavy or light DMEM, once cell confluence reached 70%, conventional double thymidine block was applied to both heavy and light cells. Briefly, thymidine stock solution was added to the cells at final concentration of 2.5mM for 19h, then, cells were washed with PBS three times and returned to SILAC medium for 9h. Thymidine was applied to the cells again for another 16h culture. After double thymidine block, the heavy G1/S cells were harvested by scraping and stored as control samples. The light cells were washed with PBS for three times and immediately released into the light media (for mitotic shake-off experiment) or the light media containing paclitaxel or nocodazole at final concentration of 1 uM or 0.2 ug/ml until 90% of cells were rounded up. G2/M cells were collected by low speed centrifugation. RIPA buffer was added to cell pellets and cells were lysed by sonication and quantified by Bradford assay. Equal amounts of light and heavy lysates were mixed and 20 ug of mixed protein were resolved on a 4-12% gradient SDS-PAGE gel and stained with Commassie blue, each sample lane was cut into gel 5 / 25



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slices. The proteins were reduced in-gel with dithiothreitol, alkylated with iodoacetamide, and digested with trypsin (Promega, Madison, WI) at 37°C overnight. Peptides were extracted with 50% acetonitrile, 0.1% formic acid and dried in a Speed-vac. Each peptide sample was desalted by stage tip25 and analyzed by LC-MS/MS on a LTQ-Orbitrap Velos mass spectrometer (Thermo Fisher Scientific, CA). CID-fragmentation was used when acquiring MS/MS spectra consisted of an orbitrap full MS scan followed by up to 10 LTQ MS/MS experiments on the most abundant ions detected in the full MS scan. MS settings were as follows: full MS (AGC 3 × 106; resolution 6 × 104; m/z range 300–1500; maximum ion accumulation time 1,000 ms); MS/MS (AGC 2 × 103; maximum ion accumulation time 150 ms; minimum signal threshold 500; isolation width 0.6 Da; dynamic exclusion time setting 30 s, collision energy was set to 35%. Data processing, peptide identification and quantification RAW files were converted into mzXML, MS/MS spectra were searched using the Sequest (version 28) against a database containing the sequences of all proteins in the human IPI protein database (version 3.68，87083 entries) and common contaminant sequences (e.g. human keratins and trypsin) in both forward and reversed orientations. 10 ppm precursor mass tolerance, 0.6 Da product ion mass tolerance, up to two missed

tryptic

cleavages,

variable

oxidation

of

methionines

and

carbamidomethylation of cysteine were allowed. The target-decoy approach was applied to control peptide and protein level false discovery rates (FDRs), peptide spectral matches were filtered to a 1% FDR at the peptide-level based on the number of decoy sequences in the remaining data set. Automated peptide quantification was performed by using the Vista program

26

. SILAC quantification setting was adjusted

to be doublets, with lysine (+ 10 Da) and arginine (+8Da) as heavy labels. Only proteins with at least two peptides identified by MS/MS were considered as reliable candidates. Dataset normalization is performed by assuming that the majority of the proteins in each dataset are not significantly altered and the peptide ratios are normalized so that the median of the 2-based logarithms is nearly zero to correct for unequal mixing of heavy (control) and light (treated) peptides. 6 / 25


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Plasmid construction and gene silencing by shRNA For stable expression of PDCD4 and UBE2S, The coding sequences of PDCD4 and UBE2S were amplified from pDONR223-PDCD4 and pDONR223-UBE2S plasmids by

using

following

primer

pairs:

PDCD4–KpnI-F

5’

