mcam mediates chemoresistance in small cell lung cancer ... · 6/23/2017 · under the nikon...

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MCAM mediates chemoresistance in small cell lung cancer via the PI3K/AKT/SOX2 signaling pathway

Satyendra C. Tripathi1, Johannes F. Fahrmann1, Muge Celiktas1, Mitzi Aguilar1, Kieren D.

Marini2, Mohit K. Jolly3, Hiroyuki Katayama1, Hong Wang1, Eunice N. Murage1, Jennifer B.

Dennison1, D. Neil Watkins2, Herbert Levine3, Edwin J. Ostrin4, Ayumu Taguchi5 and Samir M.

Hanash1*

Departments of 1Clinical Cancer Prevention, 4Pulmonary Medicine, and 5Translational Molecular

Pathology, University of Texas MD Anderson Cancer Center, Houston, Texas. 2Centre for

Cancer Research, Hudson Institute of Medical Research, Clayton, Victoria, Australia. 3Center

for Theoretical Biological Physics, Rice University, Houston, Texas.

Running title: MCAM modulates SCLC chemoresistance

Funding support: This research was supported through the Rubenstein Family Foundation, the

Lyda Hill Foundation and the MD Anderson Moonshot philanthropy grants (to S.M. Hanash)

*Corresponding: [email protected] (S.M.H.)

Conflicts of interest: The authors report no conflicts of interest.

Research. on October 14, 2020. © 2017 American Association for Cancercancerres.aacrjournals.org Downloaded from

Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited. Author Manuscript Published OnlineFirst on June 23, 2017; DOI: 10.1158/0008-5472.CAN-16-2874

http://cancerres.aacrjournals.org/

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Abstract

Despite favorable responses to initial therapy, small cell lung cancer (SCLC) relapse occurs

within a year and exhibits resistance to multiple drugs. Due to limited accessibility of patient

tissues for research purposes, SCLC-patient derived xenografts (PDX) have provided the best

opportunity to address this limitation. Here we sought to identify novel mechanisms involved in

SCLC chemoresistance. Through in-depth proteomic profiling, we identified MCAM as a

markedly upregulated surface receptor in chemoresistant SCLC cell lines and in chemoresistant

PDX compared to matched treatment-naïve tumors. MCAM depletion in chemoresistant cells

reduced cell proliferation and reduced the IC50 inhibitory concentration of chemotherapeutic

drugs in vitro. This MCAM-mediated sensitization to chemotherapy occurred via SOX2-

dependent upregulation of mitochondrial 37S ribosomal protein 1/ATP binding cassette

subfamily C member 1 (MRP1/ABCC1) and the PI3/AKT pathway. Metabolomic profiling

revealed that MCAM modulated lactate production in chemoresistant cells that exhibit a distinct

metabolic phenotype characterized by low oxidative phosphorylation. Our results suggest that

MCAM may serve as a novel therapeutic target to overcome chemoresistance in SCLC.

Keywords: Small cell lung cancer, Chemoresistance, Proteomics, MCAM, EMT, SOX2, PI3K,

AKT, CREB1, patient derived xenograft




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Introduction

Small cell lung cancer (SCLC) is an aggressive and highly metastatic lung cancer

subtype, accounting for about 10–20% of lung cancer cases (1,2). The 5-year survival rate has

remained dismal at 7% and systemic treatment options for patients with SCLC have remained

unchanged (3). Standard first-line treatment of SCLC includes cisplatin or carboplatin in

combination with etoposide, cyclophosphamide, vincristine, or doxorubicin, which leads to

complete remission in a vast majority of patients (4). SCLC is highly responsive to

chemotherapy at the start of treatment. However, relapse and resistance to treatment eventually

contributes strongly to poor prognosis.

Established mechanisms of chemoresistance in cancer include cellular pathways

associated with DNA damage and repair, apoptosis, NOTCH signaling and FGFR signaling

(5,6). Agents targeting these pathways that have shown promise for other tumor types have been

investigated in SCLC without demonstrable clinical benefit (7). Consequently, there is a need to

elucidate novel molecular mechanisms involved in chemoresistance in SCLC. Limited

translational success is largely attributed to the lack of sufficient tumor materials from SCLC

patients. Additionally, data on SCLC in public databases such as TGCA or oncomine is sparse.

SCLC patient derived xenografts (PDXs) have provided the best opportunity to address the

above mentioned limitations as PDXs replicate the biology and clinical properties of the original

patients’ tumors as compared to other animal models (8).

A comprehensive map of the actual proteome in SCLC, in particular chemoresistant

phenotype is still needed. Herein, for the first time we have investigated mechanisms of SCLC

chemoresistance with a focus on the cell surface proteins. We initially compared the proteomic

and metabolomic profiles of SCLC cell lines to identify molecular features associated with




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chemoresistance. MCAM was identified as a markedly overexpressed protein in SCLC

chemoresistants as well as patient tumors. MCAM is a cell adhesion molecule initially identified

as melanoma-specific cell-adhesion molecule (9). MCAM is also involved in several cellular

processes including cell invasion, migration, angiogenesis, epithelial mesenchymal transition,

immune response, and signal transduction (10). Additionally, MCAM has low expression levels

in normal tissue, primarily restricted at intracellular junctions of endothelial cells (10,11).

