Loss-of-function mutations in Calcitonin receptor (CALCR ... · 12/20/2017 · Collection of patient tumor sample and blood . Tumor and matched blood samples from patient were collected

1

Loss-of-function mutations in Calcitonin receptor (CALCR) identify highly

aggressive glioblastoma with poor outcome

Jagriti Pal1#

, Vikas Patil1#

, Anupam Kumar2, Kavneet Kaur

2, Chitra Sarkar

2* and Kumaravel

Somasundaram1*

1Dept. of Microbiology and Cell Biology, Indian Institute of Science, Bangalore,

2Department of

Pathology, All India Institute of Medical Science, New Delhi

#These authors have contributed equally

Running title: CALCR mutations predict poor prognosis in GBM

Abbreviations: Glioblastoma – GBM, wild type – WT, whole exome sequencing – WES, The

Cancer Genome Atlas – TCGA, CALCR – Calcitonin receptor, CT- Calcitonin.

* Corresponding authors

Tel: +91-80-23607171

Fax: +91-80-23602697

Email: [email protected], [email protected], [email protected]

Conflict of interest: The authors declare no potential conflicts of interest.

Research. on December 16, 2020. © 2017 American Association for Cancerclincancerres.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 December 20, 2017; DOI: 10.1158/1078-0432.CCR-17-1901

http://clincancerres.aacrjournals.org/

2

Translational relevance

The advancement in effective therapeutics for glioblastoma (GBM) has been minimal and the

median survival still remains at 15-17 months only. Hence, there is a need to elucidate novel

altered molecules for effective therapeutic possibilities. In this study, we explore the mutation

spectrum of GBM patients to unearth novel pathways altered by mutation that predict survival in

patients which revealed neuroactive ligand-receptor interaction pathway to be the most

significant. Calcitonin receptor (CALCR), the most mutated gene in this pathway, was studied

further which revealed this receptor to be tumor suppressor in nature and activation of it by its

ligand, calcitonin, led to decrease in tumorigenic properties of glioma cells. Moreover, CALCR

inhibited transformation of astrocytes in vitro, glioma stem-like cell growth and in vivo glioma

tumor growth in mice. Hence, for GBMs with wild type CALCR, calcitonin, which is prescribed

for post-menopausal osteoporosis, could be considered as a treatment option.




3

Abstract

Purpose

Despite significant advances in the understanding of the biology, the prognosis of glioblastoma

(GBM) remains dismal. The objective was to carry out whole exome sequencing (WES) of

Indian glioma and integrate with that of TCGA to find clinically relevant mutated pathways.

Experimental Design

WES of different astrocytoma samples (n=42; Indian cohort) was carried out and compared to

that of TCGA cohort. An integrated analysis of mutated genes from Indian and TCGA cohorts

was carried out to identify survival association of pathways with genetic alterations. Patient-

derived glioma stem-like cells, glioma cell lines and mouse xenograft models were used for

functional characterization of Calcitonin Receptor (CALCR) and establish it as a therapeutic

target.

Results

A similar mutation spectrum between Indian cohort and TCGA cohort was demonstrated. An

integrated analysis identified GBMs with defective “Neuroactive ligand-receptor interaction”

pathway (n=23; 9.54%) have significantly poor prognosis (p<0.0001). Further, GBMs with

mutated Calcitonin receptor (CALCR) or reduced transcripts levels predicted poor prognosis.

Exogenously added Calcitonin (CT) inhibited various properties of glioma cells and pro-

oncogenic signaling pathways in a CALCR-dependent manner. Patient-derived mutations in

CALCR abolished these functions with the degree of loss-of-function negatively correlating with

patient survival. WT CALCR, but not the mutant versions, inhibited Ras-mediated

transformation of immortalized astrocytes in vitro. Further, CT inhibited patient derived

neurospheres growth and in vivo glioma tumor growth in a mouse model.

Conclusions

We demonstrate CT-CALCR signaling axis is an important tumor suppressor pathway in glioma

and establish CALCR as a novel therapeutic target for GBM.

Key words: Glioblastoma, glioma, GBM, calcitonin, calcitonin receptor, prognosis, mutation.




4

Introduction

Glioblastoma (GBM) is the most common and highly aggressive adult primary brain

tumor. GBMs show significant amount of proliferation, invasion, angiogenesis, necrosis and are

also treatment refractory. Each GBM tumor carries an amalgamation of genetic alterations that

determine cancer prognosis and response to therapy. Intensive studies on candidate genes show

various genetic alterations typical to GBM, e.g., TP53 mutation and loss, EGFR amplification

and mutation, 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 The

Cancer Genome Atlas (TCGA) and have found out various novel genetic alterations which may

play important role in GBM pathogenesis (2,3). From these studies, it is evident that three

pathways - receptor-tyrosine kinase, TP53 and RB, are significantly altered in GBM tumor by

mutations or copy number alterations. However, even with the increase in our understanding of

the tumor, advancement in therapeutics is minimal and the median survival still remains at 15-17

months only (4). Hence, we need to elucidate novel altered molecules and pathways in GBM

such that more effective therapeutic possibilities can be explored.

With this objective, we propose to understand the genetic spectrum of astrocytoma

patients through WES to find novel targetable pathways in GBM. In this study, we performed

integrated analysis of mutated genes from our Indian patient cohort as well as TCGA cohort to

find out mutated pathways that predict survival in GBM patients. This analysis revealed

neuroactive ligand-receptor interaction pathway to be the most significant pathway that predicts

poor survival. We characterized calcitonin receptor (CALCR), a member of this pathway, and

demonstrated the tumor suppressor role of this gene in GBM. Further, we found that mutational

inactivation of CALCR abrogated this tumor suppressive function of the gene, making glioma

cells more aggressive.

Materials and Methods

Collection of patient tumor sample and blood

Tumor and matched blood samples from patient were collected from All India Institute of

Medical Sciences (AIIMS), Delhi. Tumor samples were resected in the neurosurgical room, and

a portion was snap-frozen in liquid nitrogen and stored at -80°C. Additionally, blood samples

collected from each patient were snap-frozen and stored at -80°C. The remaining portion of the




5

tissue was fixed in 10% buffered neutral formalin, processed for paraffin sections and was used

for histopathology and immunohistochemistry (IHC). For RNA isolation, fresh tissue was snap

frozen in RNAlater®

. Normal brain tissue was collected within 3-4 hours after death from

patients who died from non-head injury/non-CNS disorders. The study has been ratified by the

ethics committee of the AIIMS and Indian Institute of Science (IISc) and patient consent was

obtained as per the Institute Ethical Committee guidelines.

Cell lines, plasmid constructs and siRNA

The GBM cell lines, LN229, LN18, T98G, U251, U87, U343, and U373, were obtained

from Sigma Aldrich, Saint Louis, Missouri, USA. The immortalized human astrocyte cell line

IHA (NHA-hTERT-E6/E7) was obtained from Dr. Russell Pieper’s laboratory, University of

California, San Francisco. The immortalized human astrocyte cell line SVG was obtained from

Dr. Abhijit Guha’s laboratory, University of Toronto, Canada respectively. The immortalized

mouse astrocytic cell line, IMA2.1, was a kind gift from Dr. Stefan Schildknecht, University of

Konstanz, Germany. All the cells were cultured in Dulbecco’s Modified Eagles’ Medium

(DMEM) supplemented with 10% Fetal Bovine Serum (FBS). The cells were grown at 37°C in

5% CO2. Dr. Hiroaki Wakimoto, Brain Tumor Research Center, Massachusetts General Hospital,

Boston, kindly provided us with the glioma stem-like cell lines MGG4, MGG6, MGG8 and

MGG23. The GSC, 1035 (or SK1035) was a kind gift from Dr. Santosh Kesari, Pacific

Neuroscience Insitute, Santa Monica. The GSCs were cultured in Neurobasal™ medium

supplemented with 0.5mM L-Glutamine, 20 ng/µl EGF, 20 ng/µl FGF, 40 µg/ml heparin and B-

