Development of Glioblastoma from Stem Cells to a Full-Fledged Tumor
Pavel Vladimirovich NIKITIN1, Guzel Railevna MUSINA2, Valery Nikolaevich POLOZOV3, Dmitry Nikolaevich GOREIKO4, Vladimir Mikhailovich KRASNOVSKY5, Leonard WERKENBARK6, Mauric KJELIN7, Piotr Sergeevich TIMASHEV1,8,9
1Institute for Regenerative Medicine, Sechenov First Moscow State Medical University, MOSCOW, RUSSIA
2Federal Center for Brain and Neurotechnologies, MOSCOW, RUSSIA
3A.A. Bogomolets National Medical University, KYIV, UKRAINE
4Kharkiv National Medical University, KHARKIV, UKRAINE
5N.N. Blokhin Cancer Research Center, MOSCOW, RUSSIA
6University of Brussels, BRUSSELS, BELGIUM
7University of Bordeaux, BORDEAUX, FRANCE
8Chemistry Department, Lomonosov Moscow State University, MOSCOW, RUSSIA
9World-Class Research Center “Digital biodesign and personalized healthcare,” Sechenov First Moscow State Medical University, MOSCOW, RUSSIA
Keywords: Glioblastoma, Carcinogenesis, Intratumoral heterogeneity, Glioma stem cells, Tumor evolution
IDH wild-type glioblastomas (GBM) are one of the most malignant and complex tumors for treatment. The urgent question of
new therapeutic and diagnostic tools searching should be resolved based on cellular and molecular pathogenesis mechanisms, which remain
insufficiently studied. In this study, we aimed to investigate GBM pathogenesis.
Material and Method:/b> Using the isolation of different GBM cell populations and the cell cultures, animal models, and molecular genetic methods,
we tried to clarify the picture of GBM pathogenesis by constructing a projection from different glioma stem cells types to an integral neoplasm.
Results: We have shown a potential transformation pathway for both glioma stem cells and four definitive cell populations during gliomagenesis.
Moreover, we have characterized each population, taking into account its place in the pathogenetic continuum, with a description of the most
fundamental molecular and functional properties.
Conclusion: Finally, we have formed a complex holistic concept of the pathogenetic evolution of GBM at the cell-population level by integrating
our results with the data of the world literature.
Glioblastoma, IDH-wild type (GBM), is one of the deadliest
human tumors, and the existing treatment options leave
much to be desired1,2
. The one-year overall survival
of patients with GBM averages 40.2%, while the five-year
overall survival is 5.6%1,2
. So, the existing approaches
are insufficient to achieve good results in the treatment of
GBM and need to be improved3,4
. At the same time,
it is evident that the development of new therapeutic
tools should be based on progress in understanding the
nature of the disease and its pathogenesis3,4
the pathways of GBM development at different stages of
carcinogenesis sheds light on the internal mechanics of
the pathological process, allowing the creation of tools
for a point diagnostic application and targeted treatment3-6
. Such a precision personalized approach with deep
molecular and pathogenetic rationale can significantly
improve the efficiency of medical care for GBM patients.
Previous research showed that neural stem cells are the
probable locus origins of GBM and other diffuse gliomas7,8. It is most likely that they are the original ancestors of the
primary tumor clone, which later gives rise to a full-fledged
tumor node. The nature of normal stem cells’ carcinogenetic
transformation remains a mystery, possible solutions to
which are spontaneous mutations and mistakes during
possible rearrangements of the neuronal stem cells genome
during brain plastic rearrangements9,10. An important
role here is played by the features of the earliest mutational
events, which predetermine the type of the future tumor
through the molecular profile of the early precursors of
glial neoplasm. In the case of IDH1/IDH2 mutations,
further development of the tumor population is directed
towards diffuse astrocytoma, anaplastic astrocytoma, or
oligodendroglial tumors, while EGFR, CDKN2A/B, and
PTEN mutations become early driver events for the GBM11,12.
The principal reflection of the carcinogenesis mechanisms
and their product is heterogeneous tumor cell populations
in their molecular and functional properties. A necessary
type of such population is the very early precursors of glial
neoplasm, which persist at later stages as a component
of an integral large tumor node as glioma stem cells
(GSC)13,14. There are two principal types of GSC
– proneuronal GSC (PGSC), which demonstrate high
expression of neuronal differentiation and neuronal stem
cells genes, as well as mesenchymal GSC (MesGSC), in the
transcriptional profile of which, along with neuronal genes,
mesenchymal differentiation genes predominate13,14.