Previous studies have shown differential expression of MCAM in primary tumors correlated with

metastasis and poor prognosis in several cancers, showing its significant potential in cancer

therapy (12-14). Despite the identification of MCAM expression in the lung adenocarcinoma

(13), its expression and role in SCLC has not been reported yet. We further investigated the

effect of MCAM through knockdown experiments and the consequences of its overexpression on

SCLC chemoresistance and cellular functions.

Materials and Methods

Cell lines and treatment

The human SCLC cell lines H69, H82, DMS79, H209 and H196, H69AR were obtained

from the American Type Culture Collection in 2011 and 2014 respectively. All cells grew in

RPMI 1640 with 10% fetal bovine serum and a 1% penicillin/streptomycin cocktail. For stable

isotope labeling with amino acids in cell culture. Cells were allowed to grow for seven passages

in RPMI 1640 supplemented with 13C-lysine and 10% dialyzed fetal bovine serum according to a

standard protocol (15). Cell lines were cultured continuously for 6 months or less. Cell lines

were validated at the MD Anderson Sequencing and Microarray Facility using short-tandem

repeat DNA fingerprinting and routinely checked for mycoplasma by PCR (PromoKine). Cells




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were treated with 10 nM phosphoinositide 3-kinase (PI3K) inhibitor LYS294002 (Cell Signaling

Technology) for 24 hours. Accumulation of lactate in the cell culture was determined using

lactate assay kit II (Sigma-Aldrich, MAK065) according to the manufacturer's protocol.

Mass spectrometry and metabolomic analysis

Proteomic analysis of total cell extract (TCE) and cell surface proteins from SCLC cell lines was

performed using mass spectrometry as previously described (16). For metabolomic profiling all

samples were run in biological triplicates. Approximately 7.5 x 105 cells were seeded 24 hours

prior to metabolite extraction in 6 cm dishes. On day of extraction, cells were washed twice with

ice-cold 0.9% NaCl, extracted with 1mL of ice-cold 3:1 isopropanol/water mixture containing

50ng/mL internal standard (12-[[(cyclohexylamino)carbonyl]amino]-dodecanoic acid (CUDA),

Cayman Chemical), and dried using a centrifugal evaporator. Upon dryness, samples were

reconstituted in 50:50 methanol/water. Untargeted metabolomics analysis was conducted on a

Waters Acquity™ UPLC system coupled to Xevo G2-XS quadrupole time-of-flight (qTOF)

mass spectrometer. LC-MS and LC-MSe data were processed using Progenesis QI (Nonlinear,

Waters), and values were reported as area units. Details are provided in the Supplementary

Methods.

Patient tumor collection and generation of chemoresistant PDX models

Fresh SCLC cells from endobronchial ultrasound-guided transbronchial needle aspiration

(EBUS-TBNA) were obtained from the patients diagnosed with SCLC in The Kinghorn Cancer

Centre, New South Wales, Australia with informed, written consent in accordance with the

policies of the National Health and Medical Research Council of Australia, Monash Health,




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Melbourne Health and the Declaration of Helsinki. In brief, one million SCLC cells obtained

from each of 11 chemonaïve SCLC patients were centrifuged, washed, and resuspended in 50 μL

of RPMI medium. Cells were then added to 50 μL of Matrigel (BD Biosciences), gently mixed,

and kept on ice. The resulting cell suspension was injected subcutaneously into the right flanks

of nude Balb/c mice to generate PDXs. The mice were monitored daily until palpable tumors

appeared (typically 4 weeks). Tumors were measured daily using digital calipers to record the

longest (l) and shortest (s) dimensions in millimeters. The following equation was used to

calculate the tumor volume: Tumor volume = l x s2 / 2

Once tumors reached 200 mm3, mice were given single intraperitoneal injections of 60

mg/kg carboplatin. SCLC xenografts responded rapidly to this initial carboplatin-based

treatment, becoming barely palpable within 10 days. Relapse of SCLC took 50-81 days. Upon

tumor relapse in two PDX models, an additional 60 mg/kg injection of carboplatin was

administered to both when the tumors reached 200 mm3. Per national health and medical

research council ethical guidelines, a maximum of three doses of carboplatin was injected per

mouse. After the third injection of carboplatin, tumors exhibited little or no shrinkage and minor

growth delays in response to the treatment, suggesting that they were resistant to it. Mice were

then euthanized and harvested tumors were formalin fixed for paraffin embedding.

Proliferation and colony formation assays

For proliferation assays, 8 × 103 SCLC cells were seeded in triplicate and assayed using

MTS reagent (CellTiter 96 Aqueous One Solution Cell Proliferation Assay; Promega). For

colony formation assays, 200 cells were seeded in six-well plates in triplicate and allowed to




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grow for 20 days. Cells were fixed in 6% glutaraldehyde with 0.5% crystal violet and visualized

under the Nikon microscope. Colony areas were measured using the ImageJ software program.

