loss-of-functionmutationsincalcitoninreceptor calcr ... · tumor-suppressive function of the gene,...

Biology of Human Tumors

Loss-of-FunctionMutations inCalcitoninReceptor(CALCR) Identify Highly Aggressive Glioblastomawith Poor OutcomeJagriti Pal1, Vikas Patil1, Anupam Kumar2, Kavneet Kaur2, Chitra Sarkar2, andKumaravel Somasundaram1

Abstract

Purpose: Despite significant advances in the understanding ofthe biology, the prognosis of glioblastoma (GBM) remains dis-mal. The objective was to carry out whole-exome sequencing(WES) of Indian glioma and integrate with that of TCGA to findclinically relevant mutated pathways.

Experimental Design: WES of different astrocytoma samples(n¼ 42; Indian cohort) was carried out and comparedwith that ofTCGA cohort. An integrated analysis of mutated genes fromIndian and TCGA cohorts was carried out to identify survivalassociation of pathways with genetic alterations. Patient-derivedglioma stem-like cells, glioma cell lines, and mouse xenograftmodels were used for functional characterization of calcitoninreceptor (CALCR) and establish it as a therapeutic target.

Results: A similar mutation spectrum between the Indiancohort and TCGA cohort was demonstrated. An integrated anal-ysis identified GBMs with defective "neuroactive ligand–receptor

interaction" pathway (n¼ 23; 9.54%) that have significantly poorprognosis (P < 0.0001). Furthermore, GBMs with mutated calci-tonin receptor (CALCR) or reduced transcript levels predictedpoor prognosis. Exogenously added calcitonin (CT) inhibitedvarious properties of glioma cells and pro-oncogenic signalingpathways in a CALCR-dependent manner. Patient-derived muta-tions in CALCR abolished these functions with the degree of lossof function negatively correlating with patient survival. WTCALCR, but not the mutant versions, inhibited Ras-mediatedtransformation of immortalized astrocytes in vitro. Furthermore,calcitonin inhibited patient-derived neurosphere growth andin vivo glioma tumor growth in a mouse model.

Conclusions: We demonstrate CT–CALCR signaling axis isan important tumor suppressor pathway in glioma and establishCALCR as a novel therapeutic target for GBM. Clin Cancer Res; 24(6);1448–58. �2017 AACR.

IntroductionGlioblastoma (GBM) is the most common and highly aggres-

sive adult primary brain tumor. GBMs show a significantamount of proliferation, invasion, angiogenesis, necrosis, andare also treatment refractory. Each GBM tumor carries anamalgamation of genetic alterations that determine cancerprognosis and response to therapy. Intensive studies on can-didate genes show various genetic alterations typical to GBM,for example, TP53 mutation and loss, EGFR amplification andmutation, PTEN mutation and loss, etc. (1). In recent times,two independent groups have carried out whole-exome (WES)and RNA sequencing analysis of GBM tissue samples from TheCancer Genome Atlas (TCGA) and have found out variousnovel genetic alterations that may play an important role in

GBM pathogenesis (2, 3). From these studies, it is evident thatthree pathways, receptor tyrosine kinase (RTK), TP53, and RB,are significantly altered in GBM tumor by mutations or copynumber alterations. However, even with the increase in ourunderstanding of the tumor, advancement in therapeutics isminimal, and the median survival still remains at 15 to 17months only (4). Hence, we need to elucidate novel alteredmolecules and pathways in GBM such that more effectivetherapeutic possibilities can be explored.

With this objective, we propose to understand the geneticspectrum of patients with astrocytoma throughWES to find noveltargetable pathways in GBM. In this study, we performed inte-grated analysis ofmutated genes fromour Indianpatient cohort aswell as TCGA cohort to find out mutated pathways that predictsurvival in patients with GMB. This analysis revealed neuroactiveligand–receptor interaction pathway to be the most significantpathway that predicts poor survival. We characterized calcitoninreceptor (CALCR), a member of this pathway, and demonstratedthe tumor suppressor role of this gene in GBM. Furthermore, wefound that mutational inactivation of CALCR abrogated thistumor-suppressive function of the gene, making glioma cellsmore aggressive.

Materials and MethodsCollection of patient tumor sample and blood

Tumor and matched blood samples from patients were col-lected from All India Institute of Medical Sciences (AIIMS, Delhi,India). Tumor samples were resected in the neurosurgical room,

1Department of Microbiology and Cell Biology, Indian Institute of Science,Bangalore, India. 2Department of Pathology, All India Institute of MedicalScience, New Delhi, India.

Note: Supplementary data for this article are available at Clinical CancerResearch Online (http://clincancerres.aacrjournals.org/).

J. Pal and V. Patil contributed equally to this article.

CorrespondingAuthors:Kumaravel Somasundaram, Indian Institute of Science,Sir C.V. Raman Road, Bangalore, Karnataka 560 012, India. Phone: 9180-2293-2973; Fax: 9180-2360-2697; E-mail: [email protected], and Chitra Sarkar,[email protected]

doi: 10.1158/1078-0432.CCR-17-1901

�2017 American Association for Cancer Research.

ClinicalCancerResearch

Clin Cancer Res; 24(6) March 15, 20181448

on December 16, 2020. © 2018 American Association for Cancer Research.clincancerres.aacrjournals.org Downloaded from

Published OnlineFirst December 20, 2017; DOI: 10.1158/1078-0432.CCR-17-1901

http://crossmark.crossref.org/dialog/?doi=10.1158/1078-0432.CCR-17-1901&domain=pdf&date_stamp=2018-3-12

http://clincancerres.aacrjournals.org/

and a portion was snap-frozen in liquid nitrogen, and stored at�80�C. In addition, blood samples collected from each patientwere snap-frozen and stored at �80�C. The remaining portion ofthe tissue was fixed in 10% buffered neutral formalin, processedfor paraffin sections, and was used for histopathology and IHC.For RNA isolation, fresh tissue was snap frozen in RNAlater.Normal brain tissue was collected within 3 to 4 hours after deathfrompatients who died fromnonhead injury/non-CNS disorders.The study has been ratified by the ethics committee of the AIIMSand Indian Institute of Science (IISc), and patient consent wasobtained as per the Institute Ethical Committee guidelines.

Cell lines, plasmid constructs, and siRNAThe GBM cell lines, LN229, LN18, T98G, U251, U87, U343,

and U373, were obtained from Sigma Aldrich. The immortalizedhuman astrocyte cell line IHA (NHA-hTERT-E6/E7) was obtainedfromDr. Russell Pieper's laboratory, University of California, SanFrancisco (San Francisco,CA). The immortalizedhumanastrocytecell line SVG was obtained from Dr. Abhijit Guha's laboratory,University of Toronto (Toronto, Canada). The immortalizedmouse astrocytic cell line, IMA2.1, was a kind gift from Dr. StefanSchildknecht, University of Konstanz, (Konstanz, Germany). Allthe cells were cultured in DMEM supplemented with 10% FBS.The cells were grown at 37�C in 5% CO2. Dr. Hiroaki Wakimoto,Brain Tumor Research Center, Massachusetts General Hospital(Boston, MA), kindly provided us with the glioma stem-likecell (GSC) lines MGG4, MGG6, MGG8, and MGG23. TheGSC, 1035 (or SK1035), was a kind gift from Dr. Santosh Kesari,Pacific Neuroscience Institute (Santa Monica, CA). The GSCswere cultured in Neurobasal medium supplemented with 0.5mmol/L L-glutamine, 20 ng/mL EGF, 20 ng/mL FGF, 40 mg/mLheparin, and B-27 and N-2 supplements. The cells were grownat 37�C in 5% CO2. The plasmid pPM-C-HA-CALCR wasobtained from Abmgood (catalog No. PV007283). The constructused contained transcript variant 2 of CALCR (transcript ID:ENST000009994441), and one of the eight mutations detected(chr7:93091387) was not present, and hence, its effect wasnot tested. Mutated CALCR was generated by site-directed

mutagenesis (SDM) using QuikChange Multi Site-DirectedMutagenesis Kit (catalog No. 200515). The vector control (VC)plasmid was created by expelling out the CALCR open readingframe using restriction enzymes NheI and XhoI. The overhangswere end filled and ligated to generate the VC plasmid. TheshRNA plasmid constructs against RAMP1 (TRCN0000273872,TRCN0000273874, and TRCN0000273814) were obtained as akind gift from Dr. Subba Rao and Dr. Saini from MISSIONshRNA Library (Sigma Aldrich). RasV12 (KRas) constructwas a kind gift from Dr. Annapoorni Rangarajan (IISc). Cellswere transfected with Lipofectamine 2000. For selection ofstable clones of CALCR and shRNA plasmid constructs,G418 (500–1,000 mg/mL) or puromycin (1–2 mg/mL), respec-tively, were added in the complete medium and selectedfor 1 to 2 weeks. ON-TARGETplus Human CALCR (799)siRNA – SMARTpool (5 nmol/L) was obtained from Dharma-con (catalog No. L-003635-00-005), and for each experiment,100 nmol/L siRNA was transfected using DharmaFECT trans-fection reagent.