atcggtaccgatggattacaaggatgacgacgataaggatgtagaaaatgagcag 3’ PDCD4-XhoI-R 5’ aatgctcgagtcagtagctctctggtttaagacg 3’, UBE2S-EcoRI-F 5’ atcgaattcgatggattacaaggatgacgacgataagaactccaacgtggagaacc 3’ UBE2S-XhoI-R 5’ aatgctcgagctacagccgccgcagcgcccgcttctt 3’, The PCR products were inserted into pcDNA3.1/hygromycin (the EcoRI site on Hyg gene was mutated) through indicated restriction enzymes. For stable knockdown of PDCD4, shRNA-expression vectors (GV248) were purchased from Genechem (Shanghai, China) with the following target sequences 5’ ggtttgtagaagaatgttt 3’ (shPDCD4-1), 5’ accattactgtagaccaaa 3’ (shPDCD4-2) and 5’ tttggatgaaagggcattt 3’(shPDCD4-3). Plasmids were transfected by Lipofectamine2000 into desired cells and stable transfectants were selected in the presence of 200 ug/ml hygromycin B or 2.0 ug/ml puromycin (Sigma-Aldrich). Protein expression levels in these resulting clones were determined by Western blotting. Antibodies and chemical reagents All chemicals including paclitaxel, nocodazole, HPLC solvents, LC-MS grade water, acetonitrile and formic acid, unless otherwise specified, were purchased from Sigma-Aldrich. Porcine sequencing grade modified trypsin was obtained from Promega, Antibodies against Pdcd4 (Cell Signaling Technology #9535, Santa Cruz sc-27122), UBE2S (Cell Signaling Technology #9630, Santa Cruz sc-131354), TPX2 (Cell Signaling Technology #12245), kinesin family (Cell Signaling Technology #12313), GAPDH (Cell Signaling Technology #5174), phospho-H3 (Millipore #05-806), etc were purchased from the indicated company. For Western blotting, antibodies were used at dilution of 1:1000. Immunoprecipitation of PDCD4 –RNA complex and Reverse Transcription-PCR 2 x 10 7 Hela cells were cross-linked in vivo with 0.5 % formaldehyde for 20 min at RT. After washing with phosphate-buffered saline (PBS), the cells were lysed with 7 / 25



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RIPA buffer containing 50mMTris pH 7.4, 150mMNaCl, 1 mM EDTA, 0.25% sodium deoxycholate, proteinase inhibitor cocktail (Roche), RNase inhibitor (Promega; 40 U/ml) for 20 min at 4°C. Lysates were clarified by centrifugation. A total of 50 mg of proteins in 10 ml, 20 ug of rabbit anti-PDCD4 antibody (Cell signaling technology) or a rabbit control antibody, and 100 ul of magnetic protein A beads (Invitrogen) were used for each immunoprecipitation (IP). IP was performed for 2 h at 4°C with gentle rotation. Bead bound immunocomplexes were washed with RIPA buffer 3 times and an aliquot of 10 ul of bead slurry was taken for Western blotting, , the remaining beads were treated with RNase-free DNase I (40 U/ml) for 15 min at room temperature, followed by proteinase K treatment for 1 h at 37 °C and subjected to phenol-chloroform extraction and isopropyl alcohol precipitation of the bound RNAs. cDNAs were generated using qScript cDNA Super-Mix (Invitrogen), and the PCR amplification was followed to detect the transcripts of candidate genes by using following primers: PDCD4-RT-F: 5’ tgtaaaccctgcagatcctgataa 3’, PDCD4-RT-R: 5’ tggaggatgctgaaatccaa 3’, UBE2S-RT-F 5’ aggaggtgacgacactgacc 3’ , UBE2S-RT-R 5’ acttgatggtcagcagtacg 3’, p53-RT-F: 5’ caggtagctgctgggctc 3’, p53-RT-R: 5’ gctcgacgctaggatctgac 3’, GAPDH-RT-F:5’ gctgagaacgggaagcttgt 3’, GAPDH-RT-R: 5’ gccaggggtgctaagcagtt 3’, β-actin-RT-F: 5’ tgaagtgtgacgtggacatc 3’, β-actin-RT-R: 5’ ggaggagcaatgatcttgat 3’. RT-PCR products were visualized on a 3 % agarose gel and imaged by Alpha Image HP System (Protein Simple). Quantitative real-time PCR Total RNA was extracted from cells using TRIzol (Invitrogen)and then converted to first strand cDNA using SuperscriptIII reverse transcriptase (Invitrogen).Quantitative real-time PCR was performed with SYBR Premix (Invotrogen) on an Applied Biosystems7500 Fast (ABI). Changes in the threshold method were used to calculate the relative mRNA expression, and the results are represented as relative fold induction compared to the control samples and are normalized to the endogenous control GAPDH for gene expression analysis. Cell viability assay Cells were seeded into 96-well plates at 5,000 per well. 24h later, serial diluted PTX 8 / 25