27®

and N-2 supplements. The cells were grown at 37°C in 5% CO2. The plasmid pPM-C-HA-

CALCR was obtained from Abmgood (catalog no. PV007283). The construct used 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 was not tested. Mutated

CALCR was generated by site-directed mutagenesis (SDM) using QuikChange Multi Site-

Directed Mutagenesis Kit (Catalog no. 200515). The vector control (VC) plasmid was created by

expelling out the CALCR open reading frame using restriction enzymes NheI and XhoI. The

overhangs were end-filled and ligated to generate the VC plasmid. The shRNA plasmid

constructs against RAMP1 (TRCN0000273872, TRCN0000273874 and TRCN0000273814)

were obtained as a kind gift from Dr. Subba Rao and Dr. Saini from MISSION®

shRNA Library

(Sigma Aldrich, USA). RasV12 (KRas) construct was a kind gift from Dr. Annapoorni




6

Rangarajan (IISc). Cells were transfected with Lipofectamine2000. For selection of stable clones

of CALCR and shRNA plasmid constructs, G418 (500-1000 μg/ml) or puromycin (1-2 μg/ml)

respectively were added in the complete medium and selected for 1-2 weeks. ON-TARGETplus

Human CALCR (799) siRNA – SMARTpool (5 nM) was obtained from Dharmacon, India

(Catalog no. L-003635-00-005) and for each experiment 100nM siRNA was transfected using

DharmaFECT transfection reagent.

Other methods are provided in online ‘Supplementary methods’.

Results

Integrated analysis of Indian and TCGA GBM exome identifies pathways with prognostic

value

We have carried out whole exome sequencing (WES) of 42 astrocytoma tissues of Indian

origin (10 grade II, 13 grade III and 19 grade IV/GBM) and matched peripheral blood samples

(Supplementary Table S1). An average of 40±17X coverage was obtained across all samples

(for details please see supplementary information). The matched tumor-blood sequences were

analyzed using MuTect tool (5) and Indelocator (6) to identify tumor-specific non-synonymous

single nucleotide variants (SNVs) and insertions/deletions (indels) respectively (Supplementary

Tables S2-S4). The genetic spectrum of our patient cohort (Indian cohort) was explored through

the analysis of top mutated genes, chromatin modifiers and DNA repair related genes that are

known to be mutated in GBM as per previous reports (3) (Supplementary Fig. S1A-C). As

observed before, TP53 was found to be highly mutated across all grades of astrocytoma with

higher percentage of mutation (65%) in lower grade samples/LGGs (grade II and III) compared

to GBM (32%) (7). Other top mutated genes in GBM as per TCGA study such as PTEN,

PIK3CA, and NF1 were also found to be mutated in GBM samples in Indian cohort (3). We also

found IDH1 and ATRX to be mutated typically in the LGGs as shown before (8,9). To compare

the mutation spectrum of Indian cohort with that of TCGA, the three signaling pathways that

were found to be significantly altered in GBM patients– the receptor tyrosine kinase (RTK)

pathway, the TP53 pathway and the RB pathway (3) were considered. The analysis revealed that

Indian patient cohort behaves largely similar to TCGA cohort (Supplementary Fig. S1D).




7

To identify the defective pathways with genetic alterations in GBM that predict survival, an

integrated analysis involving GBM specific mutated genes derived from Indian and TCGA exome

data was carried out (for details please see in supplementary information; Supplementary Fig.

S2A). Of the several pathways carrying genetic alterations found in GBM, Cox regression analysis

revealed that 62 pathways predict survival in GBM significantly (Supplementary Fig. S2A;

Supplementary Table S5). As expected, this list contained many pathways which were previously

implicated in GBM survival like PI3K-Akt signaling, Ras signaling, mTOR signaling, insulin

signaling, focal adhesion and regulation of actin cytoskeleton (Supplementary Table S5).

However, the top five pathways that predicted survival with very high significance were not

reported previously for their association with GBM survival (Fig. 1A). The “Neuroactive ligand-

receptor interaction pathway” is particularly notable as GBMs with defect in this pathway

(mutation in at least one of the genes) have a poor median survival (3.13 months; p value <0.0001

(Fig. 1B) and it is highly mutated in both TCGA and Indian cohorts (Supplementary Tables S6

and S7 respectively). Multivariate Cox regression analysis with age, G-CIMP methylator

phenotype, MGMT promoter methylation and IDH1 mutation status revealed that the neuroactive

ligand-receptor interaction pathway is an independent predictor of survival in GBM (Fig. 1C).

Mutation or reduced transcript levels of Calcitonin receptor (CALCR) predicts poor survival

in GBM

To gain biological insight into the prognostic association of neuroactive ligand-receptor

pathway, we chose Calcitonin receptor (CALCR) for further studies as it was found to be the top

mutated gene (Supplementary Table S8). The location and nature of the eight tumor derived

mutations in CALCR is shown (Supplementary Fig. S2B). Univariate Cox regression analysis

revealed that mutation in CALCR predicted poor survival in GBM patients (Supplementary

Fig. S2C). Further, Kaplan-Meier survival analysis revealed that GBMs with mutation in

CALCR survived lesser (Fig. 1D; median survival = 4.83 months). Multivariate Cox regression

analysis with other markers such as age, IDH1 mutation and G-CIMP status revealed CALCR

mutation to be an independent prognosticator. On comparison with MGMT promoter

methylation status, CALCR mutation showed a trend towards predicting poor survival with near

significant p value (p=0.075). However, CALCR mutation status lost its significance in

multivariate analysis involving all prognostic markers (Supplementary Fig. S2C), which could

be due to the fact that there were fewer number of patients with CALCR mutations. We




8

evaluated the distribution of CALCR mutated GBM samples with respect to highly mutated

genes in GBM (TP53, PTEN, EGFR, PDGFRA, NF1 and IDH1) and GBM subtypes (G-CIMP,

MGMT, classical, mesenchymal, neural and proneural). Although there was enrichment of

CALCR mutation in patients with WT NF1, PDGFRA, EGFR and IDH1, Odds Ratio testing for

mutual exclusivity showed no significant correlation/mutual exclusivity between CALCR

mutation and any of the highly mutated genes or the different GBM subtypes (Supplementary

Table S9).

Additional investigation revealed CALCR transcript levels is down regulated in GBMs

derived from TCGA, GSE7696 and Indian cohorts (Fig. 1E and F). Kaplan-Meier survival

analysis revealed that GBMs with low levels of CALCR transcript have a poor survival in

TCGA, GSE7696 and Indian cohort (Fig. 1G-J). Further, we found that glioma derived cell lines

have reduced CALCR transcript and protein levels compared to immortalized astrocytes (Fig.

1K and L). From these results, we conclude that CALCR may function as a tumor suppressor

gene in GBM and either mutational inactivation or reduced transcript levels leads to a highly

aggressive GBM with poor survival.

CALCR is a tumor suppressor in GBM

CALCR is a G-protein coupled receptor (GPCR) with an N-terminal ligand binding

domain, a seven-pass transmembrane domain and a C-terminal domain (10). When its ligand,

calcitonin (CT) binds to the N-terminal domain, the receptor undergoes conformational change that

leads to activation of G-protein alpha present at the C-terminal cytosolic side which leads to the

regulation of various downstream signaling pathways thus affecting variety of functions (11). To

test the function of CT-CALCR signaling in glioma, we used various glioma derived established

cell lines, wherein the WT status of CALCR was confirmed (Supplementary Fig. S2D) (12,13).

We first used LN229 glioma cells which express relatively high levels of CALCR (Fig. 1K and

L). The effect of exogenously added CT on various cancer cell-associated properties of empty

vector (VC)-stable and CALCR-stable LN229 cells were tested (Fig. 2A). Exogenous addition of

CT inhibited colony formation, proliferation, migration, invasion and anchorage-independent

growth of LN229/VC stable cells very efficiently (Fig. 2B-F). LN229/CALCR stable cells also

showed significant reduction in these properties compared to LN229/VC stable cells (Fig. 2B-F).