In vitro drug sensitivity assay

SCLC cells were seeded in 96-well plates at a density of 1 × 104 cells per well and treated

in medium with doxorubicin, cisplatin, or etoposide for 24 hours. Cell survival was analyzed

using a CellTiter Glo assay (Promega) according to the manufacturer’s instructions. The range of

drug concentrations was chosen to obtain half-maximal inhibitory concentrations (IC50) values

for SCLC cell lines. After incubation with 100 μL of CellTiter Glo reagent for 10 minutes, the

luminescence was measured. Luminescence reading from the cells incubated without the drugs

were used for 100% survival and to calculate the IC50 of each drug. The data for CellTiter Glo

assay was collected from five technical and three biological replicates for each sample.

Flow cytometric analysis

SCLC cells were treated with doxorubicin, cisplatin, or etoposide for 24 hours and then

collected for apoptosis and cell-cycle analyses. For annexin V analysis, cells were incubated with

annexin V-fluorescein isothiocyanate and propidium iodide (PI) for 15 minutes at room

temperature in the dark. Samples stained with annexin V-fluorescein isothiocyanate and PI were

diluted in 400 μL of annexin V-binding buffer and immediately examined using a fluorescence-

activated cell sorting machine. Stained cells were immediately subjected to flow cytometric

analyses using a Gallios flow cytometer (Beckman Coulter). Early apoptotic cells were defined

as cells with annexin V-positive and PI-negative staining. Late apoptotic and nonviable cells

were defined as having both annexin V-positive and PI-positive staining.




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For cell-cycle analysis, SCLC cells were fixed with 70% (vol/vol) cold ethanol overnight at 4°C.

Cells were then suspended in phosphate-buffered saline buffer containing final concentrations of

20 μg/mL RNase A and 20 μg/mL PI for 20 minutes. The cell-cycle profiles for these cells were

determined using flow cytometry (Gallios; Beckman Coulter) and analyzed using the Kaluza

software program (Beckman Coulter). All samples were assayed in triplicate.

Immunohistochemistry

The paraffin embedded PDX tissues sections (5μm) on glass slides were deparaffinized

and hydrated, and antigen retrieval was performed using a decloaker with a target retrieval

solution (pH, 6.0; Dako). The intrinsic peroxidase activity was blocked using 3% methanol and

hydrogen peroxide for 10 minutes, and a serum-free protein block (Dako) was used for 5 minutes

to block nonspecific antibody binding. The slides were then incubated with antibodies against

human MCAM (ab75769, 1:200 dilution; Abcam), EGFR (ab52894, 1:100, Abcam), EPHA2

(#6997, 1:200, Cell Signaling), ITGB1 (ab52971, 1:250, Abcam) and JAG1 (ab109536, 1:100,

Abcam) overnight at 4°C. After being washed three times in Tris-buffered saline, the slides were

then incubated for 30 minutes with Dako EnVision+ Dual Link at room temperature. Slides were

incubated with Dako chromogen substrate for 5 minutes and counterstained with hematoxylin.

Formalin-fixed, paraffin-embedded, whole-section specimens with the primary antibodies

omitted were used as negative controls.

Mathematical modeling for regulation of MCAM

We developed a mathematical model that incorporates the regulations among MCAM, SOX2,

PI3K, and CREB1 and their association with chemoresistance.




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Oxygen consumption rate measurement

Oligomycin, an inhibitor of ATP synthase, was prepared from 1000× stock at a

concentration of 10 mM in dimethyl sulfoxide (DMSO). FCCP, an ionophore and strong

mitochondrial depolarizer, was prepared from 1,000 × stock at a concentration of 5 mM in

DMSO. Rotenone, a potent inhibitor of mitochondrial complex I, and antimycin A, a strong

suppressor of mitochondrial complex III, were solubilized from 1,000 × stock solutions at

concentrations of 10 mM in DMSO. To measure SCLC-cell oxygen consumption rates (OCRs),

6 × 104 cells from each cell line were seeded into each well of an XF96 microplate 16 hours

before the experiment. Immediately before the OCR measurement, culture medium of the cells

was replaced by an assay medium (low-buffered RPMI containing 25 mM D-glucose, 1 mM

sodium pyruvate, and 1 mM L-glutamine) and incubated for 1 hour at 37°C. The OCR in the

cells were measured using an Extracellular Flux Analyser (Seahorse Biosciences). After baseline

measurements of OCR the inhibitors described above prepared in the assay medium were

sequentially injected into each well to reach the final working 1× concentrations. After 5 minutes

of incubation to expose cancer cells equally to chemical inhibitors, the OCR was measured

again. Data were analyzed using the Seahorse XF software program. The OCR was reported in

pmol min−1, and measurements were normalized according to the final cell number.