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was added to the cells for 72h, MTT assay were performed according to the manual provided by the manufacturer (Invitrogen). Inhibition percentage of cell growth was calculated as (OD 495nm of untreated – OD 495nm of treated) / OD 495nm of untreated. All measurements were performed in triplicate. The inhibition rate of cell growth was presented as mean ± SD (standard deviation). Flow cytometry Log phase cells were harvested by trypsin digestion, and fixed in 1ml pre-cooled 70% ethanol for 2 hours. Cell were washed and re-suspended in 1ml PBS containing 0.25% Triton-X-100 for 10min, supernatant was removed, cells were re-suspended in 1ml PBS containing 10 ug/ml Rnase A and 20ug/ml propidium iodide in a FACS tube， after 30 min incubation in dark, the samples were analyzed by a flow cytometer (BD Biosciences). Tumor specimen preparation and Western blotting Lung tumor specimens examined in this study were obtained from patients who underwent surgical operation for lung cancer at the Department of Surgery, the tumor hospital, Harbin Medical University from Jan, 2010 to Sep. 2010. Patients did not receive any treatment before surgery, and signed informed consent forms for sample collection. The pathological stage, grade, and nodal status were obtained from the primary pathology reports according to TNM category. After surgical removal, all these patients received adjuvant chemotherapy with paclitaxel for prevention treatment. Survival data were collected from 77 patients. The median follow-up period was 36 months. Adjacent normal lung tissues were resected as controls. Tissue protein lysates were generated by grinding a piece of 20 mg of tumor tissue in a bath of nitrogen liquid, the homogenate was desolved in RIPA buffer (50mMTris pH 7.4, 150mMNaCl, 1 mM EDTA, 0.25% sodium deoxycholate, proteinase inhibitor cocktail), centrifuged at 14,000 rpm for 30 minutes at 4 degree, protein concentration was determined by Bradford assay, and 60 ug of each supernatant was fractionated on 10% SDS-PAGE gels. The proteins were transferred to PVDF membrance and incubated with specific antibodies, detected using the appropriate secondary antibodies and visualized with ECL (Amersham Bioscience, Piscataway, NJ) or using 9 / 25



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the Odyssey imaging system (Li-COR). The intensity of bands of western blot was quantified by densitometry scanning (Li-COR). After normalization with GAPDH in each tissue, we compared the signal of PDCD4 in each cancer tissue versus the signal of PDCD4 in each adjacent normal lung tissue, the ratio in each patient with equal or greater than 80% was scored as high expression of PDCD4, in between 80% and 40% was scored as medium expression of PDCD4 and lower than 40% as low expression of PDCD4. We divided these patients into two groups including high expression group and medium & low expression group to analyze the overall survival time between the two groups. Statistical analysis: The survival rates were assessed by the Kaplan-Meier method and the log-rank test was applied to examine the relationship between PDCD4-protein expression level and the cumulative lung cancer-survival rates. For PTX cytotoxicity analysis, a significant difference test was determined by the Student’s t-test or Anova test. Statistical significance was set at p < 0.05 (two-tailed). RESULTS Establishment of a PTX response database using quantitative proteomics Since most genes exert their function through their encoding proteins, we thought to profile cellular PTX responses by determining cellular protein abundance changes upon PTX treatment. We performed a quantitative proteomic analysis, using metabolic labeling by SILAC and subsequent LC-MS/MS, to profile the PTX-induced differential protein expression in human Hela cells. Since PTX is an anti-mitotic agent and cause cells to arrest at mitotic phase, most PTX responsive candidates should be mitotic dependent, thus, we used G1/S phase cells induced by double thymidine block as a reference sample, because an asynchronous cell population contains significant amount of G2/M cells which might compromise the accuracy of peptide quantification. We released the light labeled G1/S cells into 1 uM PTX for 20 hours and harvested them as a drug treated sample to assess the PTX-induced alterations in protein abundance. Meanwhile, we also performed two parallel experiments using 10 / 25