Moreover, exogenously added CT inhibited all the above properties of LN229/CALCR stable cells




9

even more efficiently than LN229/VC stable cells (Fig. 2B-F). Similar results were obtained in

CALCR-expressing cell lines T98G and U87 (Supplementary Fig. S3A-C and S3D-F

respectively). These results suggest that CT inhibits tumorigenic properties of glioma cells in a

CALCR-dependent manner. Further to test the importance of CALCR in CT-mediated functions in

glioma cells, the effect of CT in CALCR silenced LN229, T98G and U87 cells was evaluated. The

inhibition of proliferation and migration by CT seen in non-targeting siRNA transfected cells

(siNT) was significantly abrogated in CALCR siRNA transfected cells (siCALCR) (Fig. 2G-I;

Supplementary Fig. S4A-D).

To study the importance of CALCR for CT functions, the effect of CT on CALCR-low cell

lines (U343 and U373; Fig. 1K and L) was also tested. CT showed either no or very minimal

effect on colony formation, proliferation, migration, invasion and anchorage-independent growth

of U343/VC stable cells (Supplementary Fig. S5A-F) which could be due to low expression of

CALCR in these cells. U343/CALCR stable cells showed significant reduction in the above

properties compared to U343/VC stable cells (Supplementary Fig. S5B-F) suggesting the fact

that mere overexpression of the receptor is able to inhibit these functions. Furthermore,

exogenously added CT inhibited the above properties of U343/CALCR stable cells very efficiently

compared to that of U343/VC cells (Supplementary Fig. S5B-F). Similar results were obtained in

U373 cell line, which also expresses low levels of CALCR (Supplementary Fig. S6A-C). These

results demonstrate that CT inhibits various properties of cancer cells in a CALCR-dependent

manner.

To address the signaling downstream of CT-CALCR cascade, we investigated the status of

AKT, ERK and JNK signaling which are known to regulate various properties of cancer cells (14).

The exogenously added CT efficiently reduced the pAKT, pERK and pJNK levels in

U343/CALCR stable cells but not in U343/VC cells. This reduction in pAKT, pERK and pJNK

levels was seen in both LN229/VC stable and LN229/CALCR stable cells (Fig. 3A). Further,

silencing CALCR in LN229 cells efficiently reversed the inhibition by CT on AKT, ERK and JNK

signaling pathways (Fig. 3A). Receptor activity-modifying proteins (RAMP1, RAMP2 and

RAMP3) are single-transmembrane proteins that induce trafficking of CALCR thereby regulating

CT-CALCR signaling cascade (15). We found that RAMP1 transcript levels, but not RAMP2 and

RAMP3, are higher in LN229 cells where mere addition of CT inhibits various cancer cell




10

properties (Fig. 3B). To know the role of RAMP1 in CT-CALCR signaling cascade, we tested the

ability of CT to inhibit colony formation and proliferation of glioma cells in RAMP1-silenced

condition (shRAMP1) in the absence or presence of exogenously expressed CALCR (Fig. 3C). CT

inhibited both functions equally efficiently in shNT and shRAMP1 conditions 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. 6D). Collectively from these results, we conclude

that CT-CALCR signaling acts as a tumor suppressor pathway as it inhibits various properties of

cancer cells by inhibiting AKT, ERK and JNK pathways and RAMPs are not required for CT-

CALCR signaling cascade in glioma.

Patient derived mutations abolish tumor suppressive functions of CALCR

Since our study finds GBMs with CALCR mutations to be more aggressive with lesser

median survival, we hypothesized that mutations might have abolished the tumor suppressive

functions of CALCR. To test this possibility, each of the seven mutations were introduced into

CALCR through site directed mutagenesis (Fig. 4A) and the ability of exogenously expressed

CALCR mutants by themselves as well as in conjunction with CT on various cancer cell

properties in U343 and LN229 glioma cells was evaluated. We introduced empty vector (VC),

wild type and each of the 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 the presence and absence of CT. While the WT CALCR over expression

(please see “BSA” condition) inhibited glioma cell proliferation, colony formation, migration,

invasion and anchorage-independent growth efficiently, CALCR mutants failed to inhibit these

functions significantly although to varying extents in both U343 and LN229 glioma cells (Fig.

4B-F; Supplementary Fig. S7A-E; Supplementary Fig. S8A-H). Similarly, exogenously

added CT by itself (in LN229 cells) and in the presence of WT CALCR (in LN229 and U343

cells) inhibited all five properties very efficiently. However, the inhibition by CT was

significantly abrogated in LN229 and U343 CALCR mutant-stable clones although to varying

extents (Fig. 4B-F; Supplementary Fig. S7A-E; Supplementary Fig. S8A-H). The loss-of-

function was profound in CALCR mutants, A51T, V250M, A307V and R420C (‘severe

mutants’), while it was minimal in CALCR mutants, R45Q, P100L and R404C (‘mild mutants’).

In order to assess the effect of varying loss-of-function by different CALCR mutants on tumor

aggressiveness, we generated loss-of-function (LOF) score by combining the level of LOF for




11

five different properties in each cell line and this was finally correlated with GBM patient

survival (for detail please see supplementary information). The analysis revealed that the

severe mutants had higher LOF score while the mild mutants had a lower LOF score

(Supplementary Table S10). On comparison with patient survival, there was significant

negative correlation between LOF score and survival (Fig. 4G; Supplementary Fig. S7F).

To address whether the loss-of-function shown by CALCR mutants is due to their

inability to inhibit downstream signaling pathways unlike WT CALCR, we assessed the effect of

CALCR mutations on downstream AKT, ERK and JNK signaling pathways in U343 cell line

(Supplementary Fig. S9). Addition of CT to U343/VC cells led to a minimal reduction of

pAKT, pERK and pJNK levels. However, over expression of WT CALCR led to a significant

reduction in phosphorylation of the above signaling molecules which was further reduced when

CT was added to U343/CALCR cells (Supplementary Fig. S9, compare lanes 3 and 4 with 1

and 2). However, the mutant CALCRs both in the absence and presence of exogenously added

CT inhibited these three signaling pathway much less efficiently, although the effect was more

pronounced 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 of CALCR exhibit varied loss-of-

function phenotypes. This could be explained by the fact that different mutations may have

varying impact in altering the structure of CALCR. The crystal structure of the N-terminal

domain, along with calcitonin ligand bound to it has been crystalized and the structure has been

determined (PDB ID: 5II0; (16)). We used three servers - mCSM, SDM and DUET to quantify

the influence of R45Q, A51T and P100L mutations (located in the N—terminal domain) in

disruption of the protein stability of CT-CALCR complex (measured by the change in Gibbs free

energy ΔΔG between the wild-type and mutant structures). All three tools predicted A51T

mutation, one of the severe mutants, to be destabilizing. However, the above analysis predicted

R45Q and P100L (both mild mutants) to be neutral in nature (Supplementary Fig. S10).

Collectively from the above results, we can conclude that mutation in CALCR abrogates CT-

CALCR tumor suppressor signaling axis thus contributing significantly to the more aggressive

phenotype seen in GBMs.




12

Effect of CT-CALCR tumor suppressor axis on glioma stem-like cells (GSCs)

Next, we evaluated the function of CT-CALCR axis in patient-derived glioma stem-like

cells (GSCs) as well as glioma cell line derived GSCs. According to 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 (Fig. 5A, Fig. 1L and

Supplementary Fig. S11A). The WT nature of CALCR in these lines was confirmed except

MGG6, MGG23 and 1035 (Supplementary Fig. S2D). CT was exogenously added to each of

the GSCs and the effect on neurosphere growth was observed by sphere formation and limiting

dilution assays. While CT inhibited the sphere growth in most of the GSCs, the percentage

inhibition of sphere growth was found to be significantly higher in CALCR-high GSCs

compared to the CALCR-low GSCs (Fig. 5B-E). The glioma reprogramming factors - SOX2,

OLIG2, SALL2 and POU3F2 as identified by Suva et al., were found to be downregulated in CT

condition and this was more prominent in CALCR-high GSCs (Fig. 5F) (17). Further, addition

of CT to CALCR-high GSCs (MGG8, 1035 and LN229) led to a significant inhibition of pERK

and pAKT levels, which were less pronounced in the CALCR-low GSCs (U343 and MGG4)

(Fig. 5G). Next, we evaluated the effect of CT-CALCR axis on the growth of xenograft-derived

neurospheres (xGSC). Addition of CT to xGSCs significantly reduced the number as well as size

of the neurospheres (Supplementary Fig. S11B and C). Additionally, the effect of CT-CALCR

pathway was tested on reprogramming of established glioma cell lines to form GSCs. We

observed that addition of CT during reprogramming inhibited neurosphere formation

significantly in CALCR-high cell line (LN229) unlike CALCR-low cell lines (T98G, U87, U343

and U373) (Supplementary Fig. S12A-E). These results demonstrate that CT-CALCR axis

potently inhibits the growth of GSCs as well as reprogramming of glioma cell lines in a CALCR-

dependent manner.