These types of GSC largely determine the characteristic
features of the neoplasm biological behavior and the degree
of its aggressiveness. In particular, MesGSC provides
tumor insensitivity to therapeutic and radiation treatment13-16. Both GSC variants are the source of the formation
of the initial tumor clone and the source of the current
repopulation of the entire cell array13-16.
There are also definitive cell populations within GBM,
isolated using transcriptional single-cell profiling,
reflecting several features and axial patterns of the
pathogenetic process at its later stages17. Neftel et al.
showed that tumor cells in GBM can be in four primary
definitive cellular states18,19. These states resemble
in their molecular profile different types of cells in the
nervous system. Among them, neural progenitor-like
(NPC-like), oligodendrocyte-progenitor-like (OPC-like),
astrocyte-like (AC-like), and mesenchymal-like (MESlike)
states were found. Moreover, in each of these states,
characteristic molecular features that serve as drivers for
the cell population were identified. For NPC-like, this
feature is CDK4 gene amplification, OPC-like PDGFRA
gene amplification, AC-like EGFR gene amplification,
and MES-like Chr5q deletion or NF1 mutations, each
of which contributes to the development of a particular
cellular state. In addition, it turned out that some of the
cells are in a hybrid state that combines the two molecular
profiles described above. It is also interesting to note that
two cell states or populations – MES-like and NPC-like –
were additionally quite clearly subdivided into two more
subpopulations – MES1 with increased expression of the
DDIT3 gene and MES2 with increased expression of the
ANXA2 gene in the MES-like cell population, as well as
NPC -like 1 with increased expression of the DLL3 gene
and NPC-like 2 with a high level of expression of the
STMN2 gene in the NPC-like cell population17-20.
In the framework of previous studies, we examined the
issues of intratumoral heterogeneity in a slightly different
context, demonstrating the heterogeneity of the distribution of tumor cells’ functional activity depending on the position
of these cells concerning key histopathological landmarks –
tumor vessels and necrosis. The critical functions of tumor
cells taken as the basis for the analysis were proliferative
and antiapoptotic activity. As a result, we identified five cell
clusters with different features and properties18.
Thus, even though some aspects of different stages of the
GBM carcinogenetic pathway have been well studied to
a certain extent, a holistic, fundamental understanding
of the pathogenetic process has not been formed. Within
the framework of this study, we set the task of studying
several features of both early and later stages of GBM
development, projection from different GSC variants
through their functional aspects at different stages of tumor
node formation to a full-fledged neoplasm containing,
in addition to stem cells, all four critical definitive cell
populations. At the same time, to create the complete
picture, an integrated approach is used, combining the
assessment of not only functional but also molecular and
pathohistological properties of tumor cells, including their
location in a particular histological niche or histological
|General Description of the Study
The study included samples of 48 intracerebral tumors
obtained during the neurosurgical intervention in the
Federal Center for Brain and Neurotechnology and the
Burdenko Neurosurgical Institute in 2014 – 2016. The
ethics committee approved this study of the Federal
Center for Brain and Neurotechnology and the Burdenko
Neurosurgical Institute. Patients included in the study
signed informed consent to participate in the study.
According to the histopathological examination results,
all tumors included in the study were verified by three
experienced neuropathologists and to molecular typing as
GBM, IDH-wild type. Inclusion criteria were age over 18
years, primary surgery for this neoplasm, lack of previous
treatment, including chemotherapy and radiation therapy,
and the presence of a single neoplasm at the time of surgery.
If patients did not meet these criteria, we excluded them
from the study.
The average age of the patients was 58.24±4.42 years. The
number of men was slightly higher than the number of
women – 56.73% and 43.27%, respectively. In 44 cases,
the tumor was removed, and in 4 cases, stereotactic biopsy
took place. In 29.17% of cases, the tumor was located in the
temporal lobe, 25% cases in the parietal lobe, 25% cases in
the frontal lobe, and 20.83% cases in the occipital lobe.
All experimental procedures, which included human-derived
objects, fully complied with the principles of the Declaration
of Helsinki and were approved by the local ethics
committee of Sechenov University. All manipulations during
experiments using animal models were complied with
the ARRIVE guidelines and were carried out in accordance
with the U.K. Animals (Scientific Procedures) Act of 1986
and EU Directive 2010/63/EU for animal experiments.