Other methods are provided in Supplementary Methods.

ResultsIntegrated analysis of Indian and TCGA GBM exome identifiespathways with prognostic value

We have carried out WES of 42 astrocytoma tissues of Indianorigin (10 grade 2, 13 grade 3, and 19 grade 4/GBM) andmatchedperipheral blood samples (Supplementary Table S1). An averageof 40� 17� coveragewas obtained across all samples (for details,please see Supplementary Information). The matched tumorblood sequences were analyzed using MuTect tool (5) and Inde-locator (6) to identify tumor-specific nonsynonymous single-nucleotide variants and insertions/deletions (indels), respectively(Supplementary Tables S2–S4). The genetic spectrum of ourpatient cohort (Indian cohort) was explored through the analysisof top mutated genes, chromatin modifiers, and DNA repair–related genes that are known tobemutated inGBMasper previousreports (Supplementary Fig. S1A–S1C; ref. 3). As observed before,TP53 was found to be highly mutated across all grades of astro-cytoma with higher percentage of mutation (65%) in lower gradesamples/LGGs (grade 2 and 3) comparedwith GBM (32%; ref. 7).Other top mutated genes in GBM as per TCGA study, such asPTEN, PIK3CA, and NF1, were also found to be mutated in GBMsamples in an Indian cohort (3).We also found IDH1andATRX tobe mutated typically in the LGGs as shown before (8, 9). Tocompare the mutation spectrum of the Indian cohort with that ofTCGA, the three signaling pathways that were found to be signif-icantly altered in patients with GBM, the RTK pathway, the TP53pathway, and the RB pathway (3), were considered. The analysisrevealed that the Indian patient cohort behaves largely similar toTCGA cohort (Supplementary Fig. S1D).

To identify the defective pathways with genetic alterations inGBM that predict survival, an integrated analysis involving GBM-specificmutated genes derived from Indian andTCGAexomedatawas carried out (for details, please see Supplementary Fig. S2A;Supplementary information). Of the several pathways carryinggenetic alterations found in GBM, Cox regression analysisrevealed that 62 pathways predict survival in GBM significantly(Supplementary Fig. S2A; Supplementary Table S5). As expected,this list containedmanypathways thatwere previously implicatedin GBM survival like PI3K–Akt signaling, Ras signaling, mTOR

Translational Relevance

The advancement in effective therapeutics for glioblastoma(GBM) has been minimal, and the median survival stillremains at 15 to 17 months only. Hence, there is a need toelucidate novel altered molecules for effective therapeuticpossibilities. In this study, we explore the mutation spectrumof patients with GBM to unearth novel pathways altered bymutation that predict survival in patients, which revealedneuroactive ligand–receptor interaction pathway to be themost significant. Calcitonin receptor (CALCR), the mostmutated gene in this pathway, was studied further, whichrevealed this receptor to be tumor suppressive in nature, andactivation of it by its ligand, calcitonin, led to a decrease intumorigenic properties of glioma cells. Moreover, CALCRinhibited transformation of astrocytes in vitro, glioma stem-like cell growth, and in vivo glioma tumor growth in mice.Hence, GBMs with wild-type CALCR, calcitonin, which isprescribed for postmenopausal osteoporosis, could be con-sidered as a treatment option.

CALCR Mutations Predict Poor Prognosis in GBM

www.aacrjournals.org Clin Cancer Res; 24(6) March 15, 2018 1449




signaling, insulin signaling, focal adhesion, and regulation ofactin cytoskeleton (Supplementary Table S5). However, the topfive pathways that predicted survival with very high significancewere not reported previously for their association with GBMsurvival (Fig. 1A). The "neuroactive ligand–receptor interactionpathway" is particularly notable as GBMs with defect in thispathway (mutation in at least one of the genes) have a poormedian survival (3.13months; P<0.0001; Fig. 1B) and it is highlymutated in both TCGA and Indian cohorts (SupplementaryTables S6 and S7, respectively). Multivariate Cox regression anal-ysis with age, G-CIMP methylator phenotype, MGMT promotermethylation, and IDH1 mutation status revealed that the neuro-active ligand–receptor interaction pathway is an independentpredictor of survival in GBM (Fig. 1C).

Mutation or reduced transcript levels of CALCR predicts poorsurvival in GBM

To gain biological insight into the prognostic association ofneuroactive ligand–receptor pathway,we choseCALCR for furtherstudies, as it was found to be the top mutated gene (Supplemen-tary Table S8). The location and nature of the eight tumor-derivedmutations in CALCR is shown (Supplementary Fig. S2B). Uni-variate Cox regression analysis revealed that mutation in CALCRpredicted poor survival in patients with GBM (SupplementaryFig. S2C). Furthermore, Kaplan–Meier survival analysis revealedthat GBMs with mutation in CALCR survived lesser (Fig. 1D;median survival ¼ 4.83 months). Multivariate Cox regressionanalysis with other markers, such as age, IDH1 mutation, andG-CIMP status, revealed CALCR mutation to be an independent

D

G

Normal GBM-5

-4

-3

-2

-1

0

1

Log 2

ratio

Indian cohort

**

E

HF

I K

IHA

SVG

U87

LN22

9

T98G

U37

3

U34

3

CALCR

Actin

Immortalized astrocytic cell

line GBM cell line

Low expression (n = 259)Median survival = 12.77 months

High expression (n = 259)Median survival = 15.03 monthsP = 0.001

0 50 100 1500

20

40

60

80

100

Overall survival (months)

Perc

ent s

urvi

val

TCGA Affymetrix

Low expression (n = 61)Median survival = 14.47 months

Overall survival (months)0 20 40 60 80

0

20

40

60

80

100

High expression (n = 19)Median survival = 25.13 months

Perc

ent s

urvi

val

P = 0.003

GSE7696 JLow expression (n = 11)Median survival = 13.1 monthsHigh expression (n = 27)Median survival = 19.43 months

0 10 20 30 40 50 600

20

40

60

80

100

Perc

ent s

urvi

val

P = 0.006


Indian cohort

Low expression (n = 107)Median survival = 11.9 monthsHigh expression (n = 428)Median survival = 14.6 months

Perc

ent s

urvi

val


TCGA Agilent

0 20 40 60 80 100 120 1400

20

40

60

80

100

P = 0.018

L

0 2 4 6 8 10 12 14 16 18 20

Neuroactive ligand−receptorinteraction

Oxytocin signaling pathway

RNA Transport

cGMP−PKG Signaling pathway

Th17 Cell differentiation

- Log10 PC

A7.48

5.52

6.54

7.19

7.33

Log 2

ratio

GBM cell lineImmortalized astrocytic cell line

-3

-2

-1

0

1

2

IHA

SVG

U87

LN22

9

T98G

U37

3

U34

3

***

B6

Normal GBM Normal GBM Normal GBM-4

-2

0

2

4

TCGA Agilent

TCGA Affymetrix

GSE7696

** *** *

Log 2 ra

tio

P < 0.0001


Neuroactive ligand-receptorinteraction pathway

0 10 20 30 40 50 60 700

20

40

60

80

100

Perc

ent s

urvi

val

Altered (n = 23)Median survival = 3.13 months

Wild type (n = 218)Median survival =14.73 months

P = 0.009


Perc

ent s

urvi

val

0 10 20 30 40 50 60 700

20

40

60

80

100CALCR

Altered (n = 7)Median survival = 4.83 months

Wild type (n = 234)Median survival = 13.93 months

Factor No. of patients

HR B coefficient

P

I. Univariate analysis TCGA dataset

Neuroactive$

II. Multivariate analysis with TCGA dataset

III. Multivariate analysis of all the markers in TCGA dataset

-

Figure 1.