CT-CALCR tumor suppressor axis is a potential therapeutic target

To confirm the tumor suppressive function of CT-CALCR axis, we tested the effect of

CALCR co-transfection on the ability of Ras (KRasV12) to transform SV40 immortalized mouse

astrocytes (IMA2.1 cells) in vitro. We observed that Ras transformed IMA2.1 cells efficiently as

seen by the increased number of colonies in soft agar (Fig. 6A and B bar 1). Further, we tested the




13

effects of WT and mutated CALCR on astrocyte transformation. While WT CALCR inhibited

Ras-mediated transformation very efficiently (Fig. 6A and B compare bar 2 with 1), CALCR

mutants failed to inhibit Ras mediated transformation efficiently although to varying levels (Fig.

6A and B compare bars 3 to 9 with 2). In particular, the severe mutants with highest LOF score

(A51T and V250M) were found to have completely lost the ability to inhibit Ras-mediated

transformation. To ascertain pathways that could be involved in CALCR-mediated inhibition of

transformation by RasV12, we evaluated the effect of CALCR on the phosphorylation status of

ERK, AKT and JNK molecules in RasV12 transformed cells. Ras-transformed IMA2.1 cells

showed an increase in pERK and pJNK (Supplementary Fig. S13; compare lane 3 with 1),

which was abrogated significantly when CALCR was exogenously introduced (Supplementary

Fig. S13; compare lane 4 with 3). These results demonstrate that CALCR targets ERK, JNK and

AKT signaling molecules independent of Ras and perhaps involving other signaling pathways. To

evaluate the importance of CT-CALCR axis as a therapeutic target, we tested the effect of CT

intra-peritoneal injections on the xenograft tumor growth of LN229-luc cells in NIH female nu/nu

mice. We found that treatment with CT inhibited LN229 xenograft tumor growth significantly

(Fig. 6C-E). In summary, these results confirm the tumor suppressive nature of CT-CALCR axis

and highlight the importance of the axis as a novel therapeutic target in glioma (Fig. 6F). When

glioma cells harbor WT CALCR (left panel), binding of CT leads to inhibition of JNK, ERK and

AKT phosphorylation resulting in reduced oncogenic properties of the cells such as proliferation,

migration, invasion and anchorage-independent growth capacity. This ultimately contributes to

better survival of GBM patients with less aggressive tumor. Also, treatment with calcitonin could

be an option for therapy for these patients. However, when CALCR gets mutated (right panel),

binding of CT to CALCR, change in conformation of the receptor or activation of G-protein by

CALCR may be abrogated and this will damage the inhibitory signals downstream. Therefore,

increased levels of pERK, pAKT and pJNK levels are observed with a resultant increase in

oncogenic properties of the glioma cells mentioned before. Hence, this will result in poor survival

in GBM patients with very aggressive tumor.

Discussion

In this study, we analyzed somatic mutations in an Indian cohort of 42 gliomas compared

with matched blood samples using whole exome sequencing. The mutation spectrum was found

to be largely similar to that of TCGA (3). While TP53, IDH1 and ATRX were mutated typically




14

in lower grades, mutations in PTEN, PIK3CA and NF1 were largely seen in GBMs. Integrative

analysis of the exome data of Indian and TCGA cohorts identified several pathways to be

associated with GBM survival. GBMs with mutations in one or more genes that belong to

“neuroactive ligand-receptor interaction pathway” predicted worst prognosis. We also show that

calcitonin receptor (CALCR), the top mutated gene belonging to the above pathway, along with

its ligand functions as a tumor suppressor axis and inactivating mutations/reduced transcript

levels in CALCR defines a highly aggressive subset of GBM with very poor survival.

An integrated survival analysis involving GBM specific mutated genes derived from

Indian and TCGA cohorts identified several pathways being associated with GBM survival. Of

these, genetic alterations in “neuroactive ligand-receptor interaction pathway” genes were found

to be associated with poor survival with high significance. This pathway consists of a large

number of G protein-coupled receptors which upon activation by their respective ligands have

been shown to regulate neuronal signaling in specific ways thus influencing variety of animal

behavior (18). Epigenetic alterations in neuroactive ligand-receptor interaction pathway have

been shown to be associated with risk of developing pancreatic cancer (19,20), small cell lung

cancer (21), renal cell carcinoma (22), hepatocellular carcinoma (23) etc. In TCGA pan-cancer

data study, neuroactive ligand-receptor interaction pathway came up to be the fifth most highly

mutated pathways in cancer (24). However, there are no studies that show the functional

significance of genetic alterations in this pathway with respect to cancer development. This study

demonstrates that mutational alteration of neuroactive-ligand interaction pathway promotes

GBM aggressiveness. Our finding has translational relevance as agonists and antagonists for

many GPCRS are available and hence one could utilize a drug repositioning approach wherein

the known GPCR inhibitors may have potential anti-cancer therapeutic implications (25).

Calcitonin (CT), the ligand of CALCR, is a 32 amino acid polypeptide hormone

synthesized primarily by thyroid (26). Binding of CT to CALCR regulates variety of signaling

downstream resulting in the regulation of bone metabolism, calcium flux and cancer cell

proliferation (26-29). While mutations in CALCR gene have been reported in lung

adenocarcinoma (30), the functional importance of CALCR mutations with respect to cancer

development is not known. Our study demonstrates that CT-CALCR signaling inhibits cell

proliferation, migration, invasion and anchorage-independent growth of established glioma cell

lines with a concomitant inhibition of downstream AKT, MEK and JNK signaling. Further, we




15

show that somatic mutations in CALCR led to loss-of-function (LOF) in glioma cells and

patients with mutated CALCR exhibited poor prognosis. In fact, the LOF score, calculated from

the experiments (depicts the severity of the mutants), correlated significantly with patient

survival although the small number of samples preclude the ability to make strong conclusions.

Our study reveals the potential of the CT-CALCR axis as a novel therapeutic target as

observed by its effectiveness in the inhibition of glioma stem-like cells that led to a significant

decrease in glioma reprogramming factors. The role of CALCR as a tumor suppressor was

further validated by its potency to inhibit the first event in tumor initiation, i.e., transformation.

Indeed, CALCR inhibited RasV12-mediated transformation of immortalized astrocytes in vitro.

Moreover, CALCR was found to be capable of inhibiting pERK and pJNK even in presence of

constitutively active oncogenic Ras which suggests that CALCR is capable of directly regulating

signaling molecules present downstream of Ras. While Ras is known to activate MEK kinase

which in turn can activate ERK and other pathways such as JNK (31), it is also known that

downstream to GPCR, other upstream molecules such as PKA (32), Rac (33) can regulate ERK

and CDC42 (34), Gαi (35) can regulate JNK. Thus, we demonstrate that CT-CALCR axis is a

direct inhibitor of oncogenic signaling downstream to Ras, which further underscores the

importance of CT-CALCR axis as a compelling tumor suppressor pathway in glioma. This was

substantiated by the result that intra-peritoneal injection of CT in NIH nu/nu mice, inoculated

with LN229-luc cells to form subcutaneous flank tumor, reduced the tumor burden significantly.