After description and placement of tumor fragments in
histological cassettes, the material was fixed in formalin
(Sigma-Aldrich, USA), and the blocks were guided through
alcohols for dehydration and degreasing, and the blocks
were paraffin impregnated. Then, we cut 3-micrometer
sections from the blocks on a microtome. After that, the
paraffin was removed from the sections in two xylenes, two
minutes each. The slides were washed from xylene in two
absolute alcohols for 1 minute and two 96C° alcohols for
1 minute. Then slides were washed in water and dipped in
hematoxylin to stain the cell nuclei for 5 minutes (Mayer’s
hematoxylin, Sigma-Aldrich, USA). After hematoxylin,
slides were washed with water to remove excess dye. Then
the slides were immersed in 5% eosin (Sigma-Aldrich,
USA) to stain the cell cytoplasm for 30 seconds and again
washed with water to remove excess dye. After that, slides
were dehydrated in two 96C° alcohols for one minute and
clarified in a solution of carbol-xylene. Then the slide was
washed from carbol-xylene in xylene. The section was
placed under a cover glass.
The samples obtained after placing various types of GSC
into cell cultures and their subsequent incubation under
different conditions were also subjected to processing,
fixation in paraffin, and subsequent staining similarly to
the described method.
We used flow cytometry to solve the problem of sorting
different types of tumor stem cells and their separation
from other populations of tumor and non-tumor cells. In
the beginning, GBM tissue obtained from patients in the
form of an 8.0-mm section was dissected and placed in
the digestion buffer in the form of a solution of RPMI and
Accumax at a ratio of 1:1 (Thermo Fisher Scientific, USA).
Tissue in 30% Percoll’s solution diluted in RPMI (Thermo
Fisher Scientific, USA) was wiped through a mesh with a
diameter of 70 μm. Then, all the cells were centrifuged for
15 min at 10°C at a speed of 1500 G to precipitate them.
After that, we suspended the tumor cells in a buffer for
lysis of erythrocytes; then, they were precipitated. Next, the obtained cell mass was washed with PBS and suspended in
a buffer using antibodies for the other labeling process.
Then, endogenous Fc antibody fragments were blocked for
15 min under cooling conditions using CD16 and CD32
neutralizing antibodies at a dilution of 1:100 (Sigma-Aldrich,
USA). The GBM cells obtained at the previous stage were
washed and resuspended in an antibody cocktail containing
antibodies to specific MesGSC markers CD109 (Invitrogen,
Thermo Fisher Scientific, USA), Lyn (Invitrogen, Thermo
Fisher Scientific, USA), and WT1 (Invitrogen, Thermo
Fisher Scientific, USA), as well as PGSC markers CD133
(Invitrogen, Thermo Fisher Scientific, USA), Sox2
(Invitrogen, Thermo Fisher Scientific, USA) and Notch1
(Invitrogen, Thermo Fisher Scientific, USA), which were
incubated with cells for one h on ice before washing and
resuspending in cell staining buffer.
We applied fluorescence-activated cell sorting (FACS) (iCyt
sy3200, Sony Biotechnologies, USA) to isolate MesGSC
and PGSC from all types of cells, and for separate sorting.
Flowjo (v. 10.6.2, USA) was used as the software for analysis.
We based the gating process on the analysis of forwarding
and side scatter plots to isolate the cell from debris and
exclude possible doublets. In addition, this assay allowed
compensation using single antibody controls. Singlechannel,
unstained experimental variants, and fluorescence
minus one were used as controls. MesGSC (CD109+/ Lyn+/
WT1+/CD133-/Sox2-/ Notch1-) and PGSC (CD133+/Sox2+/
Notch1+/ CD109-/ Lyn-/ WT1-) were identified and sorted
into separate tubes.