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nocodazole arrest and mitotic shake-off to verify the PTX responsive candidates in a mitosis-dependent manner. Our profiling and validation strategy is diagrammed in Fig. 1. The resulting three datasets (designated as PTX, Nocodazole and Shake-off) from LC-MS/MS analyses allowed us to quantify > 4,000 proteins (for detailed information, see Suppl. Table S1). While the majority of the quantified proteins displayed similar levels of expression in the treated and control cells, we found 347 proteins were significantly changed after PTX treatment (down- or up-regulated by > 1.5-fold, i.e., the median ratio of treated protein versus control protein is either 1.5). For the Nocodazole and Shake-off datasets, we identified 259 and 331 changing proteins respectively (Supple. Table S2). Among these PTX responsive candidates, 163 proteins were changed in either the Nocodazole or the Shake-off dataset, and 44 out 163 were changed in all three datasets (Supple. Fig. S1A and Supple. Table S2). These 163 candidate PTX responsive protein might represent a group of core PTX responsive proteins, further analysis indicated the majority of these core responsive proteins are with theoretical molecular weights smaller than 100 KD (Supple. Fig. S1B), suggesting a possibility that the abundance of small or medium sized proteins is more likely affected by PTX treatment. Bioinformatic analysis of PTX response signaling pathways. To explore the cellular pathways that are altered by PTX treatment, we next subjected the 163 core responsive proteins to Panther Classification System, and revealed that the PTX treatment led to an enrichment of proteins involved in apoptosis, cell adhesion, cell communication and cell cycle control (Supple. Fig. S1C). Among them, kinesin family members such as KIFC1, KIF2C, KIF20A, KIF11, KIF14 and KIF23 are stabilized significantly upon PTX treatment. The observed elevation of kinesin protein levels is consistent with their role as microtubule binding proteins and force-generating motors for organelle transport and chromosome segregation during mitosis. In support of our findings, a transcription profiling of a gastric PTX resistant cell line indicated KIF23 is up-regulated in the tested cells

27

. Moreover, other

proteins involved in spindle assembly and mitotic exit were stabilized upon PTX treatment. These examples include TPX2, a microtubule nucleating protein, PLK1, a 11 / 25



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Polo-like kinase and UBE2S, a K11 linkage ubiquitin conjugating enzyme. Strikingly, the abundance of a number of cell adhesion molecules such as MCAM, L1CAM and ICAM1 were up-regulated in response to PTX. This result is in agreement with a recent study showing that paclitaxel treatment could give rise to enhanced transcription of CAM-3 28. In our experimental systems, the in vitro cultured adherent cells detach from culture matrix as they enter mitosis. they should re-adhere to the matrix again once they exit from mitosis. Thus, the elevated protein levels of adhesion molecules in mitosis might serve as a prerequisite for re-entry into inter-phase. PDCD4 is a PTX target protein and its protein level oscillates during cell cycle progression In contrast to the fact that most PTX up-regulated proteins are mitotic or spindle assembly related, the functional categories for PTX down-regulated proteins are much more diverse. Among the down-regulated proteins, PDCD4, a known tumor suppressor, was identified with at least a 4-fold decrease of protein abundance upon PTX treatment whereas the mitotic ubquitin conjugating enzyme UBE2S

29

was

increased by about 4-fold (Fig. 2). The facts that PTX is an anti-mitotic cytotoxic agent and PTX up-regulated enzyme UBE2S is a known cell cycle regulated protein 30 prompt us to examine whether PDCD4 is also regulated during cell cycle progression by using immune-blotting. Indeed, as shown in Fig.3A, PDCD4 level is decreased dramatically in nocodazole induced mitotic cells compared to thymidine induced G1/S cells or an asynchronous cell population, while the known mitotic proteins such as UBE2S, TPX2, KIFC1, phospho-Histone3(pS10) are all stabilized in mitotic cells. To further confirm our observation, we also examined PDCD4 protein level at different time points along the time course of nocodazole release experiment. Obviously, PDCD4 level gradually goes up after the nocodazole release while UBE2S level behaves oppositely (Fig. 3B). Moreover, we extracted the total RNA from control G1/S or PTX arrested cells, performed real-time quantitative PCR to determine the transcription state of PDCD4 and UBE2S genes, the quantitative PCR results indicated there is no obvious transcription changes for PDCD4 and UBE2S genes in PTX treated cells compared to the control cells (Supple. Fig S2). Thus, the 12 / 25