Thus our study identifies CT-CALCR axis acts as a tumor suppressor pathway in GBM.

Mutational inactivation of CALCR or reduced CALCR transcript levels leads to an aggressive

GBM with poor survival. Our findings have multiple translational implications. Most

importantly, for GBMs with wild type CALCR, Calcitonin could be considered as a treatment

option (36). In fact, salmon calcitonin is prescribed for post-menopausal osteoporosis (37) and

also in therapy of giant cell granuloma (38). For GBMs with mutated CALCR receptor, a

combination of inhibitors of AKT, MEK and JNK pathways could be tried.




16

Acknowledgements

The results published here are in whole or part based upon data generated by The Cancer

Genome Atlas pilot project established by the NCI and NHGRI. 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

Dr Hiroaki Wakimoto, Dr Samuel Rabkin and Dr. Santosh Kesari for providing us with GSCs.

We thank Dr. Stefan Schildknecht for providing mouse immortalized astrocyte cells. JP

acknowledges Indian Institute of Science for the research fellowship. VP and JP thank DBT,

Government of India for financial support. The NGS facility, Indian Institute of Science is

acknowledged for exome sequencing. The Centre for Animal Facility (CAF), Indian Institute of

Science and Dr. Krishnaveni (CAF) are acknowledged. KS acknowledges CSIR and DBT,

Government of India for research grant. Infrastructure support by funding from DST-FIST, DBT

grant-in-aid and UGC (Centre for Advanced Studies in Molecular Microbiology) to MCB is

acknowledged. KS is a J. C. Bose Fellow of the Department of Science and Technology. Prof.

Partha Majumder (NIBMG) and Arjun Arkal Rao are acknowledged for their invaluable inputs.




17

References

1. Cancer Genome Atlas Research N. Comprehensive genomic characterization defines human

glioblastoma genes and core pathways. Nature 2008;455(7216):1061-8 doi 10.1038/nature07385.

2. Frattini V, Trifonov V, Chan JM, Castano A, Lia M, Abate F, et al. The integrated landscape of

driver genomic alterations in glioblastoma. Nature genetics 2013;45(10):1141-9 doi

10.1038/ng.2734.

3. Brennan CW, Verhaak RG, McKenna A, Campos B, Noushmehr H, Salama SR, et al. The

somatic genomic landscape of glioblastoma. Cell 2013;155(2):462-77 doi

10.1016/j.cell.2013.09.034.

4. Stupp R, Hegi ME, Mason WP, van den Bent MJ, Taphoorn MJ, Janzer RC, et al. Effects of

radiotherapy with concomitant and adjuvant temozolomide versus radiotherapy alone on survival

in glioblastoma in a randomised phase III study: 5-year analysis of the EORTC-NCIC trial. The

Lancet Oncology 2009;10(5):459-66 doi 10.1016/S1470-2045(09)70025-7.

5. Cibulskis K, Lawrence MS, Carter SL, Sivachenko A, Jaffe D, Sougnez C, et al. Sensitive

detection of somatic point mutations in impure and heterogeneous cancer samples. Nature

biotechnology 2013;31(3):213-9 doi 10.1038/nbt.2514.

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

7. Ohgaki H, Kleihues P. Genetic pathways to primary and secondary glioblastoma. The American

journal of pathology 2007;170(5):1445-53 doi 10.2353/ajpath.2007.070011.

8. Vigneswaran K, Neill S, Hadjipanayis CG. Beyond the World Health Organization grading of

infiltrating gliomas: advances in the molecular genetics of glioma classification. Annals of

translational medicine 2015;3(7):95 doi 10.3978/j.issn.2305-5839.2015.03.57.

9. Kannan K, Inagaki A, Silber J, Gorovets D, Zhang J, Kastenhuber ER, et al. Whole-exome

sequencing identifies ATRX mutation as a key molecular determinant in lower-grade glioma.

Oncotarget 2012;3(10):1194-203 doi 10.18632/oncotarget.689.

10. Ji TH, Grossmann M, Ji I. G protein-coupled receptors. I. Diversity of receptor-ligand

interactions. The Journal of biological chemistry 1998;273(28):17299-302.

11. Kobilka BK. G protein coupled receptor structure and activation. Biochimica et biophysica acta

2007;1768(4):794-807 doi 10.1016/j.bbamem.2006.10.021.

12. Patil V, Pal J, Somasundaram K. Elucidating the cancer-specific genetic alteration spectrum of

glioblastoma derived cell lines from whole exome and RNA sequencing. Oncotarget

2015;6(41):43452-71 doi 10.18632/oncotarget.6171.

13. Degrauwe N, Schlumpf TB, Janiszewska M, Martin P, Cauderay A, Provero P, et al. The RNA

Binding Protein IMP2 Preserves Glioblastoma Stem Cells by Preventing let-7 Target Gene

Silencing. Cell reports 2016;15(8):1634-47 doi 10.1016/j.celrep.2016.04.086.

14. New DC, Wong YH. Molecular mechanisms mediating the G protein-coupled receptor regulation

of cell cycle progression. Journal of molecular signaling 2007;2:2 doi 10.1186/1750-2187-2-2.

15. Morfis M, Tilakaratne N, Furness SG, Christopoulos G, Werry TD, Christopoulos A, et al.

Receptor activity-modifying proteins differentially modulate the G protein-coupling efficiency of

amylin receptors. Endocrinology 2008;149(11):5423-31 doi 10.1210/en.2007-1735.

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-ray Crystallography. The Journal of biological

chemistry 2016;291(26):13689-98 doi 10.1074/jbc.M116.726034.




18

17. Suva ML, Rheinbay E, Gillespie SM, Patel AP, Wakimoto H, Rabkin SD, et al. Reconstructing

and reprogramming the tumor-propagating potential of glioblastoma stem-like cells. Cell

2014;157(3):580-94 doi 10.1016/j.cell.2014.02.030.

18. Engel SR, Grant KA. Neurosteroids and behavior. International review of neurobiology

2001;46:321-48.

19. Wei P, Tang H, Li D. Insights into pancreatic cancer etiology from pathway analysis of genome-

wide association study data. PloS one 2012;7(10):e46887 doi 10.1371/journal.pone.0046887.

20. Li L, Hanahan D. Hijacking the neuronal NMDAR signaling circuit to promote tumor growth and

invasion. Cell 2013;153(1):86-100 doi 10.1016/j.cell.2013.02.051.

21. Jahchan NS, Dudley JT, Mazur PK, Flores N, Yang D, Palmerton A, et al. A drug repositioning

approach identifies tricyclic antidepressants as inhibitors of small cell lung cancer and other

neuroendocrine tumors. Cancer discovery 2013;3(12):1364-77 doi 10.1158/2159-8290.CD-13-

0183.

22. Liu X, Wang J, Sun G. Identification of key genes and pathways in renal cell carcinoma through

expression profiling data. Kidney & blood pressure research 2015;40(3):288-97 doi

10.1159/000368504.

23. Zhang MH, Shen QH, Qin ZM, Wang QL, Chen X. Systematic tracking of disrupted modules

identifies significant genes and pathways in hepatocellular carcinoma. Oncology letters

2016;12(5):3285-95 doi 10.3892/ol.2016.5039.

24. Dees ND, Zhang Q, Kandoth C, Wendl MC, Schierding W, Koboldt DC, et al. MuSiC:

identifying mutational significance in cancer genomes. Genome research 2012;22(8):1589-98 doi

10.1101/gr.134635.111.

25. Liu Y, An S, Ward R, Yang Y, Guo XX, Li W, et al. G protein-coupled receptors as promising

cancer targets. Cancer letters 2016;376(2):226-39 doi 10.1016/j.canlet.2016.03.031.

26. Masi L, Brandi ML. Calcitonin and calcitonin receptors. Clinical cases in mineral and bone

metabolism : the official journal of the Italian Society of Osteoporosis, Mineral Metabolism, and

Skeletal Diseases 2007;4(2):117-22.

27. Purdue BW, Tilakaratne N, Sexton PM. Molecular pharmacology of the calcitonin receptor.

Receptors & channels 2002;8(3-4):243-55.