Statistical analysis

All bar and line graphs represent means and standard deviations. The error bars in OCR line

graphs are standard deviations. The unpaired t-test was used to compare differences between two




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groups. For comparison of more than two groups, one-way Analysis Of Variance (ANOVA) was

used. A P value less than 0.05 was considered statistically significant. Data were analyzed using

the Prism software program (GraphPad Software) unless otherwise stated. All experiments were

independently repeated at least three times.

Supplementary Data

Supplementary Data includes supplementary methods, five figures, and two tables.

Results

Increased MCAM expression in chemoresistant SCLC

In-depth proteomic multi-compartment profiling was performed to quantify proteomic

changes associated with chemoresistance of SCLC cells (Fig. 1A). We used H69 and H69AR as

a paired SCLC chemosensitive and chemoresistant cell line. Metastasis and chemoresistance in

cancer are linked phenomena (17), hence we used H82 representing a metastatic SCLC cell line.

We also used DMS79, a SCLC cell line established from the tumor cells of a patient who had

undergone chemotherapeutic and radiation treatment, as assumed to be a surviving fraction of

primary SCLC cells and may possess some similarities to chemoresistant cells. In total, we

quantified 3,605, 3,574, 3,205, and 3,211 proteins in total cell extracts (TCE) and 2,852, 1,884,

1,981, and 2,344 proteins on the surface of the H69, H82, DMS79, and H69AR cell lines,

respectively (Supplementary Table 1).

Chemoresistant H69AR exhibited a highly distinct enriched cell surface proteome

relative to other SCLC cell lines (Fig. 1B and Supplementary Table 2), marked by a high

abundance of proteins associated with cytoskeletal reorganization as well as cell adhesion and




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PI3K/AKT-regulated pathways based on Ingenuity Pathway Analysis (Table 1 and

Supplementary Fig. 1A). Differentially expressed surface proteins in H69AR relative to H69

cells were further assessed by immunoblotting (Fig. 1C). To narrow our list of candidate targets,

we focused on cell surface receptors that exhibited the most robust differences between

chemoresistant SCLC cells compared to other cell lines. Five surface membrane receptors

(EGFR, JAG1, ITGB1, EPHA2, and MCAM) were found most highly expressed in

chemoresistant SCLC cells compared to the other cell lines (Fig. 1D). We validated our results

by immunoblotting in these SCLC cell lines also including H196, which has similar

chemoresistant properties as of H69AR, and H209, which is chemosensitive to the

chemotherapeutic drugs. Increased expression of H69AR surface enriched protein on DMS79

and H196 is in concordance to their higher IC50 values for chemotherapeutic drugs compared to

H69, H82 and H209 (Fig. 1C and Supplementary Fig. 1B and 1C). We found that DMS79 and

H196 closely related to H69AR, whereas H82 and H209 resembles H69 in terms of their surface

protein expression. Next, we examined established PDXs derived from SCLC patients for

expression of these receptors. The PDX models replicate the biology and clinical properties of

the original patients’ tumors (8). We observed increased MCAM expression in chemoresistant

tumors compared to matched treatment-naïve tumors (Fig. 1E and Supplementary Fig. 1D). We

also observed increased MCAM expression as early as after two cycles of carboplatin

(Supplementary Fig. 1E) in contrast with EGFR, JAG1, or ITGB1 which did not exhibit any

difference in immunostaining between chemonaïve and chemoresistant tumors. EPHA2 was

undetectable by immunostaining in any of the PDXs (Supplementary Fig. 1F).




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MCAM expression is associated with a mesenchymal phenotype, increased proliferation

and colony formation

MCAM expression was highly correlated with a mesenchymal transition related gene

expression pattern in SCLC cell lines annotated in the Cancer Cell Line Encyclopedia database,

(Supplementary Fig. 2A). Concordantly, we also observed altered expression of multiple

epithelial-mesenchymal transition (EMT) markers, including reduced expression of CDH1 and

NCAM and increased expression of VIM, CDH2, LGALS1, and COL1A1 (Fig. 2A) in H69AR

cells. Interestingly, LGALS1 has also been reported as a ligand for MCAM in melanoma and

endothelial cells (18,19). Ingenuity Pathway Analysis revealed Transforming growth factor β and

ZEB1 as key upstream regulators of altered gene expression in chemoresistant cells

(Supplementary Fig. 2B-D). Higher expression of the EMT regulators ZEB1 and TWIST1 in

H69AR cells compared to H69 cells was confirmed by immunoblotting (Fig. 2B).

Knockdown of MCAM expression in chemoresistant cells using RNA interference had

no effect on mesenchymal-related protein expression (Fig. 2C-E and Supplementary Fig. 3A-C).

However, MCAM knockdown in chemoresistant cells significantly decreased cell proliferation

(p < 0.001, ANOVA) (Fig. 2F and Supplementary Fig. 3D, 3E) and colony-forming rates (p <

0.01, unpaired t-test) (Fig. 2G).