Clinical significance of neuroactive ligand–receptor interaction pathway and CALCR in GBM. A, Top significant mutated pathways (with �5% genes mutatedand �5% samples mutated) that predict poor survival in GBM as per univariate and Kaplan–Meier survival analyses. The log (base 10) of the P value is plottedon the x-axis. The number on the right of each bar represents the percentage of genes mutated in the corresponding pathway. B, Kaplan–Meier survivalanalysis of GBMs stratified by the genetic status of neuroactive ligand–receptor interaction pathway. "Altered" refers to patients having mutation in one ormore of the genes in the pathway. C, Multivariate Cox regression analysis of neuroactive ligand–receptor interaction pathway (denoted by $) with age, G-CIMPmethylation, MGMT promotermethylation, and IDH1mutation status.D,Kaplan–Meier survival analysis of GBMs stratified by CALCRmutation status. Note: Althoughthere were 8 patients with mutation found in the analysis, only 7 patients had survival information. E, RNA levels of CALCR from microarray data in TCGAAgilent, TCGA Affymetrix, and GSE7696 datasets. F, Real-time qPCR analysis of RNA levels of CALCR in the Indian patient cohort (control¼ 5; GBM¼ 20). Kaplan–Meier survival analysis of GBM samples expressing high versus low CALCR RNA levels in –TCGA Agilent data (G), TCGA Affymetrix data (H), GSE7696 data (I), andIndian patient cohort (J). K, RNA levels of CALCR in glioma-derived cell lines compared with immortalized astrocytes. L, Protein levels of CALCR in glioma-derivedcell lines versus immortalized astrocytes. The P values for panels A–K are represented by � , �� and �� , which denote P values of <0.05, 0.01, and 0.001, respectively.

Pal et al.

Clin Cancer Res; 24(6) March 15, 2018 Clinical Cancer Research1450




prognosticator. On comparison with MGMT promoter methyla-tion status, CALCR mutation showed a trend toward predictingpoor survival with near significant P value (P¼ 0.075). However,CALCR mutation status lost its significance in multivariate anal-ysis involving all prognostic markers (Supplementary Fig. S2C),which could be due to the fact that there were fewer number ofpatients with CALCRmutations. We evaluated the distribution ofCALCR-mutated GBM samples with respect to highly mutatedgenes inGBM(TP53, PTEN, EGFR, PDGFRA,NF1, and IDH1) andGBM subtypes (G-CIMP, MGMT, classical, mesenchymal, neural,and proneural). Although there was enrichment of CALCRmuta-tion in patients with wild-type (WT) NF1, PDGFRA, EGFR, andIDH1, odds ratio testing for mutual exclusivity showed no sig-nificant correlation/mutual exclusivity between CALCRmutationand any of the highly mutated genes or the different GBMsubtypes (Supplementary Table S9).

Additional investigation revealed CALCR transcript levelsare downregulated in GBMs derived from TCGA, GSE7696,and Indian cohorts (Fig. 1E and F). Kaplan–Meier survivalanalysis revealed that GBMs with low levels of CALCR tran-script have a poor survival in TCGA, GSE7696, and Indiancohort (Fig. 1G–J). Furthermore, we found that glioma-derivedcell lines have reduced CALCR transcript and protein levelscompared with immortalized astrocytes (Fig. 1K and L). Fromthese results, we conclude that CALCR may function as atumor suppressor gene in GBM and either mutational inacti-vation or reduced transcript levels lead to a highly aggressiveGBM with poor survival.

CALCR is a tumor suppressor in GBMCALCR is a G-protein–coupled receptor (GPCR) with an

N-terminal ligand-binding domain, a seven-pass transmembranedomain, and a C-terminal domain (10). When its ligand, calci-tonin (CT), binds to the N-terminal domain, the receptor under-goes conformational change that leads to activation of G-proteina present at the C-terminal cytosolic side, which leads to theregulation of various downstream signaling pathways, thus affect-ing a variety of functions (11). To test the function of CT–CALCRsignaling in glioma, we used various glioma-derived establishedcell lines, wherein the WT status of CALCR was confirmed (Sup-plementary Fig. S2D; refs. 12, 13). We first used LN229 gliomacells, which express relatively high levels ofCALCR (Fig. 1K andL).The effects of exogenously added calcitonin on various cancercell–associated properties of empty vector (VC)-stable andCALCR-stable LN229 cells were tested (Fig. 2A). Exogenousaddition of calcitonin inhibited colony formation, proliferation,migration, invasion, and anchorage-independent growth ofLN229/VC stable cells very efficiently (Fig. 2B–F). LN229/CALCRstable cells also showed significant reduction in these propertiescompared with LN229/VC stable cells (Fig. 2B–F). Moreover,exogenously added calcitonin inhibited all the above propertiesof LN229/CALCR stable cells even more efficiently than LN229/VC stable cells (Fig. 2B–F). Similar results were obtained inCALCR-expressing cell lines T98G and U87 (Supplementary Fig.S3A–S3C and S3D–S3F, respectively). These results suggest thatcalcitonin inhibits tumorigenic properties of glioma cells in aCALCR-dependent manner. Furthermore, to test the importanceof CALCR in calcitonin-mediated functions in glioma cells, theeffect of calcitonin in CALCR-silenced LN229, T98G, and U87cells was evaluated. The inhibition of proliferation andmigrationby calcitonin seen in nontargeting siRNA transfected cells (siNT)

was significantly abrogated in CALCR siRNA transfected cells(siCALCR; Fig. 2G–I; Supplementary Fig. S4A–S4D).

To study the importance of CALCR for calcitonin functions, theeffect of calcitonin on CALCR-low cell lines (U343 andU373; Fig. 1K and L) was also tested. Calcitonin showed eitherno or very minimal effect on colony formation, proliferation,migration, invasion, and anchorage-independent growth ofU343/VC stable cells (Supplementary Fig. S5A–S5F), which couldbe due to low expression of CALCR in these cells. U343/CALCRstable cells showed significant reduction in the above propertiescompared with U343/VC stable cells (Supplementary Fig. S5B–S5F), suggesting the fact that mere overexpression of the receptoris able to inhibit these functions. Furthermore, exogenouslyadded calcitonin inhibited the above properties of U343/CALCRstable cells very efficiently compared with that of U343/VCcells (Supplementary Fig. S5B–S5F). Similar results were obtainedin U373 cell line, which also expresses low levels of CALCR(Supplementary Fig. S6A–S6C). These results demonstrate thatcalcitonin inhibits various properties of cancer cells in a CALCR-dependent manner.

To address the signalingdownstreamofCT–CALCRcascade,weinvestigated the status of AKT, ERK, and JNK signaling, whichare known to regulate various properties of cancer cells (14). Theexogenously added calcitonin efficiently reduced the pAKT,pERK, and pJNK levels in U343/CALCR stable cells but not inU343/VC cells. This reduction in pAKT, pERK, and pJNK levelswas seen in both LN229/VC stable and LN229/CALCR stable cells(Fig. 3A). Furthermore, silencing CALCR in LN229 cells efficientlyreversed the inhibition by calcitonin on AKT, ERK, and JNKsignaling pathways (Fig. 3A). Receptor activity–modifying pro-teins (RAMP1, RAMP2, and RAMP3) are single-transmembraneproteins that induce trafficking of CALCR, thereby regulating CT–CALCR signaling cascade (15). We found that RAMP1 transcriptlevels, but not RAMP2 and RAMP3, are higher in LN229 cellswhere mere addition of calcitonin inhibits various cancer cellproperties (Fig. 3B). To know the role of RAMP1 in CT–CALCRsignaling cascade, we tested the ability of calcitonin to inhibitcolony formation and proliferation of glioma cells in RAMP1-silenced condition (shRAMP1) in the absence or presence ofexogenously expressed CALCR (Fig. 3C). Calcitonin inhibitedboth functions equally efficiently in shNT and shRAMP1 condi-tions of LN229/VC, and this inhibition was enhanced in LN229/CALCR cells, although similar in shNT versus shRAMP1 condition(Fig. 3D and E; Supplementary Fig. S6D). Collectively from theseresults, we conclude that CT–CALCR signaling acts as a tumorsuppressor pathway as it inhibits various properties of cancer cellsby inhibiting AKT, ERK, and JNK pathways and RAMPs are notrequired for CT–CALCR signaling cascade in glioma.

Patient-derived mutations abolish tumor-suppressivefunctions of CALCR

Because our study finds GBMs with CALCR mutations to bemore aggressivewith lessermedian survival, we hypothesized thatmutationsmight have abolished the tumor-suppressive functionsof CALCR. To test this possibility, each of the seven mutationswere introduced into CALCR through site-directed mutagenesis(Fig. 4A) and the ability of exogenously expressedCALCRmutantsby themselves as well as in conjunctionwith calcitonin on variouscancer cell properties in U343 and LN229 glioma cells wasevaluated. We introduced empty vector (VC), WT, and each ofthe mutant CALCR constructs into U343 and LN229 cells and






assessed the effect on glioma cell proliferation, colony formation,migration, invasion, and anchorage-independent growth in thepresence and absence of calcitonin. Although the WT CALCRoverexpression (please see "BSA" condition) inhibited glioma cellproliferation, colony formation,migration, invasion, and anchor-age-independent growth efficiently, CALCR mutants failed toinhibit these functions significantly, although to varying extentsin both U343 and LN229 glioma cells (Fig. 4B–F; SupplementaryFigs. S7A–S7E and S8A–S8H). Similarly, exogenously addedcalcitonin by itself (in LN229 cells) and in the presence of WTCALCR (in LN229 and U343 cells) inhibited all five propertiesvery efficiently. However, the inhibition by calcitonin wassignificantly abrogated in LN229 and U343 CALCR-mutantstable clones although to varying extents (Fig. 4B–F; Supplemen-tary Figs. S7A–S7E and S8A–S8H). The loss of function (LOF) wasprofound in CALCR mutants, A51T, V250M, A307V, and R420C("severe mutants"), whereas it was minimal in CALCR mutants,

R45Q, P100L, andR404C ("mildmutants"). To assess the effect ofvarying LOF by different CALCR mutants on tumor aggres-siveness, we generated LOF score by combining the level of LOFfor five different properties in each cell line, and this was finallycorrelated with GBM patient survival (for details, please seeSupplementary Information). The analysis revealed that thesevere mutants had higher LOF score, whereas the mild mutantshad a lower LOF score (Supplementary Table S10). In comparisonwith patient survival, there was significant negative correlationbetween LOF score and survival (Fig. 4G; SupplementaryFig. S7F).