28. Robbins EW, Travanty EA, Yang K, Iczkowski KA. MAP kinase pathways and calcitonin

influence CD44 alternate isoform expression in prostate cancer cells. BMC cancer 2008;8:260 doi

10.1186/1471-2407-8-260.

29. Terra SR, Cardoso JC, Felix RC, Martins LA, Souza DO, Guma FC, et al. STC1 interference on

calcitonin family of receptors signaling during osteoblastogenesis via adenylate cyclase

inhibition. Molecular and cellular endocrinology 2015;403:78-87 doi 10.1016/j.mce.2015.01.010.

30. George J, Lim JS, Jang SJ, Cun Y, Ozretic L, Kong G, et al. Comprehensive genomic profiles of

small cell lung cancer. Nature 2015;524(7563):47-53 doi 10.1038/nature14664.

31. Xia Y, Makris C, Su B, Li E, Yang J, Nemerow GR, et al. MEK kinase 1 is critically required for

c-Jun N-terminal kinase activation by proinflammatory stimuli and growth factor-induced cell

migration. Proceedings of the National Academy of Sciences of the United States of America

2000;97(10):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 the Gesellschaft fur Biochemie und

Molekularbiologie Lecture delivered on 5 July 2003 at the Special FEBS Meeting in Brussels.

The FEBS journal 2005;272(14):3491-504 doi 10.1111/j.1742-4658.2005.04763.x.

33. Eblen ST, Slack JK, Weber MJ, Catling AD. Rac-PAK signaling stimulates extracellular signal-

regulated kinase (ERK) activation by regulating formation of MEK1-ERK complexes. Molecular

and cellular biology 2002;22(17):6023-33.

34. Wang L, Yang LD, Burns K, Kuan CY, Zheng Y. Cdc42GAP regulates c-Jun N-terminal kinase

(JNK)-mediated apoptosis and cell number during mammalian perinatal growth. Proceedings of




19

the National Academy of Sciences of the United States of America 2005;102(38):13484-9 doi

10.1073/pnas.0504420102.

35. Bastin G, Yang JY, Heximer SP. Galphai3-Dependent Inhibition of JNK Activity on Intracellular

Membranes. Frontiers in bioengineering and biotechnology 2015;3:128 doi

10.3389/fbioe.2015.00128.

36. Wookey PJ, McLean CA, Hwang P, Furness SG, Nguyen S, Kourakis A, et al. The expression of

calcitonin receptor detected in malignant cells of the brain tumour glioblastoma multiforme and

functional properties in the cell line A172. Histopathology 2012;60(6):895-910 doi

10.1111/j.1365-2559.2011.04146.x.

37. Leggate J, Farish E, Fletcher CD, McIntosh W, Hart DM, Sommerville JM. Calcitonin and

postmenopausal osteoporosis. Clinical endocrinology 1984;20(1):85-92.

38. Pogrel MA. Calcitonin therapy for central giant cell granuloma. Journal of oral and maxillofacial

surgery : official journal of the American Association of Oral and Maxillofacial Surgeons

2003;61(6):649-53; discussion 53-4 doi 10.1053/joms.2003.50129.




20

Figure Legends

Figure 1. Clinical significance of neuroactive ligand-receptor interaction pathway and

Calcitonin receptor (CALCR) in GBM. A) Top significant mutated pathways (with ≥5% genes

mutated and ≥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 plotted on the X-axis. The

number on the right of each bar represents the percentage of genes mutated in the corresponding

pathway. B) Kaplan-Meier survival analysis of GBMs stratified by the genetic status of

neuroactive ligand-receptor interaction pathway. “Altered” refers to patients having mutation in

one or more of the genes in the pathway. C) Multivariate Cox regression analysis of neuroactive

ligand-receptor interaction pathway (denoted by $) with age, G-CIMP methylation, MGMT

promoter methylation and IDH1 mutation status. D) Kaplan-Meier survival analysis of GBMs

stratified by CALCR mutation status. Note: While there were 8 patients with mutation found in

the analysis, only 7 patients had survival information. E) RNA levels of CALCR from

microarray data in TCGA Agilent, TCGA Affymetrix and GSE7696 datasets. F) Real time qPCR

analysis of RNA levels of CALCR in Indian patient cohort (control = 5; GBM = 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) and Indian patient

cohort (J). K) RNA levels of CALCR in glioma-derived cell lines compared to immortalized

astrocytes. L) Protein levels of CALCR in glioma-derived cell lines versus immortalized

astrocytes. The p values for panels A-K are represented by *, ** and *** which denotes p values

of < 0.05, 0.01 and 0.001 respectively.

Figure 2. Effect of Calcitonin (CT) on various properties of CALCR-high LN229 glioma

cells. A) Overexpression of CALCR in LN229 cell line verified by checking RNA and protein

levels. B) Colony suppression assay, C) Proliferation assay, D) Migration assay, E) Invasion

assay and F) Soft agar assay for CALCR in vector control (VC)/ CALCR (wild-type) conditions

in presence or absence of CT. All assays are quantified and the bar plots are provided to the right

side of the 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+BSA) was normalized to 100%




21

and the values for the other conditions (VC+CT, CALCR+BSA and CALCR+CT) were

calculated with respect to normalized VC+BSA. G) Silencing of CALCR in LN229 cell line

verified by checking RNA and protein levels. H) Proliferation assay and I) Migration assay in

CALCR silenced conditions in presence or absence of CT. All assays are quantified and the bar

plots are provided to the right side of the 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

(siNT +BSA) was normalized to 100% and the values for the other conditions (siNT+CT,

siCALCR+BSA and siCALCR+CT) were calculated with respect to normalized siNT +BSA.

The p values for all panels are represented by *, ** and *** which denotes p values of < 0.05,

0.01 and 0.001 respectively and NS refers to non-significant p value (≥0.05).

Figure 3. Regulation of ERK, JNK and AKT signaling by CT-CALCR signaling axis and

the role of RAMP co-receptors in CALCR-mediated tumor suppressor functions in glioma

cells. A) Western blot analysis of phosphorylation of downstream signaling molecules ERK,

JNK and AKT in CALCR overexpression conditions (in U343 and LN229 cells) and CALCR-

silenced condition (in LN229 cells) in presence or absence of CT. The quantification for each

phospho-protein is provided at the bottom of 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 value for VC+BSA for each phospho-protein was normalized to 1 and

the other conditions (VC+CT, CALCR+BSA and CALCR+CT) were calculated with respect to

the normalized VC+BSA. B) Transcript levels of RAMP1, 2 and 3 in LN229 cells compared to

control brain tissue. C) Knockdown of RAMP1 in LN229 cells shown by real time qPCR and

western blotting. D) Colony suppression assay in LN229/VC and LN229/CALCR stable cells

transfected with shRAMP1. E) Proliferation assay in LN229/VC and LN229/CALCR stable cells

transfected with shRAMP1. The quantification for 6th

day of proliferation as given in the

Supplementary figure S6D is given in bar plot, wherein the value for LN229/VC/shNT+BSA

condition was normalized to 100% and the rest of the conditions were plotted accordingly. NS

refers to non-significant p value (≥0.05).

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 the mutations in the protein

domains. Quantification of Proliferation assay (B), Colony suppression assay (C), Migration




22

assay (D), Invasion assay (E) and Soft agar assay (F) for CALCR overexpression in U343 cells

transfected with WT CALCR and the seven mutated CALCRs (The eighth mutation Y186C was

not included in this analysis as this position is absent in the transcript variant 2 of CALCR

(transcript ID: ENST000009994441) used in this study). The value of the control condition

(VC+BSA) was normalized to 100% and the values for the other conditions were calculated with

respect to normalized VC+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 denotes 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. This analysis did not include R45Q

as the patient harboring this mutation did not have survival information. Please see

supplementary information for LOF score calculation.

Figure 5. Effect of CT-CALCR tumor suppressor axis on glioma stem-like cells.