MCAM expression is a determinant of SCLC chemoresistance and sensitivity

To determine the effects of MCAM expression on chemoresistance of SCLC cells, we

treated shMCAM-H69AR cells with varying doses of chemotherapeutic drugs (doxorubicin,

cisplatin, and etoposide). MCAM knockdown in chemoresistant cells increased chemosensitivity,

with significant reductions (p < 0.001, ANOVA) in the IC50 and cell survival (Fig. 3A-3D and




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Supplementary Fig. 3F, 3G). Reduced MCAM expression led to a marked increase in apoptosis

after chemotherapy as determined by flow cytometry (Fig. 3E). Immunoblotting was performed

for proteins in the apoptotic pathway. Of note, expression of p-BAD, a pro-apoptotic protein,

increased after MCAM knockdown. Additionally, cleaved caspase-3 markedly increased during

chemotherapeutic treatment confirming an apoptotic mechanism (Fig. 3F). We also observed

increased cell-cycle arrest at G0/G1 and G2/M after treatment with doxorubicin or cisplatin and

etoposide, respectively, in shMCAM-H69AR compared to H69AR (Supplementary Fig. 4A-C).

To determine whether MCAM expression is sufficient to induce SCLC chemoresistance,

we ectopically expressed MCAM in the chemosensitive H69 cell line. Overexpression of

MCAM resulted in a slight increase in the cell proliferation, however this was not statistically

significant (Fig. 4A–C and Supplementary Fig. 5A). MCAM overexpression resulted in

markedly increased chemotherapeutic IC50 values and cell survival (Fig. 3D and 4D). These

findings were corroborated by reductions in apoptosis and reduced cell cycle arrest at G0/G1 and

G/2M following treatment with doxorubicin or cisplatin and etoposide, respectively (Fig. 4E and

Supplementary Fig. 5B).

Regulation of MCAM via PI3K/AKT pathway in a SOX2/CREB1 dependent manner

PI3K/AKT signaling emerged as an upregulated pathway in chemoresistant SCLC cells

(Table 1). We tested whether MCAM regulates PI3K/AKT activation. MCAM knockdown

considerably reduced the activation state of PI3K/AKT pathway based on phosphoprotein

analysis (Fig. 5A and Supplementary Fig. 4D). Moreover, inhibition of PI3K activity using

LYS29004 markedly decreased MCAM expression suggesting a potential bidirectional

regulation (Fig. 5B). MCAM expression is known to be regulated via CREB1 (20), and CREB1




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activation is dependent on the AKT pathway (21). The gene for the transcription factor SOX2 is

frequently amplified in SCLC (22) and its expression is also regulated via AKT (23). Hence, we

examined the effect of SOX2 knockdown and PI3K inhibition on CREB1 and MCAM protein

expression levels in chemoresistant SCLC cells. Both SOX2 inhibition and LYS29004 treatment

reduced CREB1 and MCAM protein expression (Fig. 5C and 5D). However, CREB1

knockdown reduced MCAM but did not affect SOX2 expression (Fig. 5E).

Our findings led to a mathematical model for a regulatory network mediating

chemoresistance of SCLC that can behave as a bi-stable switch (i.e., cells can attain one of two

stable-steady phenotypes—chemosensitive or chemoresistant, and can transit from one to the

other based on the expression levels of SOX2 and MCAM (Fig. 5F, 5G and Supplementary

data).

Given our observation of a bidirectional regulation of MCAM and PI3K/AKT pathway

activation, we further assessed whether MCAM regulates known PI3K/AKT-regulated targets

that have been associated with chemoresistance. Of particular interest, is the ABCC transporter,

MRP1, which plays a key role in the chemoresistance of several cancers (24,25) and regulated

by PI3K/AKT (26,27). We observed markedly decreased expression of MRP1 protein following

MCAM knockdown, suggesting that MRP1 regulation is associated with MCAM expression in

chemoresistant cells (Fig. 5H).We also observed reduced levels of NRF2, a known modulator of

MRP1 in SCLC (28), in MCAM knockdown cells (Supplementary Figure 4D).

Increased lactate and low oxidative phosphorylation are key features of SCLC chemoresistance

PI3K/AKT activation promotes increased glycolysis rather than oxidative

phosphorylation in cancer (29). MRP1 is known to transport glutathione and glutathione-




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conjugates out of the cell. Thus, the association between MCAM, PI3K/AKT activation and

MRP1 inherently suggests metabolic rewiring, a characteristic that may in part be regulated by

MCAM.