To address whether the LOF shown by CALCR mutants is dueto their inability to inhibit downstream signaling pathwaysunlike WT CALCR, we assessed the effect of CALCR mutationson downstream AKT, ERK, and JNK signaling pathways in U343cell line (Supplementary Fig. S9). Addition of calcitonin toU343/VC cells led to a minimal reduction of pAKT, pERK, and

LN22

9/VC

LN22

9/C

ALC

R

BSA CT

0123456789

0 1 2 3 4 5 6Days

No.

of p

rolif

erat

ing

cells

(¥15

,000

)

LN22

9/VC

LN22

9/C

ALC

R

BSA CT

0

20

4060

80100120

% C

ells

mig

rate

d

BSA CT BSA CT

**

** *

LN229/VC

LN229/CALCR

0

20

40

60

80

100

120

BSA CT BSA CTLN229/

siNTLN229/

siCALCR

*

% C

ells

mig

rate

d

CBA

ED

IHG

-10123456789

10

LN229/VC

LN229/CALCR

CALCR

Actin

LN22

9/C

ALC

RLN

229/

VC

BSA CT

BSA CT

LN22

9/si

NT

LN22

9/si

CA

LCR

LN22

9/VC

LN22

9/C

ALC

R

BSA CT

020406080

100120

% C

ells

inv

aded

BSA CT BSA CTLN229/

VCLN229/CALCR

**

**

***

F

% C

olon

ies

0

20

40

60

80

100

120 ****

***

BSA CT BSA CTLN229/

VCLN229/CALCR

-2.5

-2.0

-1.5

-1.0

-0.5

0.0

0.5

Log 2

ratio

Log 2

ratio

LN229/siCALCR

LN229/siNT

CALCR �

Actin �

BSA CT BSA CT

LN229/siNT

LN229/siCALCR

% P

rolif

erat

ing

cells

0

20

40

60

80

100

120 **Day 5

0

20406080

100120

BSA CT BSA CTLN229/

VCLN229/CALCR

*NS

***

% C

olon

ies

0

20

40

60

80

100

120

BSA CT BSA CT

% P

rolif

erat

ing

cells

LN229/VC

LN229/CALCR

*** ***

*Day 6

LN229/VC + CTLN229/CALCR + BSALN229/CALCR + CT

LN229/VC + BSA

0123456789

0 1 2 3 4 5Days �

No.

of p

rolif

erat

ing

cells

(¥15

,000

) LN229/siNT + CT

LN229/siCALCR + CT

LN229/siNT + BSA

LN229/siCALCR + BSA

Figure 2.

Effect of calcitonin on various properties of CALCR-high LN229 glioma cells. A, Overexpression of CALCR in LN229 cell line verified by checking RNA andprotein levels. B–F, Colony suppression assay (B), proliferation assay (C), migration assay (D), invasion assay (E), and soft agar assay (F) for CALCR in vectorcontrol (VC)/CALCR (wild-type) conditions in presence or absence of calcitonin. All assays are quantified and the bar plots are provided at the right side ofthe representative images. For each experiment, the quantification at the end of the assay is used for the bar plot. The value of the control condition (VC þ BSA)was normalized to 100%, and the values for the other conditions (VCþCT, CALCRþBSA, andCALCRþCT)were calculatedwith respect to normalizedVCþBSA.G,Silencing of CALCR in LN229 cell line verified by checking RNA and protein levels. H and I, Proliferation assay (H) and migration assay (I) in CALCR silencedconditions in the presence or absence of calcitonin. All assays are quantified and the bar plots are provided to the right side of the representative images. For eachexperiment, the quantification at the end of the assay is used for the bar plot. The value of the control condition (siNT þ BSA) was normalized to 100%, andthe values for the other conditions (siNTþCT, siCALCRþBSA, and siCALCRþCT)were calculatedwith respect to normalized siNTþBSA. The P values for all panelsare represented by � , ��, and �� , which denote P values of <0.05, 0.01, and 0.001, respectively, and NS refers to nonsignificant P value (�0.05).

Pal et al.





pJNK levels. However, overexpression of WT CALCR led to asignificant reduction in phosphorylation of the above signalingmolecules, which was further reduced when calcitonin wasadded to U343/CALCR cells (Supplementary Fig. S9, comparelanes 3 and 4 with 1 and 2). However, the mutant CALCRs bothin the absence and presence of exogenously added calcitonininhibited these three signaling pathways much less efficientlywith the inhibition being negligible in the severe mutants(Supplementary Fig. S9, compare lanes 5 to 18 with 3 and 4).

From the above results, it is clear that the mutant forms ofCALCR exhibit varied LOF phenotypes. This could be explainedby the fact that different mutations may have a varying impactin altering the structure of CALCR. The crystal structure of theN-terminal domain, along with calcitonin ligand bound to it

has been crystalized, and the structure has been determined(PDB ID: 5II0; ref. 16). We used three servers, mCSM, SDM, andDUET, to quantify the influence of R45Q, A51T, and P100Lmutations (located in the N-terminal domain) in disruption ofthe protein stability of CT–CALCR complex (measured by thechange in Gibbs free energy DDG between the wild-type andmutant structures). All three tools predicted A51T mutation,one of the severe mutants, to be destabilizing. However, theabove analysis predicted R45Q and P100L (both mild mutants)to be neutral in nature (Supplementary Fig. S10). Collectivelyfrom the above results, we can conclude that mutation inCALCR abrogates CT–CALCR tumor suppressor signaling axis,thus contributing significantly to the more aggressive pheno-type seen in GBMs.

RAMP1RAMP2RAMP3

-1.5

-1.0

-0.5

0.0

0.5

1.0

1.5

Control LN229

Log 2 r

atio Lo

g 2 rat

io

BSA

CT

LN229/VC + shNT

LN229/CALCR +

shNT

LN229/VC +

shRAMP1

LN229/CALCR +shRAMP1

B C

-4.0-3.5-3.0-2.5-2.0-1.5-1.0-0.50.00.5

shNT shRAMP1

DE

RAMP1

Actin

0

20

40

60

80

100

120

shN

T

shR

AM

P1

shN

T

shR

AM

P1

shN

T

shR

AM

P1

shN

T

shR

AM

P1

% P

rolif

erat

ing

cells

VC+CT

CALCR+CT

CALCR+BSA

VC+BSA

NS

NS

NS

NS

Day 6

ABSA CT BSA CT

U343/VC

U343/CALCR

1.0 0.9 0.8 0.4

1.0 0.9 0.7 0.3

BSA CT BSA CT

LN229/VC

LN229/CALCR

1.0 0.6 0.8 0.4

1.0 0.5 0.7 0.3

1.0 0.5 0.9 0.9

pJNK

tERK

tJNK

LN229/siNT

LN229/siCALCR

Actin

1.0 1.0 0.8 0.5 1.0 0.7 0.8 0.6 1.0 0.5 0.8 0.9

pAKT

tAKT

BSA CT BSA CT

pERK

1.0 0.4 1.0 0.8

CALCR

Figure 3.