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changes of PDCD4 and UBE2S during cell cycle progression or upon PTX exposure most likely are a result from the alteration of protein abundance. On the other hand, FACS analysis clearly demonstrated that there are more G1 phase DNA content and less S phase DNA content in U2OS cells over-expressing PDCD4 by a mammalian expression vector compared to the cells transfected with the empty vector (Fig. 3C and 3D). Additionally, a slightly decreased cell proliferation rate was observed in the PDCD4 over-expressing cells (Supple. Fig. S3), suggesting that PDCD4 protein level may affect cell cycle progression vice versa. Protein levels of PDCD4 influence cancer cell sensitivity to PTX We next wanted to determine if PDCD4 protein levels affect cancer cell sensitivity to PTX in vitro. First, we determined the PDCD4 protein levels in several human cancer cell lines including cervical epithelial cell Hela，osteosarcoma cell U2OS, colon carcinoma cell HT29 and ovarian cancer cell UACC-1598, and then measured their sensitivity to 10 nM PTX as a function of the inhibition rate of cell growth after 72 h treatment. As shown in Fig. 4A and 4B, the PDCD4 level in each cell line positively correlates with their sensitivity to PTX. In order to further establish the correlation between PDCD4 protein levels and PTX sensitivity, we used shRNA expression vector to knock down the endogenous PDCD4 in Hela cells, which have relatively high levels of endogenous PDCD4. As shown in Fig. 4C and 4D, PDCD4 knockdown cells exhibited decreased sensitivity to PTX at concentrations of 10 nM and 100 nM compared to the shRNA-FF2 control cell line (p< 0.05). In a complementary experiment, we measured sensitivity upon over-expression of PDCD4 in U2OS cells, which have relatively low endogenous levels. Upon introduction of pcDNA3 vector driving the expression of PDCD4 in U2OS cells, the PDCD4 over-expressing cells exhibited increased sensitivity to PTX at the concentrations of 1nM, 10nM, 100nM compared to the empty vector transfected U2OS cells (p < 0.05) (Fig. 4E and 4F). Therefore, the PDCD4 protein levels can positively influence cancer cell sensitivity to PTX. PDCD4 binds to mRNAs of UBE2S The mechanism by which PDCD4 exerts its effect on PTX sensitivity remains unclear. 13 / 25



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A couple of recent findings suggested PDCD4 might bind to the mRNAs of a group of specific molecules through an RRM domain in its N–terminus and suppress their translation. Based on our observations of the opposite PTX effects on the protein abundance of PDCD4 and UBE2S, we further explored the relation between them. we immunoprecipitated PDCD4 from Hela cell lysates, used semi-quantitative RT-PCR to test whether the mRNAs of UBE2S are the binding targets of PDCD4. As shown in Fig. 5, a strong UBE2S RT-PCR product signal was observed from the anti-PDCD4 immunoprecipitation, while a very weak signal was detected from a control pull-down by using an unrelated antibody. By contrast, there is no any increase of RT-PCR signal intensity for mRNAs of GAPDH and β-actin, two abundant transcripts served as non-specific binding controls, in both immunoprecipitations, High expression of PDCD4 correlates with the longer survival time of Chinese lung cancer patients with paclitaxel based adjuvant therapy It has been shown that loss of PDCD4 expression correlates with rapid disease progression and poor prognosis in Caucasian lung cancer patients 14. To test whether a similar correlation exists in Chinese lung cancer patients, we looked at a cohort of patients treated with PTX based adjuvant chemotherapy after their diagnosis. We collected lung cancer tissues and their adjacent normal tissues from 77 cases of lung cancer patients undergoing surgical operations. We tested the expression level of PDCD4 in these tissues by immuno-blotting, we normalized PDCD4 protein levels by comparing with GAPDH expression in each tissue. Based on the ratios of PDCD4 levels in the tumor and matched control tissues, the patients were divided into high, medium and low expression group. We scored 26 cases with high expression of PDCD4 and 51 cases with low or medium expression of PDCD4(Fig. 6). After surgical operations, these patients were also administered adjuvant chemotherapy in combination with PTX. Regardless of the effectiveness of these treatments, we followed up the survival state of these patients in a 36-month period of time. The cumulative survival rate in the high expression group is 61.5%, which was much higher than the rate in the low and medium combined group (39.2%) (Fig. 6C), a log-rank test indicated there was a significant difference of the survival rates between 14 / 25


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the two groups (p< 0.05). By contrast, age, gender and pathological features of these patients did not influence PDCD4 levels (Supple. Table S3). Therefore, the high level of PDCD4 in the tested Chinese lung cancer patients may not only correlate with longer survival time, but also be a useful biomarker for predicting the efficacy of PTX based adjuvant chemotherapy in the clinic.