A) Transcript levels of CALCR in patient-derived glioma stem-like cells (GSCs) and cell line

derived GSCs as detected by real time qPCR. The transcript levels divide the GSCs into

CALCR-low (MGG4, T98G, U87, U343 and U373) and CALCR-high (1035, MGG4, MGG6,

MGG8 and MGG23). B, C) GSC growth as neurospheres was assessed in the presence of BSA

or CT. The percentage inhibition of neurosphere growth in CT condition as compared to BSA

when all spheres (B) and spheres with size >30µm in diameter (C) were considered. For each

GSC cell line, the number of spheres in the BSA condition was normalized to 100% and then the

CT condition was 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. = low magnification (2.5X) and H.M. = high

magnification (10X). E) Limiting dilution assay for GSCs. For BSA and CT conditions, 1, 5, 10,

20, 50, 100, 200 cells were plated (n=12). At the endpoint, number of wells not having any

sphere was calculated and the graph was plotted using Extreme Limiting Dilution Analysis

(ELDA) software. Total number of cells (dose) is plotted on the X-axis and log fraction of

nonresponding/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 CT condition compared to BSA in various GSC cell lines tested. The Log 2




23

values are plotted for CT calculated with respect to the BSA condition (normalized to 0). G)

pERK and pAKT levels in GSCs in BSA versus CT conditions in CALCR-low GSCs (U343 and

MGG4) and CALCR-high GSCs (MGG8, 1035 and LN229). The quantification for each

phospho-protein is provided at the bottom of 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 value for BSA for each phospho-protein per cell line was normalized to

1 and value for CT was calculated in comparison to the normalized BSA. The p values for all the

panels are represented by *, ** and *** which denotes p values of < 0.05, 0.01 and 0.001

respectively.

Figure 6. Effect of CALCR on Ras-mediated transformation of immortalized astrocytes in

vitro and in vivo xenograft tumor growth. A) Transformation of mouse immortalized

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/CALCR mutants was calculated from A and plotted. C) The pictorial representation

of the experimental design of in vivo xenograft mouse model for testing the therapeutic efficacy

of CT. The day 0 begins with the subcutaneous injection of LN229-luc cells in the NIH nu/nu

mice (n=4). Luciferase reading was taken every 5 days till day 30. The CT injection regime

followed was - days 10 - 17 (1 I.U./mouse/24 hrs) and days 18 – 25 (1 I.U./mouse/48 hrs). D)

The tumor growth (days 10 – 30) for BSA and CT injected mice are shown by bioluminescence

imaging. E) The total flux of luminescence from the tumors of BSA and CT treated mice are

plotted. The scale has been adjusted to – minimum flux = 600 radiance counts (photon/s) and

maximum flux = 2000 radiance counts (photon/s). The p values for panels B and E represented

by *, ** and *** which denotes p values of < 0.05, 0.01 and 0.001 respectively. F) Graphical

representation of the 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 on the

right describes how CALCR mutation abolishes CT-CALCR tumor suppressor pathway leading

to an aggressive GBM tumor.




D

G

Normal GBM -5

-4

-3

-2

-1

0

1

Lo

g 2

ra

tio

Indian cohort

**

E

F H

I K

IHA

SV

G

U8

7

LN

22

9

T9

8G

U3

73

U3

43

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 months

p value = 0.001

0 50 100 150 0

20

40

60

80

100

Overall survival (Months)

Per

cen

t su

rviv

al

TCGA Affymetrix

Low expression (n= 61)

Median survival = 14.47

months


0 20 40 60 80 0

20

40

60

80

100

High expression (n= 19)


months

Per

cen

t su

rviv

al

p value = 0.003

GSE7696 J Low expression (n=11)


months

High expression (n=27)


months

0 10 20 30 40 50 60 0

20

40

60

80

100

Per

cen

t su

rviv

al

p value = 0.006


Indian cohort

Low expression

(n=107)

Median survival =

11.9 months

High expression

(n=428)

Median survival =

14.6 months

Per

cen

t su

rviv

al


TCGA Agilent

0 20 40 60 80 100 120 140 0

20

40

60

80

100

p value = 0.018

L

0 2 4 6 8 10 12 14 16 18 20

Neuroactive ligand-receptor

interaction

Oxytocin signaling pathway

RNA transport

cGMP-PKG signaling pathway

Th17 cell differentiation

- Log10 p value C

A 7.48

5.52

6.54

7.19

7.33

Pal et al., 2017, Figure 1

Lo

g 2

ra

tio

GBM cell line Immortalized

astrocytic cell line

-3

-2

-1

0

1

2 IH

A

SV

G

U8

7

LN

22

9

T9

8G

U3

73

U3

43

***

B

6

Normal GBM Normal GBM Normal GBM

-4

-2

0

2

4

TCGA

Agilent

TCGA

Affymetrix

GSE7696

** *** *

Lo

g 2

ra

tio

p value < 0.0001


Neuroactive ligand-receptor

interaction pathway

0 10 20 30 40 50 60 70 0

20

40

60

80

100

Per

cen

t su

rviv

al

Altered (n = 23)

Median survival =

3.13 months

Wild type (n = 218)

Median survival =

14.73 months

p value = 0.009


Per

cen

t su

rviv

al

0 10 20 30 40 50 60 70 0

20

40

60

80

100

CALCR

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 value

I. Univariate analysis TCGA dataset

Age 241 1.039 0.038 <0.0001

G-CIMP methylation 240 0.229 -1.475 0.004

MGMT methylation 183 0.593 -0.523 0.008

IDH1 mutation 241 0.249 -1.389 0.006

Neuroactive$ 241 7.527 2.018 <0.0001

II. Multivariate analysis with TCGA dataset

Age 241 1.029 0.029 <0.0001

Neuroactive 5.617 1.726 <0.0001

G-CIMP 240 0.253 -1.374 0.007

Neuroactive 6.980 1.943 <0.0001

MGMT 183 0.654 -0.425 0.033

Neuroactive 6.295 1.840 <0.0001

IDH1 241 0.276 -1.287 0.011

Neuroactive 7.090 1.959 <0.0001

III. Multivariate analysis of all the markers in TCGA dataset

Age 183 1.032 0.032 0.001

G-CIMP 0.000 -9.647 0.946

MGMT 0.792 -0.233 0.239

IDH1 5482 8.609 0.952

Neuroactive 4.636 1.534 <0.0001




LN

22

9/

VC

LN

22

9/

CA

LC

R

BSA CT

0

1

2

3

4

5

6

7

8

9

0 1 2 3 4 5 6 Days

No

. o

f p

roli

fera

tin

g c

ells

(x

15

,00

0)

LN

22

9/

VC

LN

22

9/

CA

LC

R

BSA CT

0

20

40

60

80

100

120

% C

ells

mig

rate

d

BSA

CT

BSA

CT

**

** *

LN229/

VC LN229/

CALCR

0

20

40

60

80

100

120

BSA CT BSA CT

LN229/

siNT

LN229/

siCALCR

*

% C

ells

mig

rate

d

A B C

D E

G H I

-1 0 1 2 3 4 5 6 7 8 9

10

LN229/

VC

LN229/

CALCR

CALCR

Actin

Lo

g2 r

ati

o

LN

22

9/

CA

LC

R

LN

22

9/

VC

BSA

CT

BSA CT

LN

22

9/

siN

T

LN

22

9/

siC

AL

CR

LN

22

9/

VC

LN

22

9/

CA

LC

R

BSA CT

0

20

40

60

80

100

120

% C

ells

in

va

ded

BSA CT BSA CT

LN229/

VC

LN229/

CALCR

**

**

***

F

% C

olo

nie

s

0

20

40

60

80

100

120

**

**

***

BSA CT BSA CT

LN229/

VC

LN229/

CALCR


-2.5

-2.0

-1.5

-1.0

-0.5

0.0

0.5

Lo

g2

rati

o

LN229/

siCALCR

LN229/

siNT

CALCR

Actin

BSA CT BSA CT

LN229/

siNT

LN229/

siCALCR

% P

roli

fera

tin

g c

ells

0

20

40

60

80

100

120 ** Day 5

0

20

40

60

80

100

120

BSA CT BSA CT

LN229/

VC

LN229/

CALCR

* NS

***

% C

olo

nie

s

0

20

40

60

80

100

120

BSA CT BSA CT

% P

roli

fera

tin

g c

ells

LN229/

VC

LN229/

CALCR

*** ***

*

Day 6

LN229/VC + CT

LN229/CALCR + BSA

LN229/CALCR + CT

LN229/VC + BSA

0

1

2

3

4

5

6

7

8

9

0 1 2 3 4 5 Days

No

. o

f p

roli

fera

tin

g c

ells

(x

15

,00

0)