Regulation of ERK, JNK, and AKT signaling by calcitonin–CALCR signaling axis and the role of RAMP coreceptors in CALCR-mediated tumor suppressorfunctions in glioma cells. A, Western blot analysis of phosphorylation of downstream signaling molecules ERK, JNK, and AKT in CALCR overexpressionconditions (in U343 and LN229 cells) and CALCR-silenced condition (in LN229 cells) in the presence or absence of calcitonin. The quantification for each phospho-protein is provided at the bottomof the corresponding blot. The total protein for each lanewas normalized to the actin levels, and subsequently, the phospho-proteinwas normalized to the normalized total. For CALCR overexpression experiments, the value for VCþBSA for each phospho-proteinwas normalized to 1, and the otherconditions (VC þ CT, CALCR þ BSA, and CALCR þ CT) were calculated with respect to the normalized VC þ BSA. For the CALCR silencing experiment, thevalue for siNTþ BSA for each phospho-protein was normalized to 1, and the other conditions (siNTþ CT, siCALCRþ BSA, and siCALCRþ CT) were calculated withrespect to the normalized siNTþBSA.B, Transcript levels of RAMP1, 2 and 3 in LN229 cells comparedwith control brain tissue.C,Knockdownof RAMP1 in LN229 cellsshown by real-time qPCR andWestern blotting.D, Colony suppression assay in LN229/VC and LN229/CALCR stable cells transfectedwith shRAMP1. E, Proliferationassay in LN229/VC and LN229/CALCR stable cells transfected with shRAMP1. The quantification for the 6th day of proliferation as given in the SupplementaryFig. S6D is given in the bar plot, wherein the value for LN229/VC/shNT þ BSA condition was normalized to 100%, and the rest of the conditions were plottedaccordingly. NS, nonsignificant P value (�0.05).






Effect of CT–CALCR tumor suppressor axis on GSCsNext, we evaluated the function of CT–CALCR axis in patient-

derived GSCs as well as glioma cell line–derived GSCs. Accordingto the RNA and protein levels, we divided the GSCs into CALCR-high (1035, MGG6, MGG8, MGG23, and LN229) and CALCR-low (MGG4, T98G, U87, U343, and U373) cell lines (Figs. 5Aand 1L; Supplementary Fig. S11A). The WT nature of CALCR inthese lines was confirmed except MGG6, MGG23, and 1035(Supplementary Fig. S2D). Calcitonin was exogenously added toeach of the GSCs, and the effect on neurosphere growth wasobserved by sphere formation and limiting dilution assays.Although calcitonin inhibited the sphere growth in most of the

GSCs, the percentage inhibition of sphere growth was found tobe significantly higher in CALCR-high GSCs compared with theCALCR-lowGSCs (Fig. 5B–E). The glioma reprogramming factors,SOX2, OLIG2, SALL2, and POU3F2, as identified by Suva andcolleagues, were found to be downregulated in calcitonin condi-tion, and this was more prominent in CALCR-high GSCs (Fig. 5F;ref. 17). Furthermore, addition of calcitonin to CALCR-highGSCs(MGG8, 1035, and LN229) led to a significant inhibition of pERKand pAKT levels, which were less pronounced in the CALCR-lowGSCs (U343 andMGG4; Fig. 5G). Next, we evaluated the effect ofCT–CALCR axis on the growth of xenograft-derived neurospheres(xGSC). Addition of calcitonin to xGSCs significantly reduced

A

U343/CALCRU343/R45Q

U343/P100L

U343/VC

U343/A51T

U343/V250MU343/A307VU343/R404CU343/R420C

B

Spearman R -0.890.03P value

V250MA51TR420C A307V

P100L

R404C

C

D

E

F

G

***

020406080

100120

TCASB

% C

olon

ies

Colony formation assay

***

020406080

100120140

TCASB

% P

rolif

erat

ing

cells

Proliferation assay (day 6)

******

***

020406080

100120

TCASB

% C

ells

mig

rate

d

Migration assay**

0.0 0.2 0.4 0.6 0.8 1.00

5

10

15

20

25

LOF Score

Patie

nt s

urvi

val (

mon

ths)

020406080

100120

CTBSA

*** *Invasion assay

% C

ells

inva

ded

020406080

100120

TCASB

Soft agar assay*** **

% C

olon

ies

GDP aβ

γ

G-protein

C-ter

N-ter

Hormone receptor domain

Extracellular

Cytoplasm

12

3

4

5

6 7

1. R45Q2. A51T3. P100L

4. V250M5. A307V6. R404C7. R420C

Figure 4.

Effect of mutation of CALCR on U343 glioma cell properties. A, Representation of the structure of CALCR. Star denotes the approximate positions of themutations in the protein domains. B–F, Quantification of proliferation assay (B), colony suppression assay (C), migration assay (D), invasion assay (E), andsoft agar assay (F) for CALCR overexpression in U343 cells transfected with WT CALCR and the seven mutated CALCRs [the eighth mutation Y186C was notincluded in this analysis as this position is absent in the transcript variant 2 of CALCR (transcript ID: ENST000009994441) used in this study)]. The valueof the control condition (VC þ BSA) was normalized to 100%, and the values for the other conditions were calculated with respect to normalized VC þ BSA.Comparison of mutant CALCR phenotypes with that of WT CALCR was done using one-way ANOVA. The P values are represented by � , �� , and �� ,which denote P values of <0.05, 0.01, and 0.001, respectively. G, Correlation between LOF score from the results in U343 cells versus patient survival. Thisanalysis did not include R45Q, as the patient harboring this mutation did not have survival information. Please see Supplementary Information for LOFscore calculation.

Pal et al.





the number as well as size of the neurospheres (SupplementaryFig. S11B and S11C). In addition, the effect of CT–CALCR path-way was tested on reprogramming of established glioma cell linesto form GSCs. We observed that addition of calcitonin duringreprogramming inhibited neurosphere formation significantly inCALCR-high cell line (LN229) unlike CALCR-low cell lines(T98G, U87, U343, and U373; Supplementary Fig. S12A–S12E). These results demonstrate that CT–CALCR axis potentlyinhibits the growth of GSCs as well as reprogramming of gliomacell lines in a CALCR-dependent manner.

CT–CALCR tumor suppressor axis is a potential therapeutictarget

To confirm the tumor-suppressive function of CT–CALCRaxis, we tested the effect of CALCR co-transfection on the abilityof Ras (KRasV12) to transform SV40-immortalized mouseastrocytes (IMA2.1 cells) in vitro. We observed that Ras trans-formed IMA2.1 cells efficiently as seen by the increased numberof colonies in soft agar (Fig. 6A and B, bar 1). Furthermore, wetested the effects of WT and mutated CALCR on astrocytetransformation. Although WT CALCR inhibited Ras-mediated

-10-8-6-4-202468

MG

G4

T98G U87

U34

3

U37

3

1035

MG

G6

MG

G8

MG

G23

LN22

9

CALCR Low CALCR High

CA

LCR

Low

CA

LCR

Hig

h


Log 2 r

atio


-20-10

01020304050607080

MG

G4

T98G U87

U34

3

U37

3

1035

MG

G6

MG

G8

MG

G23

LN22

9

% S

pher

e in

hibi

tion

All spheres


-20

0

20

40

60

80

100

120

MG

G4

T98G U87

U34

3

U37

3

1035

MG

G6

MG

G8

MG

G23

LN22

9

% S

pher

e in

hibi

tion

>30 mmol/L spheres

** ***

-7

-6

-5

-4

-3

-2

-1

0

1

MGG4 T98G U87 U343 U373 1035 MGG6 MGG8 MGG23 LN229

SOX2

OLIG2

SALL2

POU3F2

Log 2 ra

tio

A B C

D

Pal et al., 2017, Figure 5

E

F G MGG8 U343 MGG4 LN2291035

1.0 0.2 1.21.0

0.1 1.31.0 1.0

pERK Æ

Æ

Æ

Æ

Æ

tERK

pAKT

tAKT

Actin

BSA CT BSA CT BSA CT BSA CTBSA CT

1.0 0.8 0.91.0 0.71.0

1.0 0.5 0.91.0 0.71.0

U373/BSA

U373/CT

L.M

.H

.M.

U343/BSA

U343/CT

L.M

.H

.M.

MGG8/BSA

L.M

.H

.M.

MGG8/CT

MGG23/BSA

MGG23/CT

L.M

.H

.M.

