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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.
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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.
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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.
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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
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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
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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).
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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
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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
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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
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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
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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.
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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
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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
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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
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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.
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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.
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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%
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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
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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
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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.
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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
Overall survival (Months)
0 20 40 60 80 0
20
40
60
80
100
High expression (n= 19)
Median survival = 25.13
months
Per
cen
t su
rviv
al
p value = 0.003
GSE7696 J Low expression (n=11)
Median survival = 13.1
months
High expression (n=27)
Median survival = 19.43
months
0 10 20 30 40 50 60 0
20
40
60
80
100
Per
cen
t su
rviv
al
p value = 0.006
Overall survival (Months)
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
Overall survival (Months)
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
Overall survival (Months)
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
Overall survival (Months)
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
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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
Pal et al., 2017, Figure 2
-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
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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
Pal et al., 2017, Figure 3
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
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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)
Pal et al., 2017, Figure 4
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
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-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
CALCR Low CALCR High
Lo
g 2
ra
tio
CALCR Low CALCR High
-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
CALCR Low CALCR High
-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
Pal et al., 2017, Figure 5
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
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VC CALCR
R45Q VC
A51T
P100L
V250M
A307V
R404C
R420C
A B
Pal et al., 2017, Figure 6
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
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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)
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