To determine whether H69AR exhibited a unique metabolic profile compared to the

parental H69 cell line, we conducted Ingenuity Pathway Analysis, focusing on proteins that

exhibited at least two-fold changes in TCE and at least 5 MS/MS counts in both cell lines

(Supplementary Table 2). We found that mitochondrial dysfunction was the most altered

pathway (Fig. 6A). Moreover, many of the top perturbed pathways linked to altered metabolism

included oxidative phosphorylation, gluconeogenesis, glycolysis, pentose phosphate pathway,

and mammalian target of rapamycin signaling (Fig. 6A). We thus evaluated the basal OCRs in

the chemoresistant H69AR and other SCLC cell lines (H69, H82, and DMS79) using a Seahorse

assay (Fig. 6B). The basal OCR was significantly lower (p < 0.001, unpaired t-test) in the

chemoresistant cell line compared to the other SCLC cell lines, demonstrating that the basal

metabolic conditions in drug-resistant SCLC cell lines favor elevated aerobic glycolysis and

reduced oxidative phosphorylation. Lactate production rate was significantly higher (p < 0.001,

unpaired t-test) in H69AR cells than in H69 cells (Fig. 6C). These findings are consistent with a

shift towards a glycolytic phenotype associated with PI3K/AKT activation (29). Lactate

production decreased significantly (p < 0.01, unpaired t-test) after MCAM knockdown (Fig. 6D)

suggesting a potential shift away from glycolysis. We also observed reduced levels of

glutathione reductase (GSR), a downstream effector molecule of NRF2 in MCAM knockdown

cells (Supplementary Figure 4D).

Discussion




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The rapid emergence of chemoresistance in SCLC following treatment is a key

contributor to poor survival. Therefore, there is critical clinical need to develop novel strategies

that overcomes chemoresistance and provide significant survival benefits to patients.

Analysis of in depth proteomic profiling for TCE and cell surface enrich proteins of

SCLC cell lines revealed that the chemoresistant cells have marked distinct surface and TCE

profiles. In particular, proteins related to integrin signaling and PI3/AKT signaling such as

ITGB1, ITGB5, ITGA2, ITGA4, VCL, ZYX and CTNNB1, PP2A, GYS respectively, observed

to be upregulated in TCE as well as enriched on surface of chemoresistant cells. The integrin-

ECM interactions are a well-known phenomenon for cell survival and drug resistance in various

cancers including solid and hematological malignancies (30). On the other hand, Akt signaling

can induce transformation and renders tumor cell resistant to chemotherapeutic agent through its

anti-apoptotic activity and induction of cell cycle progression (31-33). We also observed

differential expression of proteins related to cancer stem cell (CD44, ALDH3A2, ALDH7A1,

EpCAM), EMT (CDH1, Vim, CDH2) and receptor signaling (EGFR, LGALS1, EPHA2, JAG1)

that can modulate chemoresistance in cancer cells (34-39).

Our enriched cell surface data identified MCAM among the highly differentially

upregulated surface proteins in chemoresistant compared to other SCLC cells. MCAM (also

designated as CD146 or MUC18) is a marker of endothelial cell lineage(10). One of the

limitation of our study is lack of chemoresistant tissues from SCLC patients. However, SCLC

PDX models can replicate the biology of cancer in patients and hence are superior to traditional

xenograft tumor models. We thus incorporated PDX models as a component for validation of our

proteomics data. We observed markedly increased expression of MCAM protein in

chemoresistant than in chemo-naive SCLC PDXs. Increased expression of MCAM on DMS79




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but not on H82 and on PDX tissues even after two cycles of chemotherapeutic treatment

suggested that the overexpression might be an early event for an acquired chemoresistance in

SCLC cells. MCAM overexpression has been observed in several tumor types including

melanoma, prostate, pancreatic, lung, gastric, breast, and ovarian cancers (10). Altered

expression of MCAM was associated with cell viability and colony forming abilities in SCLC

cells, which is in concordance with the reports of MCAM linked to altered cell proliferation,

angiogenesis, metastasis, cell motility and invasion (10,40,41). The modulation of

chemoresistance through altered MCAM expression is a novel finding, which may be mediated

by regulating the apoptosis related protein expression. We also observed increased LGALS1

protein levels, a known ligand of MCAM (15,16), in chemoresistant cells. MCAM and its ligand

LGALS1 has been reported to regulate apoptosis in cancer cells (18,19,42-44), which further

support our findings.

Given that SCLC is a neuroendocrine tumor type, it is noteworthy that multidrug-

resistance in SCLC was associated with an EMT phenotype suggesting that mesenchymal

transition is a potentially important mechanism of survival for chemoresistant cells in SCLC and

analysis of CCLE (45) data revealed a strong association between MCAM and EMT. Zeng et al.,

(14) demonstrated that high MCAM expression in triple-negative breast cancers induced EMT

and cancer stem cell properties. However, we observed That MCAM modulation has no

significant effect on EMT properties of SCLC cells.

In melanoma, MCAM upregulation is dependent on PI3K/AKT pathway which is a

known contributor of chemoresistance in numerous malignancies (46). However, our results

implicate that in chemoresistant SCLC cells, the relationship between MCAM and PI3K/AKT

activation is bidirectional and postulated to be mediated via SOX2/CREB1 axis. These findings




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are also in concordance with those of recent studies suggesting that SOX2 expression levels in

malignant cells are dependent on AKT regulation (47-49). However, further studies needed to

confirm this potential relationship.