0 50 100 150 200

0.0

-0.5

-1.0

-1.5

-2.0

-2.5

-3.0

0 50 100 150 200

0.0

-0.5

-1.0

-1.5

-2.0

-2.5

-3.0

0 50 100 150 200

0.0

-0.5

-1.0

- 1.5

-2.0

-2.5

-3.0

0 50 100 150 200

0.0

-0.5

-1.0

-1.5

-2.0

-2.5

-3.0

MGG4

P < 0.0001

CA

LCR

Low

Log

frac

tion

nonr

espo

ndin

g

Dose (no. of cells)

BSACT

T98G

P = 0.0005

Log

frac

tion

nonr

espo

ndin

g

Dose (no. of cells)

BSACT

U87

P = 0.0123

Log

frac

tion

nonr

espo

ndin

g

Dose (no. of cells)

BSACT

U343

P = 0.122

Log

frac

tion

nonr

espo

ndin

g

Dose (no. of cells)

BSACT

U373

P = 0.675

Log

frac

tion

nonr

espo

ndin

g

Dose (no. of cells)0 50 100 150 200

0.0

-0.5

-1.0

-1.5

-2.0

-2.5

BSACT

0 50 100 150 200

0.0

-0.5

-1.0

-1.5

-2.0

-2.5

-3.0

CA

LCR

Hig

hLo

g fr

actio

n no

nres

pond

ing

Dose (no. of cells)

1035

p < 0.0001

BSACT

0 50 100 150 200

Log

frac

tion

nonr

espo

ndin

g

Dose (no. of cells)

MGG6

P < 0.0001

0.0

-0.5

-1.0

- 1.5

-2.0

-2.5

-3.0

BSACT

Log

frac

tion

nonr

espo

ndin

g

Dose (no. of cells)

MGG8

P < 0.0001

0 50 100 150 200

0.0

-0.5

-1.0

-1.5

-2.0

-2.5

-3.0

BSACT

Log

frac

tion

nonr

espo

ndin

g

Dose (no. of cells)

MGG23

P < 0.0001

0 50 100 150 200

0.0

-0.5

-1.0

-1.5

-2.0

-2.5

-3.0

BSACT

LN229

P < 0.0001

Log

frac

tion

nonr

espo

ndin

g

Dose (no. of cells)0 50 100 150 200

0.0

-0.5

-1.0

-1.5

-2.0

-2.5

-3.0

BSACT

Figure 5.

Effect of CT–CALCR tumor suppressor axis on GSCs. A, Transcript levels of CALCR in patient-derived GSCs and cell line–derived GSCs as detected byreal-time qPCR. The transcript levels divide theGSCs intoCALCR-low (MGG4, T98G, U87, U343, andU373) andCALCR-high (1035,MGG4,MGG6,MGG8, andMGG23).B and C, GSC growth as neurospheres was assessed in the presence of BSA or calcitonin. The percentage inhibition of neurosphere growth in calcitonincondition as compared with BSA when all spheres (B) and spheres with size >30 mm in diameter (C) were considered. For each GSC cell line, the number ofspheres in the BSA conditionwas normalized to 100%, and then the calcitonin conditionwas calculated. The difference in neurosphere growth percentage is plotted.Student's t test was performed to evaluate the statistical significance between the two groups. D, Representative images of neurosphere assay for CALCR-low(U373 and U343) and CALCR-high (MGG8 and MGG23) GSCs. L.M., lowmagnification (2.5�) and H.M., high magnification (10�). E, Limiting dilution assay for GSCs.For BSA and calcitonin conditions, 1, 5, 10, 20, 50, 100, and 200 cells were plated (n¼ 12). At the endpoint, number of wells not having any spherewas calculated, andthe graph was plotted using extreme limiting dilution analysis (ELDA) software. Total number of cells (dose) is plotted on the x-axis, and the log fraction ofnonresponding/empty well is plotted on the y-axis. The dotted lines represent the confidence interval (0.95). F, Transcript levels of glioma reprogramming factors(SOX2, OLIG2, SALL2, and POU3F2) in calcitonin condition compared with BSA in various GSC cell lines tested. The log2 values are plotted for calcitonincalculated with respect to the BSA condition (normalized to 0). G, pERK and pAKT levels in GSCs in BSA versus calcitonin conditions in CALCR-low GSCs(U343 andMGG4) andCALCR-highGSCs (MGG8, 1035, and LN229). The quantification for each phospho-protein is provided at the bottomof the corresponding blot.The total protein for each lane was normalized to the actin levels, and subsequently, the phospho-protein was normalized to the normalized total. The valuefor BSA for each phospho-protein per cell line was normalized to 1, and the value for calcitonin was calculated in comparison with the normalized BSA. The P valuesfor all the panels are represented by � , �� , and �� , which denote P values of <0.05, 0.01, and 0.001, respectively.






transformation very efficiently (Fig. 6A and B, compare bar 2with 1), CALCR mutants failed to inhibit Ras-mediated trans-formation efficiently, although to varying levels (Fig. 6A and B,compare bars 3 to 9 with 2). In particular, the severe mutantswith the highest LOF scores (A51T and V250M) were found tohave completely lost the ability to inhibit Ras-mediated trans-formation. To ascertain pathways that could be involved inCALCR-mediated inhibition of transformation by RasV12, weevaluated the effect of CALCR on the phosphorylation status ofERK, AKT, and JNK molecules in RasV12-transformed cells. Ras-transformed IMA2.1 cells showed an increase in pERK andpJNK (Supplementary Fig. S13; compare lane 3 with 1), whichwas abrogated significantly when CALCR was exogenouslyintroduced (Supplementary Fig. S13; compare lane 4 with3). These results demonstrate that CALCR targets ERK, JNK,

and AKT signaling molecules independent of Ras and perhapsinvolving other signaling pathways. To evaluate the importanceof CT–CALCR axis as a therapeutic target, we tested the effectof calcitonin intraperitoneal injections on the xenograft tumorgrowth of LN229-luc cells in NIH female nu/nu mice. We foundthat treatment with calcitonin inhibited LN229 xenografttumor growth significantly (Fig. 6C–E). In summary, theseresults confirm the tumor-suppressive nature of CT–CALCRaxis and highlight the importance of the axis as a noveltherapeutic target in glioma (Fig. 6F). When glioma cells harborWT CALCR (left), binding of calcitonin leads to inhibition ofJNK, ERK, and AKT phosphorylation resulting in reduced onco-genic properties of the cells such as proliferation, migration,invasion, and anchorage-independent growth capacity. Thisultimately contributes to better survival of patients with GBM

VC CALCR

R45QVC

A51T

P100L

V250M

A307V

R404C

R420C

A B

VC

CA

LCR

R45

Q

P100

L

A51

T

V250

M

R40

4C

A30

7V

R42

0C

% C

olon

ies

form

ed

** ***

-100

102030405060

1 2 3 4 5 6 7 8 9

C

0 5 15 2510 20 30

Injection of LN229-luc

cells

Divide into two groups. Calcitonin

injection/dayCalcitonin injection/

alternate dayStop

injection

D

E

BSA CT

Day

10

Day

30

Day

15

Day

20

Day

25

0.0

0.5

1.0

1.5

2.0

2.5

10 15 20 25 30

BSACT

Tota

l flu

x (¥

105 )

* **

*

Days

Days

F

α βγ

G-protein

C-ter

N-terExtracellular

Cytoplasm

α βγ

G-protein

C-ter

N-terExtracellular

Cytoplasm

WT CALCR

MutatedCALCR

Reduced proliferation, migration invasion,anchorage-independent growth

CT

JNK

ERKAKT

JNK

ERKAKT

PP

PP

P P

CT

Less aggressive

tumor

Veryaggressive

tumor

Better survivalTreatment with Salmon calcitonin

Worse survivalOther treatment option required

Enhanced proliferation, migrationinvasion, anchorage-independent growth

Figure 6.

Effect of CALCR on Ras-mediated transformation of immortalized astrocytes in vitro and in vivo xenograft tumor growth. A, Transformation of mouseimmortalized astrocytes IMA2.1 by RasV12 oncogene tested by colony formation in soft agar in presence of WT and the seven mutated forms of CALCR.B, The total number of colonies in RasV12/CALCR condition was normalized to 0%, and the percentage of colonies in RasV12/VC and RasV12/CALCRmutants was calculated from A and plotted. C, The pictorial representation of the experimental design of in vivo xenograft mouse model for testing the therapeuticefficacy of calcitonin. Day0beginswith the subcutaneous injection of LN229-luc cells in theNIH nu/numice (n¼4). Luciferase readingwas taken every 5 days till day30. The calcitonin injection regime followed was days 10–17 (1 I.U./mouse/24 hrs) and days 18–25 (1 I.U./mouse/48 hours). D, The tumor growth (days 10–30)for BSA and calcitonin injected mice are shown by bioluminescence imaging. E, The total flux of luminescence from the tumors of BSA and calcitonin treatedmice are plotted. The scale has been adjusted to – minimum flux ¼ 600 radiance counts (photon/s) and maximum flux ¼ 2,000 radiance counts (photon/s).The P values for panels B and E represented by � , �� , and �� , which denote P values of <0.05, 0.01, and 0.001, respectively. F, Graphical representation ofthe clinical efficacy of the key findings from this study. The panel on the left describes therapeutic utilization of CT-CALCR axis in CALCR WT glioma. The panel onthe right describes how CALCR mutation abolishes CT-CALCR tumor suppressor pathway leading to an aggressive GBM tumor.

Pal et al.





with less aggressive tumors. Also, treatment with calcitonincould be an option for therapy for these patients. However,when CALCR gets mutated (right), binding of calcitonin toCALCR, change in conformation of the receptor, or activationof G-protein by CALCR may be abrogated, and this will damagethe inhibitory signals downstream. Therefore, increased levelsof pERK, pAKT, and pJNK are observed with a resultant increasein oncogenic properties of the glioma cells mentioned before.Hence, this will result in poor survival in patients with GBMwith very aggressive tumors.