DISCUSSION Recent advances in large scale quantitative proteomics provide a powerful approach to study the global cellular effects of a drug or chemical agent

31-33

. Quantitative

proteomics combined with functional analysis has been used successfully to identify biomarkers and drug targets and to evaluate the efficacy and synergy of multidrug combinations

34-36

. Using this approach, we have quantified >4,000 cellular proteins

and identified 347 proteins whose levels changed in response to PTX treatment in Hela cells. More than half of these PTX responsive candidates can be confirmed by an parallel verification method such as nocodazole arrest or mitotic shake-off. Thus, these proteins may represent a core group of PTX responsive proteins in human cancer cells. One fact needed to be pointed out is that some known PTX targets including β-tubulin, P-glycoprotein, the product of MDR1 gene 7, 8 are missing in our PTX responsive list (Supple. Table S1), this may suggest our profiling result is just part of a PTX response proteome due to current technology limitations as well as the stochastic nature of our data acquisition method. Furthermore, there are 184 candidates were not validated by either nocodazole arrest or mitotic shake-off. The two validation approaches are based on the mitotic blockage feature of PTX, may not recapitulate the entire PTX response and fail to validate some responsive candidates specific only to PTX treatment. Whether those 184 candidates are paclitaxel specific or not remains to be answered by more vigorous investigations. But theoretically, there should be some response candidates only specific to paclitaxel treatment. Nevertheless, our screen indicates proteins involving in cell cycle control, cell communication, cell adhesion and apoptosis comprise of a core group of PTX response proteins in human cancer cells. 15 / 25



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PDCD4, a tumor suppressor identified initially as apoptosis induced protein, is down-regulated by PTX, this regulation is likely executed on the post-transcription level since PDCD4 transcription is not affected upon PTX treatment (Supple. Fig S2), which is in contrast to a couple of drugs such as isocorydine and decorin giving rise to transcriptional activation of PDCD4 gene

37, 38

. Furthermore, we found the protein

level of PDCD4 is oscillated during cell cycle progression, PDCD4 peaks at G1 and are down at mitosis. Previous studies reported serum addition to starved cells or IFNα stimulation triggered phosphorylation of Ser 67 on PDCD4 by either p70 S6 kinase (S6K) or p90 ribosomal protein S6K (RSK) leading to β-TRCP mediated degradation and subsequent initiation and progression of cell cycle

21, 39

. In addition, an elegant

quantitative phosphoproteomic profiling done by Olsen JV, et al have shown the down-regulation of PDCD4 and up-regulation of UBE2S during mitosis40. These observations are in good agreement with our finding that PDCD4 protein level is regulated by cell cycle.

The expression level of PDCD4 has been implicated in cancer cell sensitivity to several chemotherapeutics, including tamoxifen and geldanamycin23, though some results at times were unclear and even contradictory. In our study, we have clearly demonstrated that high levels of PDCD4 confer sensitivity to PTX, while low levels of PDCD4 yield decreased sensitivity. One more layer of evidence to support our finding is that miR-21, a known negative regulator of post-transcription of PDCD419, is involved in PTX resistance. The inhibition of miR-21 increases sensitivity to taxane in a variety of cancer cells including ovarian cancer, prostate cancer and glioblastoma 41-44

. In addition, in a cohort of paclitaxel treated Chinese lung cancer patients, those

with higher PDCD4 protein levels survived longer further supported that PDCD4 affects the outcomes of paclitaxel treatment.

The molecular mechanism underlying PDCD4 mediated drug sensitivity remains unclear. Generally, PDCD4 exerts its tumor suppression activity through binding to 16 / 25


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eIF4A and eIF4G, inhibiting the helicase activity of eIF4A and preventing cap-dependent translation. However, so far，only a few natural mRNAs such as p53, c-myb45,

46

are identified as targets of PDCD4. Recent findings that in

vitro-transcribed XIAP and Bcl-xL 5’ UTRRNAs, but not the cIAP1 3’ UTR-RNA, are binding targets of PDCD4, suggest that PDCD4 may only target to a group of specific molecules in cells, not be a general suppressor of protein translation47.