To define the mechanism(s) by which MCAM can modulate chemoresistance, we

evaluated known targets regulated by the PI3K/AKT pathway. Of relevance was MRP1, which

has been previously implicated in promoting chemoresistance in numerous cancer types,

including SCLC (26,50). Knockdown of MCAM reduced MRP1 expression. MRP1 has a high

affinity for exporting glutathione-conjugated metabolites and drugs (51). Multidrug-resistant

H69AR cells exhibited greater Nrf2 activation than H69 cells and its expression is associated

with MRP1 regulation (28). Nrf2 regulates a number of metabolic pathways, including the

induction of antioxidant pathways including the glutathione pathway, as well as NADPH

production through G6PD, the rate-limiting enzyme in the pentose phosphate pathway (52).

Thus, the observed reduction in MRP1, NRF2 and its downstream effector glutathione reductase

due to MCAM knockdown suggests that MCAM works in concert with altered Nrf2 activation, a

notion that is supported by the observation that activation of the PI3K/AKT pathway promotes

Nrf2 activation in other cancer types (53). In the present study, comparison of the proteome of

chemoresistant to other SCLC cell lines revealed perturbations in various metabolic pathways,

highlighted by dysregulation of mitochondrial function, gluconeogenesis, glycolysis, and the

pentose phosphate pathway. Consistently, chemoresistant cells exhibited reduced basal oxygen

consumption, elevated lactate production consistent with increased aerobic glycolysis, and

reduced oxidative phosphorylation. Collectively, these findings implicate a metabolic rewiring of

glucose metabolism and redox status, both of which inherently linked to PI3K/AKT and Nrf2-

activation (29,46,53). Notably, lactate production reduced upon MCAM knockdown implicating




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a reduction in glucose catabolism through the glycolytic pathway. Further studies, including

stable isotope tracer studies, will be required to elucidate the role of MCAM in modulating

cancer cell metabolism; however, these remain outside of the immediate scope of this study.

Our findings point to an important role for MCAM in SCLC chemoresistance. Moreover,

targeting surface MCAM may serve as a novel therapeutic strategy to combat chemoresistance

by modulating the activity and expression of PI3K, Nrf2 and MRP1, well documented and

interconnected contributors of drug resistance.

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Table 1. Dysregulated pathways and their associated proteins in chemoresistant cells.

MAPK, mitogen-activated protein kinase; NF, nuclear factor; TGF, transforming growth factor.

Related pathways Mass Spec Counts

Symbol Gene name Upregulated H69AR H69 H82 DMS79 Fold change

ITGB1 integrin, beta 1 Integrin and PI3/AKT signaling 242 89 86 144 2.73

COL1A1 collagen, type I, alpha 1 PI3/AKT signaling 221 0 0 8 22071.00

EIF4A1 eukaryotic translation initiation factor 4A1 TGF-beta 207 19 8 25 11.11

RPL3 ribosomal protein L3 Infectious diseases 148 0 0 9 14771.00 COL1A2 collagen, type I, alpha 2 PI3/AKT signaling 147 4 0 32 34.09

MCAM melanoma cell adhesion molecule Cell adhesion 135 20 51 107 6.73

ATIC IMP cyclohydrolase Purine biosynthesis 125 12 9 22 10.29

LGALS1 lectin, galactoside-binding, soluble, 1

NF-kappaB and MAPK signaling 116 3 0 3 40.34

JAG1 jagged 1 Notch signaling 114 0 3 0 11406.00

EPHA2 EPH receptor A2 PI3/AKT signaling 98 0 0 3 9752.00

Downregulated

LMNB2 lamin B2 PI3-AKT signaling 24 256 110 210 0.09

NCAM1 neural cell adhesion molecule 1 Cell adhesion 13 342 177 268 0.04

SYNE2 spectrin repeat containing, nuclear envelope 2 Cell cycle 10 115 1 122 0.08

TGM2 transglutaminase 2 Phospholipase-C and CREB 2 111 0 1 0.02

CNTN1 contactin 1 Notch signaling 1 323 88 0 0.00

NCAM2 neural cell adhesion molecule 2 Cell adhesion 0 106 0 6 0.00

FLNB filamin B, beta MAPK signaling 0 156 0 0 0.00 ACTA1 actin, alpha 1, skeletal muscle AKT signaling 0 160 0 0 0.00

CES1 carboxylesterase 1 Xenobiotic metabolism 0 174 0 3 0.00

ALCAM activated leukocyte cell adhesion molecule Cell adhesion 0 191 23 298 0.00




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Figure legends:

Figure 1: MCAM in SCLC chemoresistant cells. A) Schematic diagram of the proteomics

workflow. B) Heatmap cluster of SCLC cell line surface proteins in H69AR compared to other

SCLC cell lines. C) Immunoblot of differentially expressed proteins on cell surface of H69AR

compared to other SCLC cell lines. D) Bar chart of Mass Spec (MS) counts for five most

abundant cell surface receptors on H69AR compared to other SCLC cell lines. E) Schematic

diagram of chemoresistant tumor formation in SCLC PDX models. Highly abundant expression

of MCAM in chemoresistant compared to their respective naïve PDX tissues. Representative

images of MCAM immunohistochemistry at 20X (scale bar is 100μm) and 40X (scale bar is

50μm) magnification.