DiscussionIn this study, we analyzed somatic mutations in an Indian

cohort of 42 gliomas compared with matched blood samplesusingWES. Themutation spectrumwas found tobe largely similarto that of TCGA (3). Although TP53, IDH1, and ATRX weremutated typically in lower grades, mutations in PTEN, PIK3CA,and NF1 were largely seen in GBMs. Integrative analysis of theexome data of Indian and TCGA cohorts identified several path-ways to be associatedwithGBM survival. GBMswithmutations inone or more genes that belong to "neuroactive ligand–receptorinteraction pathway" predicted worst prognosis. We also showthat CALCR, the top mutated gene belonging to the above path-way, alongwith its ligand functions as a tumor suppressor axis andinactivatingmutations/reduced transcript levels in CALCRdefinesa highly aggressive subset of GBM with very poor survival.

An integrated survival analysis involvingGBM-specificmutatedgenes derived from Indian and TCGA cohorts identified severalpathways being associated with GBM survival. Of these, geneticalterations in "neuroactive ligand–receptor interaction pathway"genes were found to be associated with poor survival with highsignificance. This pathway consists of a large number of GPCRs,which upon activation by their respective ligands have beenshown to regulate neuronal signaling in specific ways, thusinfluencing a variety of animal behavior (18). Epigenetic altera-tions in neuroactive ligand–receptor interaction pathway havebeen shown tobe associatedwith the riskof developingpancreaticcancer (19, 20), small-cell lung cancer (21), renal cell carcinoma(22), hepatocellular carcinoma (23), etc. In TCGA pan-cancerdata study, neuroactive ligand–receptor interaction pathwaycame up to be the fifth most highly mutated pathways in cancer(24). However, there are no studies that show the functionalsignificance of genetic alterations in this pathway with respect tocancer development. This study demonstrates that mutationalalteration of neuroactive–ligand interaction pathway promotesGBM aggressiveness. Our finding has translational relevance asagonists and antagonists for many GPCRs are available, andhence, one could utilize a drug repositioning approach whereinthe known GPCR inhibitors may have potential anticancer ther-apeutic implications (25).

Calcitonin, the ligand of CALCR, is a 32 amino acid polypep-tide hormone synthesized primarily by thyroid (26). Binding ofcalcitonin to CALCR regulates a variety of signaling downstreamresulting in the regulation of bone metabolism, calcium flux,and cancer cell proliferation (26–29). Although mutations theCALCR gene have been reported in lung adenocarcinoma (30),the functional importance of CALCR mutations with respectto cancer development is not known. Our study demonstratesthat CT–CALCR signaling inhibits cell proliferation, migration,invasion, and anchorage-independent growth of established gli-

oma cell lines with a concomitant inhibition of downstream AKT,MEK, and JNK signaling. Furthermore, we show that somaticmutations in CALCR led to LOF in glioma cells, and patientswith mutated CALCR exhibited poor prognosis. In fact, the LOFscore, calculated from the experiments (depicts the severity of themutants), correlated significantly with patient survival, althoughthe small number of samples preclude the ability to make strongconclusions.

Our study reveals the potential of the CT–CALCR axis as a noveltherapeutic target as observed by its effectiveness in the inhibitionof GSCs that led to a significant decrease in glioma reprogram-ming factors. The role of CALCR as a tumor suppressorwas furthervalidated by its potency to inhibit the first event in tumorinitiation, that is, transformation. Indeed, CALCR inhibitedRasV12-mediated transformation of immortalized astrocytes invitro. Moreover, CALCR was found to be capable of inhibitingpERK and pJNK even in the presence of constitutively activeoncogenic Ras, which suggests that CALCR is capable of directlyregulating signaling molecules present downstream of Ras.Although Ras is known to activate MEK kinase, which in turncan activate ERK and other pathways such as JNK (31), it is alsoknown that downstream to GPCR, other upstream molecules,such as PKA (32) andRac (33), can regulate ERK andCDC42 (34),Gai (35) can regulate JNK. Thus, we demonstrate that CT–CALCRaxis is a direct inhibitor of oncogenic signaling downstream toRas, which further underscores the importance of CT–CALCR axisas a compelling tumor suppressor pathway in glioma. This wassubstantiated by the result that intraperitoneal injection of calci-tonin in NIH nu/nu mice, inoculated with LN229-luc cells toform subcutaneous flank tumor, reduced the tumor burdensignificantly.

Thus, our study identifies CT–CALCR axis acts as a tumorsuppressor pathway in GBM. Mutational inactivation of CALCRor reduced CALCR transcript levels leads to an aggressive GBMwith poor survival. Our findings have multiple translationalimplications. Most importantly, for GBMswithwild-type CALCR,calcitonin could be considered as a treatment option (36). In fact,salmon calcitonin is prescribed for postmenopausal osteoporosis(37) and also in therapy of giant cell granuloma (38). For GBMswith mutated CALCR receptor, a combination of inhibitors ofAKT, MEK, and JNK pathways could be tried.

Disclosure of Potential Conflicts of InterestNo potential conflicts of interest were disclosed.

Authors' ContributionsConception and design: J. Pal, V. Patil, C. Sarkar, K. SomasundaramDevelopment of methodology: J. Pal, V. Patil, C. Sarkar, K. SomasundaramAcquisition of data (provided animals, acquired and managed patients,provided facilities, etc.): J. Pal, V. Patil, K. Kaur, C. Sarkar, K. SomasundaramAnalysis and interpretation of data (e.g., statistical analysis, biostatistics,computational analysis): J. Pal, V. Patil, A. Kumar, C. Sarkar, K. SomasundaramWriting, review, and/or revision of the manuscript: J. Pal, V. Patil,K. SomasundaramAdministrative, technical, or material support (i.e., reporting or organizingdata, constructing databases): A. Kumar, K. SomasundaramStudy supervision: K. Somasundaram

AcknowledgmentsThe results published here are in whole or part based upon data generated

by The Cancer Genome Atlas pilot project established by the NCI andNHGRI. Information about TCGA and the investigators and institutions






that constitute the TCGA research network can be found at http://cancergenome.nih.gov/. We also acknowledge the use of GSE7696 in this study.We thank Drs. Hiroaki Wakimoto, Samuel Rabkin, and Santosh Kesarifor providing us with GSCs. We thank Dr. Stefan Schildknecht for providingmouse immortalized astrocyte cells. J. Pal acknowledges Indian Institute ofScience for the research fellowship. V. Patil and J. Pal thank DBT, Govern-ment of India for financial support. The NGS facility, Indian Institute ofScience is acknowledged for exome sequencing. The Centre for AnimalFacility (CAF), Indian Institute of Science, and Dr. Krishnaveni (CAF)are acknowledged. K. Somasundaram acknowledges CSIR and DBT,Government of India for research grant. Infrastructure support by fundingfrom DST-FIST, DBT grant-in-aid and UGC (Centre for Advanced Studies

in Molecular Microbiology) to MCB is acknowledged. Prof. ParthaMajumder (NIBMG) and Arjun Arkal Rao are acknowledged for theirinvaluable inputs.

The costs of publication of this article were defrayed in part by thepayment of page charges. This article must therefore be hereby markedadvertisement in accordance with 18 U.S.C. Section 1734 solely to indicatethis fact.

Received July 7, 2017; revised November 15, 2017; accepted December 14,2017; published OnlineFirst December 20, 2017.

References1. The Cancer Genome Atlas Research Network. Comprehensive genomic

characterization defines human glioblastoma genes and core pathways.Nature 2008;455:1061–8.

2. Frattini V, Trifonov V, Chan JM, Castano A, Lia M, Abate F, et al. Theintegrated landscape of driver genomic alterations in glioblastoma. NatGenet 2013;45:1141–9.

3. Brennan CW, Verhaak RG, McKenna A, Campos B, Noushmehr H, SalamaSR, et al. The somatic genomic landscape of glioblastoma. Cell 2013;155:462–77.

4. Stupp R, Hegi ME, Mason WP, van den Bent MJ, Taphoorn MJ, Janzer RC,et al. Effects of radiotherapywith concomitant and adjuvant temozolomideversus radiotherapy alone on survival in glioblastoma in a randomisedphase III study: 5-year analysis of the EORTC-NCIC trial. Lancet Oncol2009;10:459–66.

5. Cibulskis K, LawrenceMS,Carter SL, SivachenkoA, JaffeD, SougnezC, et al.Sensitive detection of somatic point mutations in impure and heteroge-neous cancer samples. Nat Biotechnol 2013;31:213–9.