Several layers of evidence support our finding that PDCD4 confers PTX sensitivity by binding to mRNAs of UBE2S and suppressing the translation of UBE2S. First of all, there are mRNAs of UBE2S existing in the immuno-precipitated PDCD4 protein complex. Secondly, there is an inverse correlation between PDCD4 protein level and UBE2S protein level across the cell cycle and PDCD4 and UBE2S respond to PTX treatment oppositely. Thirdly, over-expression of UBE2S is a common phenotype in breast cancer, low level of PDCD4 is often associated with worse overall survival of breast cancer 48. Fourthly, the expression level of UBE2S itself affects drug sensitivity. A previous study reported HeLa cells treated with E2-EPF/UBE2S siRNA were approximately two-fold more sensitive to the topo II inhibitors etoposide and doxorubicin than the cells transfected with control siRNA

30

. Lastly, introduction of

UBE2S cDNA by a mammalian expression vector into human Hela cells leads to a slight increase of cell resistance to PTX, though there is no statistically significant increase between the UBE2S expressing cells and the empty vector cells (p>0.05) (Supple. Fig. S4). This observation also suggests there might be more molecules targeted by PDCD4 other than UBE2S alone in the PDCD4 mediated PTX sensitivity.

UBE2S is an E2 enzyme for K11-linked polyubiquitination of mitotic regulators, together with the anaphase-promoting complexes(APC/C), plays a critical role in regulating spindle assembly29. How is the UBE2S regulated mitotic exit and PDCD4 mediated PTX sensitivity connected to each other in cells? A previous study reported elevated activity of UBE2S usually leads to forced mitotic exit or slippage from mitotic arrest and renders cells more resistance to mitotic arrest induced by 17 / 25



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anti-mitotics including PTX 49. Therefore, based on our findings and other published observations, we propose a working model for PDCD4 mediated PTX sensitivity in human cells as diagrammed in Fig. 7. We think PDCD4 controls the translation of a group of mitotic proteins including UBE2S in a cell cycle-dependent manner. In normal G1 phase cells, the activity for PDCD4 phosphorylation and ubiquitin dependent degradation of PDCD4 is low, thus, PDCD4 protein level is maintained high, and more PDCD4 proteins bind to mRNAs of its targeting genes (e.g, UBE2S) in mitotic exit control and suppress the translation of these proteins. At G2/M phase, PDCD4 becomes phosphorylated and is subjected to β-TRCP mediated proteasomal degradation. Decreasing levels of PDCD4 cause de-repression of the translation of these proteins. Thus, these PDCD4 target proteins are maintained at appropriate levels to ensure timely mitotic exit in normal cells. However, in cancer cells, aberrantly low levels of PDCD4 lead to deregulation of translation of PDCD4 target proteins enhanced mitotic slippage and loss of sensitivity to PTX, which was evidenced by the observation that low expression or depletion of UBE2S resulted in prolonged mitotic arrest caused by PTX

49

. At this point, there probably are more unknown PDCD4

targets during mitotic exit other than UBE2S. For example, similar to UBE2S, knockdown of TPX2, another important mitotic regulator, led to increased PTX sensitivity in pancreatic cancer cells 50. How many PDCD4 targets in the cells are still unknown, a large scale pull-down of PDCD4-RNA complexes, combining with a highthrough-put RNA sequencing or microarray may shed more light onto this aspect in the future. In summary, by performing a quantitative proteomic profiling, we have established a PTX responsive proteomic database. Most importantly, we identified the tumor suppressor PDCD4 is down-regulated by PTX, and PDCD4 protein levels positively affect cancer cell sensitivity to PTX. Loss or reduction of PDCD4 mediated translation suppression of UBE2S might be one of the molecular mechanisms for PDCD4-confered paclitaxel resistance in human cancers. Additionally, PDCD4 level is associated with lung cancer survival in Chinese lung cancer patients treated with PTX based adjuvant chemotherapy. Thus, PDCD4 may be a useful biomarker for both 18 / 25


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the prognosis of this disease progression and the prediction of drug effectiveness for paclitaxel-based personalized chemotherapy for the treatment of cancer.