Figure 2: Effect of MCAM knockdown on SCLC chemoresistant cells with mesenchymal

phenotype. A) Bar chart for Mass Spec (MS) counts of mesenchymal related proteins in SCLC

cell lines. B) Immunoblot for epithelial to mesenchymal transition related proteins and

transcription factors. C and D) Knockdown efficiency of shRNAs for MCAM at transcriptional

(C) and translational (D) levels Data were pooled from three biological replicates (n = 3). E)

Highly efficient reduction of MCAM protein on cell surface after MCAM knockdown was

observed using flow cytometry. F) Stable knockdown of MCAM statistically significantly (p <

0.01, ANOVA) reduced the cell proliferation in chemoresistant H69AR cells Data were pooled

from three biological replicates (n = 3). G) H69AR cells statistically significantly (p < 0.01,

unpaired t-test) lost their colony forming abilities after stable knockdown of MCAM. Colonies




25

were stained with crystal violet. Error bars represent means ± SD from three biological replicates

(n = 3). *p < 0.05, **p < 0.01, ***p < 0.001 vs. control shRNA group.

Figure 3: Effect of MCAM knockdown on SCLC chemoresistance. A-C) The cell

proliferation rate were measured using CellTiter Glo assay. Data were pooled from three

biological replicates (n = 3) Values are presented as percentage of cell proliferation in

doxorubicin (A), cisplatin (B) and etoposide (C) treated and untreated cells. *P < 0.001 (one-way

ANOVA; compared with corresponding negative control groups). D) Bar graph representing

effect of MCAM modulation on drug sensitivity of SCLC cell lines. Data were pooled from three

biological replicates (n = 3)). E) MCAM knockdown increased cell apoptosis in SCLC cells after

chemotherapy (n = 3). Representative FACS profiles shown, on which cell population in the

quadrant of Annexin V± DAPI represents apoptotic cells. F) Chemoresistant H69AR cells

(parental and MCAM knockdown clones) were treated with doxorubicin (170 μM) for 24 hours,

and cell lysates were immunoblotted for MCAM, pBAD and cleaved caspase 3.

Figure 4: Effect of MCAM overexpression on SCLC chemoresistance. A and B) Efficient

overexpression of MCAM in H69 cells both at transcriptional (A) and translational (B) level.

Data were pooled from three biological replicates (n = 3) Error bars represent means ± SD; ***p <

0.001. C) Increased MCAM expression on cell surface after MCAM overexpression was

confirmed by flow cytometry. D) The cell proliferation rate were measured using CellTiter Glo

assay. Values are presented as percentage of cell proliferation in doxorubicin, cisplatin,

etoposide-treated and untreated cells (n = 3). E) MCAM overexpression markedly decreased cell




26

apoptosis in SCLC cells after chemotherapy. Representative FACS profiles are shown, on which

cell population in the quadrant of Annexin V± DAPI represents apoptotic cells.

Figure 5: Regulation of MCAM expression in SCLC chemoresistant cells. A and B) Lysates

from H69AR cells treated with either shMCAM (A) or PI3K inhibitor LYS29004 for 24 hours

(B) were immunoblotted with the indicated antibodies and revealed an inhibited PI3K/AKT

pathway. C-E) Lysates from H69AR cells treated with siSOX2 for 72 hours (C), LYS29004 for

24 hours (D) and siCREB1 for 72 hours (E) were immunoblotted for MCAM, CREB1 and

SOX2. F) Proposed regulatory network for chemoresistance in SCLC. G) Mathematical model of

the network denoting two stable steady states (phenotypes) – chemosensitivity for (low MCAM,

low SOX2) and chemoresistance for (high MCAM, high SOX2) shown by filled circles. The

hollow circle denotes unstable steady state. The red and blue curves are the nullclines denoting

the impact of model variables on MCAM and SOX2 respectively. H) MRP1 expression in

H69AR cells with stable MCAM knockdown.

Figure 6: Effect of MCAM on SCLC metabolism. A) Top perturbed pathways in ingenuity

pathway analysis linked to altered metabolism in SCLC chemoresistant cells. B) OCR

(pmol/min) in SCLC cells measured by a Seahorse Analyser. Basal measurements were

normalized for cell number and protein concentrations. C) Lactate concentration compared

between H69 sensitive and H69AR chemoresistant cells. D) Lactate concentration was assessed

in stable knockdown of MCAM in H69AR chemoresistant cells. Unpaired t-test was used to

calculate significance. Error bars represent means ± SD from triplicates or three independent

experiments. **p < 0.01, ***p < 0.001.




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Published OnlineFirst June 23, 2017.Cancer Res Satyendra C. Tripathi, Johannes F Fahrmann, Muge Celiktas, et al. the PI3K/AKT/SOX2 signaling pathwayMCAM mediates chemoresistance in small cell lung cancer via

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