LN229/siNT + CT

LN229/siCALCR + CT

LN229/siNT + BSA

LN229/siCALCR + BSA




RAMP1

RAMP2

RAMP3

-1.5

-1.0

-0.5

0.0

0.5

1.0

1.5

Control LN229

Log

2 r

ati

o

BS

A

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

-0.5

0.0

0.5

shNT shRAMP1

Lo

g2 r

ati

o

D


E

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

roli

fera

tin

g c

ells

VC+

CT CALCR+

CT CALCR+

BSA VC+

BSA

NS

NS

NS

NS

Day 6

A

BSA 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




A

U343/CALCR

U343/R45Q

U343/P100L

U343/VC

U343/A51T

U343/V250M

U343/A307V

U343/R404C

U343/R420C

B

Spearman R -0.89

p value 0.03

V250M A51T

R420C A307V

P100L

R404C

C

D

E

F

G

***

0

20

40

60

80

100

120

BSA CT

% C

olo

nie

s

Colony formation assay

***

0

20

40

60

80

100

120

140

BSA CT

% P

roli

fera

tin

g c

ells

Proliferation Assay (Day 6)

***

***

***

0

20

40

60

80

100

120

BSA CT

% C

ells

mig

rate

d

Migration assay

**

0.0 0.2 0.4 0.6 0.8 1.0 0

5

10

15

20

25

LOF score

Pati

ent

surv

iva

l (M

on

ths)


0

20

40

60

80

100

120

BSA CT

*** * Invasion assay

% C

ells

in

va

ded

0

20

40

60

80

100

120

BSA CT

Soft agar assay ***

**

% C

olo

nie

s

GDP α

β

γ

G - protein

C-ter

N-ter

Hormone receptor domain

Extracellular

Cytoplasm

1 2

3

4

5

6 7

1. R45Q

2. A51T

3. P100L

4. V250M

5. A307V

6. R404C

7. R420C




-10

-8

-6

-4

-2

0

2

4

6

8 M

GG

4

T9

8G

U8

7

U3

43

U3

73

10

35

MG

G6

MG

G8

MG

G2

3

LN

22

9

CALCR Low CALCR High

CA

LC

R L

ow

C

AL

CR

Hig

h


Lo

g 2

ra

tio


-20

-10

0

10

20

30

40

50

60

70

80

MG

G4

T9

8G

U8

7

U3

43

U3

73

10

35

MG

G6

MG

G8

MG

G2

3

LN

22

9

% S

ph

ere

inh

ibit

ion

All spheres


-20

0

20

40

60

80

100

120

MG

G4

T9

8G

U8

7

U3

43

U3

73

10

35

MG

G6

MG

G8

MG

G2

3

LN

22

9

% S

ph

ere

inh

ibit

ion

>30μM spheres

** *

**

-7

-6

-5

-4

-3

-2

-1

0

1

MGG4 T98G U87 U343 U373 1035 MGG6 MGG8 MGG23 LN229

SOX2

OLIG2

SALL2

POU3F2

Lo

g 2

ra

tio

A B C

D


E

F G MGG8 U343 MGG4 LN229 1035

1.0 0.2 1.2 1.0

0.1 1.3 1.0 1.0

pERK

tERK

pAKT

tAKT

Actin

BSA CT BSA CT BSA CT BSA CT BSA CT

1.0 0.8 0.9 1.0 0.7 1.0

1.0 0.5 0.9 1.0 0.7 1.0

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

LC

R L

ow

L

og

fra

cti

on

no

nresp

on

din

g

Dose (no. of cells)

BSA

CT

T98G

p = 0.0005

Lo

g f

ra

cti

on

no

nresp

on

din

g

Dose (no. of cells)

BSA

CT

U87

p = 0.0123

Lo

g f

ra

cti

on

no

nresp

on

din

g

Dose (no. of cells)

BSA

CT

U343

p = 0.122

Lo

g f

ra

cti

on

no

nresp

on

din

g

Dose (no. of cells)

BSA

CT

U373

p = 0.675

Lo

g f

ra

cti

on

no

nresp

on

din

g

Dose (no. of cells)

0 50 100 150 200

0.0

-0

.5

-1.0

-1

.5

-2.0

-2

.5

BSA

CT

0 50 100 150 200

0.0

-0

.5

-1.0

-1

.5

-2.0

-2

.5

-3.0

CA

LC

R H

igh

L

og

fra

cti

on

no

nresp

on

din

g

Dose (no. of cells)

1035

p < 0.0001

BSA

CT

0 50 100 150 200

Lo

g f

ra

cti

on

no

nresp

on

din

g

Dose (no. of cells)

MGG6

p < 0.0001

0.0

-0

.5

-1.0

-1

.5

-2.0

-2

.5

-3.0

BSA

CT

Lo

g f

ra

cti

on

no

nresp

on

din

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

BSA

CT

Lo

g f

ra

cti

on

no

nresp

on

din

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

BSA

CT

LN229

p < 0.0001

Lo

g f

ra

cti

on

no

nresp

on

din

g

Dose (no. of cells)

0 50 100 150 200

0.0

-0

.5

-1.0

-1

.5

-2.0

-2

.5

-3.0

BSA

CT




VC CALCR

R45Q VC

A51T

P100L

V250M

A307V

R404C

R420C

A B


VC

CA

LC

R

R4

5Q

P1

00

L

A5

1T

V2

50

M

R4

04

C

A3

07

V

R4

20

C

% C

olo

nie

s fo

rmed

** ***

-10

0

10

20

30

40

50

60

1 2 3 4 5 6 7 8 9

C

Days 0 5 15 25 10 20 30

Injection of

LN229-luc

cells

Divide into

two groups.

Calcitonin

injection/day

Calcitonin injection/

alternate day

Stop

injection

D

E

BSA CT

Da

y 1

0

Da

y 3

0

Da

y 1

5

Da

y 2

0

Da

y 2

5

0.0

0.5

1.0

1.5

2.0

2.5

10 15 20 25 30

BSA

CT

To

tal

flu

x (

x 1

05) * **

*

Days

F

α β

γ

G-protein

C - ter

N - ter

Extracellular

Cytoplasm

α β

γ

G-protein

C - ter

N - ter

Extracellular

Cytoplasm

WT

CALCR Mutated

CALCR

Reduced proliferation, migration invasion,

anchorage-independent growth

CT

JNK

ERK

AKT

JNK

ERK

AKT

P P

P P

P P

CT

Less aggressive

tumor

Very aggressive

tumor

Better survival Treatment with Salmon calcitonin

x Worse survival x Other treatment option required

Enhanced proliferation, migration

invasion, anchorage-independent growth




Published OnlineFirst December 20, 2017.Clin Cancer Res Jagriti Pal, Vikas Patil, Anupam Kumar, et al. identify highly aggressive glioblastoma with poor outcomeLoss-of-function mutations in Calcitonin receptor (CALCR)

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:

Manuscript

Authoredited. Author manuscripts have been peer reviewed and accepted for publication but have not yet been

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

Subscriptions

Reprints and

[email protected] at

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

Permissions

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

.http://clincancerres.aacrjournals.org/content/early/2017/12/20/1078-0432.CCR-17-1901To 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/cgi/alerts

mailto:[email protected]

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


Documents

Loss-of-function mutations in Calcitonin receptor (CALCR ... · 12/20/2017 · Collection of patient tumor sample and blood . Tumor and matched blood samples from patient were collected