ASSOCIATED CONTENT Supporting information Supplemental Table S1 Paclitaxel response proteome and its validation, Supplemetal Table S2 List of core PTX responsive proteins and their validation, Supplemental Fig. S1 Identification of 163 core PTX responsive candidates, Supplemental Fig. S1 Identification of 163 core PTX responsive candidates, Supplemental Fig. S2 The transcription of PDCD4 and UBE2S is not affected by PTX treatment, and Supplemental Fig. S3 A slight increase of cell resistance to PTX upon introduction of UBE2S expression. This material is available free of charge via the internet at http://pubs.acs.org.

ACKNOWLEDGMENTS The authors thank Drs. Bo Zhai, Willi Haas of SPG lab for their help with this project. H.X., H.S., X.N., H.Z, J.L. and C.Z. are supported by Grant 81272582 from the Natural Sciences Foundation of China. N.D. and S.P.G. are supported by National Institutes of Health.

ABBREVIATIONS PTX paclitaxel; PDCD4 programmed cell death 4; SILAC stable isotope labeling by amino acids in cell culture; DMEM Dulbecco's modified eagle's medium ； LC-MS/MS liquid chromatography combined with tandem mass spectrometry; SDS-PAGE sodium dodecyl sulfate-polyacrylamide gel electrophoresis. REFERENCES 1.

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Figure legends: Fig. 1. Comparative proteomics to identify global cellular response targets of paclitaxel in Hela cells Diagrammed is the work flow of global profiling cellular PTX response proteins. Hela cells were metabolically labeled with stable isotopes, and subjected to G1/S arrest in heavy medium as controls or to G1/S arrest in light medium and released into PTX or nocodazole containing medium or mitotic shake-off, control and PTX treated lysates were mixed in equal amounts and resolved in SDS-PAGE. Gel bands were excised, followed by in-gel tryptic digestion and LC-MS/MS analysis to accomplish the indicated quantitative datasets.

Fig 2. Quantitative proteomics identifies paclitaxel down-regulates PDCD4 and up-regulates UBE2S

Upper panel, representative MS1 chromatograms showing

relative quantification signals of a single heavy and light PDCD4 peptide pair (left) and a UBE2S peptide pair (right). Lower panel, a summary of abundance changes of the PDCD4 and UBE2S peptides upon PTX treatment. The peptide ratio was calculated as described in materials and methods.

Fig. 3. PTX response protein PDCD4 is regulated by cell cycle

A. The level of

PDCD4 peaks at G1/S phase and drops in mitosis. Lysates from thymidine induced G1/S Hela cells and nocodazole induced G2/M cells were immunoblotted to determine the protein levels of PDCD4 and a group of mitotic PTX response 23 / 25



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candidates. Phospho-H3 was used to monitor G2/M cell status and GAPDH was used as internal loading controls. B. PDCD4 protein levels

gradually increase upon

mitotic exit. Hela cells were released from nocodazole arrest and cells were harvested at the indicated times to monitor PDCD4 and UBE2S expression during cell cycle progression. C and D. Over-expression of PDCD4 altered cell cycle profile of U2OS cells. Compared to empty vector transformed cells, more G1 DNA content and less S-phase DNA content were detected in cells over-expressing PDCD4, * indicates p < 0.05 by a Student’s t-test.

Fig. 4. Expression levels of PDCD4 in cancer cells influence their sensitivity to PTX A and B: A positive correlation between PDCD4 levels and cancer cell sensitivity to PTX. Cells were exposed to 10nM PTX for 72h. The PTX sensitivities of four human cancer cell lines were measured by MTT cell viability assay, and PDCD4 expression level in each cell line was visualized by immuno-blotting. C and D: knockdown of PDCD4 by shRNAs leads to decreased sensitivity to PTX in Hela cells. Cells were stably transfected with control shFF2 or with three Pdcd4-targeting shRNAs. Cell lysates were resolved by SDS-PAGE and analyzed by immune-blotting to confirm PDCD4 knockdown. MTT assays were performed to determine the PTX sensitivity in the indicated cell lines. PTX treatment time was 72 hours. * indicates p

Proteomic Profiling of Paclitaxel Treated Cells Identifies a Novel

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