6. Cancer Genome Analysis. Indelocator. Cambridge, MA: Broad Institute.Available from: http://archive.broadinstitute.org/cancer/cga/indelocator.

7. Ohgaki H, Kleihues P. Genetic pathways to primary and secondary glio-blastoma. Am J Pathol 2007;170:1445–53.

8. Vigneswaran K, Neill S, Hadjipanayis CG. Beyond the World HealthOrganization grading of infiltrating gliomas: advances in the moleculargenetics of glioma classification. Ann Transl Med 2015;3:95.

9. Kannan K, Inagaki A, Silber J, Gorovets D, Zhang J, Kastenhuber ER, et al.Whole-exome sequencing identifies ATRX mutation as a key moleculardeterminant in lower-grade glioma. Oncotarget 2012;3:1194–203.

10. Ji TH, Grossmann M, Ji I. G protein-coupled receptors. I. Diversity ofreceptor-ligand interactions. J Biol Chem 1998;273:17299–302.

11. Kobilka BK. G protein coupled receptor structure and activation. BiochimBiophys Acta 2007;1768:794–807.

12. Patil V, Pal J, Somasundaram K. Elucidating the cancer-specific geneticalteration spectrum of glioblastoma derived cell lines from whole exomeand RNA sequencing. Oncotarget 2015;6:43452–71.

13. Degrauwe N, Schlumpf TB, Janiszewska M, Martin P, Cauderay A, ProveroP, et al. TheRNAbinding protein IMP2preserves glioblastoma stem cells bypreventing let-7 target gene silencing. Cell Rep 2016;15:1634–47.

14. New DC, Wong YH. Molecular mechanisms mediating the G protein-coupled receptor regulation of cell cycle progression. JMol Signal 2007;2:2.

15. Morfis M, Tilakaratne N, Furness SG, Christopoulos G, Werry TD, Chris-topoulos A, et al. Receptor activity-modifying proteins differentially mod-ulate the G protein-coupling efficiency of amylin receptors. Endocrinology2008;149:5423–31.

16. Johansson E, Hansen JL, Hansen AM, Shaw AC, Becker P, Schaffer L, et al.Type II turn of receptor-bound salmon calcitonin revealed by X-raycrystallography. J Biol Chem 2016;291:13689–98.

17. Suva ML, Rheinbay E, Gillespie SM, Patel AP, Wakimoto H, Rabkin SD,et al. Reconstructing and reprogramming the tumor-propagating potentialof glioblastoma stem-like cells. Cell 2014;157:580–94.

18. Engel SR, Grant KA. Neurosteroids and behavior. Int Rev Neurobiol 2001;46:321–48.

19. Wei P, Tang H, Li D. Insights into pancreatic cancer etiology from pathwayanalysis of genome-wide association study data. PLoSOne2012;7:e46887.

20. Li L, Hanahan D. Hijacking the neuronal NMDAR signaling circuit topromote tumor growth and invasion. Cell 2013;153:86–100.

21. Jahchan NS, Dudley JT, Mazur PK, Flores N, Yang D, Palmerton A, et al. Adrug repositioning approach identifies tricyclic antidepressants as inhibi-tors of small cell lung cancer and other neuroendocrine tumors. CancerDiscov 2013;3:1364–77.

22. Liu X, Wang J, Sun G. Identification of key genes and pathways in renal cellcarcinoma through expression profiling data. Kidney Blood Press Res2015;40:288–97.

23. Zhang MH, Shen QH, Qin ZM, Wang QL, Chen X. Systematic tracking ofdisrupted modules identifies significant genes and pathways in hepato-cellular carcinoma. Oncol Lett 2016;12:3285–95.

24. Dees ND, Zhang Q, Kandoth C, Wendl MC, Schierding W, Koboldt DC,et al. MuSiC: identifying mutational significance in cancer genomes.Genome Res 2012;22:1589–98.

25. LiuY, An S,WardR,Yang Y,GuoXX, LiW, et al. Gprotein-coupled receptorsas promising cancer targets. Cancer Lett 2016;376:226–39.

26. Masi L, Brandi ML. Calcitonin and calcitonin receptors. Clin Cases MinerBone Metab 2007;4:117–22.

27. Purdue BW, Tilakaratne N, Sexton PM. Molecular pharmacology of thecalcitonin receptor. Receptors Channels 2002;8:243–55.

28. Robbins EW, Travanty EA, YangK, Iczkowski KA.MAPkinase pathways andcalcitonin influence CD44 alternate isoform expression in prostate cancercells. BMC Cancer 2008;8:260.

29. Terra SR,Cardoso JC, Felix RC,Martins LA, SouzaDO,GumaFC, et al. STC1interference on calcitonin family of receptors signaling during osteoblas-togenesis via adenylate cyclase inhibition. Mol Cell Endocrinol 2015;403:78–87.

30. George J, Lim JS, Jang SJ, Cun Y, Ozretic L, Kong G, et al. Comprehensivegenomic profiles of small cell lung cancer. Nature 2015;524:47–53.

31. Xia Y, Makris C, Su B, Li E, Yang J, Nemerow GR, et al. MEK kinase 1 iscritically required for c-Jun N-terminal kinase activation by proinflamma-tory stimuli and growth factor-induced cell migration. Proc Natl Acad SciU S A 2000;97:5243–8.

32. Dumaz N, Marais R. Integrating signals between cAMP and the RAS/RAF/MEK/ERK signalling pathways. Based on the anniversary prize of theGesellschaft fur Biochemie und Molekularbiologie Lecture delivered on5 July 2003 at the Special FEBS Meeting in Brussels. FEBS J 2005;272:3491–504.

33. Eblen ST, Slack JK, Weber MJ, Catling AD. Rac-PAK signaling stimulatesextracellular signal-regulated kinase (ERK) activation by regulating forma-tion of MEK1-ERK complexes. Mol Cell Biol 2002;22:6023–33.

34. Wang L, Yang LD, Burns K, Kuan CY, Zheng Y. Cdc42GAP regulatesc-Jun N-terminal kinase (JNK)-mediated apoptosis and cell numberduring mammalian perinatal growth. Proc Natl Acad Sci U S A 2005;102:13484–9.

35. Bastin G, Yang JY, Heximer SP. Galphai3-dependent inhibition of JNKactivity on intracellular membranes. Front Bioeng Biotechnol 2015;3:128.

36. Wookey PJ, McLean CA, Hwang P, Furness SG, Nguyen S, Kourakis A, et al.The expression of calcitonin receptor detected in malignant cells ofthe brain tumour glioblastoma multiforme and functional propertiesin the cell line A172. Histopathology 2012;60:895–910.

37. Leggate J, Farish E, Fletcher CD, McIntosh W, Hart DM, Sommerville JM.Calcitonin and postmenopausal osteoporosis. Clin Endocrinol 1984;20:85–92.

38. Pogrel MA. Calcitonin therapy for central giant cell granuloma. J OralMaxillofac Surg 2003;61:649–53.


Pal et al.



http://cancergenome.nih.gov/

http://cancergenome.nih.gov/

http://archive.broadinstitute.org/cancer/cga/indelocator


2018;24:1448-1458. Published OnlineFirst December 20, 2017.Clin Cancer Res Jagriti Pal, Vikas Patil, Anupam Kumar, et al. Identify Highly Aggressive Glioblastoma with Poor Outcome

)CALCRLoss-of-Function Mutations in Calcitonin Receptor (

Updated version

10.1158/1078-0432.CCR-17-1901doi:

Access the most recent version of this article at:

Material

Supplementary

http://clincancerres.aacrjournals.org/content/suppl/2017/12/20/1078-0432.CCR-17-1901.DC1

Access the most recent supplemental material at:

Cited articles

http://clincancerres.aacrjournals.org/content/24/6/1448.full#ref-list-1

This article cites 37 articles, 7 of which you can access for free at:

E-mail alerts related to this article or journal.Sign up to receive free email-alerts

Subscriptions

Reprints and

[email protected]

To order reprints of this article or to subscribe to the journal, contact the AACR Publications Department at

Permissions

Rightslink site. Click on "Request Permissions" which will take you to the Copyright Clearance Center's (CCC)

.http://clincancerres.aacrjournals.org/content/24/6/1448To request permission to re-use all or part of this article, use this link



http://clincancerres.aacrjournals.org/lookup/doi/10.1158/1078-0432.CCR-17-1901

http://clincancerres.aacrjournals.org/content/suppl/2017/12/20/1078-0432.CCR-17-1901.DC1

http://clincancerres.aacrjournals.org/content/24/6/1448.full#ref-list-1

http://clincancerres.aacrjournals.org/cgi/alerts

mailto:[email protected]

http://clincancerres.aacrjournals.org/content/24/6/1448


loss-of-functionmutationsincalcitoninreceptor calcr ... · tumor-suppressive function of the gene,...

Documents