C57BL/6m mice at the age of 5 – 6 weeks were used to
create different cell cultures. At the first stage, the brain was
removed from the mice, after which we placed the brain in a
tissue culture dish containing sterile PBS solution and placed
it on ice (Figure 1A, B). Within the framework of this study,
two types of organotypic slice brain culture were obtained,
including hemisphere slice culture and subventricular slice
culture at the subsequent stages. To create a hemisphere
slice culture, the mouse forebrain was isolated and placed
in a dish with preheated 3% SeaPlaque agarose (Lonza
Bioscience, Switzerland); the rest of the brain, including
the cerebellum, brain stem, and olfactory bulbs, was
removed. To isolate the subventricular slice culture, the
subventricular zone of the mouse brain tissue was excised,
and then placed in a dish with preheated 3% SeaPlaque
agarose (Lonza Bioscience, Switzerland); we removed the
rest of the brain. The material cooled with ice was cut with a
scalpel into small cubic pieces with a facet size of 2 cm. Then a six-well Millicell Cell Culture Insert plate (Merck, USA)
was used, into the wells of which one cell culture fragment
was injected together with 1 ml of culture medium diluted
in serum-free primary NSC medium, Dulbecco’s modified
Eagle medium (Life Technologies, Thermo Fisher Scientific,
USA). An embedded brain was placed in a Leica VT1200S
vibratome plate (Leica, Germany) fixed on a platform using
a special glue, after which the platform was filled with PBS
with penicillin-streptomycin at a dilution of 1:100 (Thermo
Fisher Scientific, USA). After that, sections with 250 μm
thickness were made with a vibration frequency of 8 and a
speed of 3. Then each section was transferred to the upper
part of the Millipore culture insert. We placed a six-well
plate in an incubator, and then the incubation process took
place at 37°C, 5% CO2, and the sections were incubated for
24 – 48 hours before tumor cell transplantation.
Seeding GSC into Cell Cultures
We applied a Gilson pipette to transplant MesGSC
and PGSC isolated from human GBM tissue with flow
cytometry; using a pipette, 0.2 μL of cells were added to the
center of the incubated cell culture. Before implantation,
centrifuged cells were harvested and resuspended in
solution to a concentration of 100 000 cells/μl. We used
an automatic nanoliter injector (Nanoject II, Drummond
Scientific, USA) to inject 40 nL of GSC. All injections were
performed using tips with a diameter of 10 – 20 μm and an
automatic needle remover (Drummond Scientific, USA).
In a single injection, we injected 200 nL into a socket in a
section of the cell medium made with forceps to facilitate
the engraftment of GSCs in the medium. With a single
injection, 4000 GSC were transplanted. We incubated cell
cultures with GSC under different conditions depending
on the experimental objectives. As part of the simulation
of classical conditions of tumor growth, cell cultures were
incubated at 37°C and 3% O2 for 1 and 8 days; in the case
of simulating hypoxic conditions, we incubated the cell
cultures at 37°C and 1% O2 for one day. Fresh StemPro
NSC SFM medium (Thermo Fisher Scientific, USA) was
added every two days. We monitored the growth of the
planted cells in the cell medium using a Leica M205 C
stereomicroscope (Leica, Germany), and the engraftment
of cells was observed 3 – 4 days after transplantation.
After incubation under different experimental conditions,
tumor nodes grown in cell cultures were excised, sectioned,
Seeding GSC in the Mouse Brain
MesGSC and PGSC isolated from GBM patient’s samples
by flow cytometry were plated in agar-coated flasks (0.85%)
and allowed to self-organize and form organoids for about two weeks at 37°C and 5% CO2 in DMEM medium containing
0.4 mM NEAA, two mM L-glutamine, 10% FBS,
and 100 U/ml Pen-Strep (Lonza Bioscience, Switzerland).
After that, the obtained organоids, which had a diameter
of 400 – 900 μm, were implanted into the brains of nude
mice (NOD/Scid) using a Hamilton syringe (Hamilton,
USA) into the right frontal cortex. The animals were kept
under SPF conditions and sacrificed depending on the experimental
design 6 or 8 weeks after implantation. Tumor
volume was monitored using MRI. Further, according to
the visual macroscopic assessment, we took the material to
include the tumor zone and peritumoral fragments of brain
tissue. After that, we subjected the material to pathohistological
examination with hematoxylin and eosin staining
according to the method described above in all cases and,
depending on the task of the experiment, to confocal microscopy
multiparametric fluorescent in situ hybridization
The GBM samples obtained at the previous stages were
incubated with primary mouse monoclonal antibodies to
CD133 (Thermo Fisher Scientific, USA) at a dilution of
1:100 and primary rabbit monoclonal antibodies to CD109
(Thermo Fisher Scientific, USA) at a dilution of 1:100 for 24
hours at 4°C, followed by secondary antibodies conjugated
with Alexa Fluor 488 dye (Thermo Fisher Scientific,
USA) at a dilution of 1:100 for CD133 and secondary
antibodies conjugated with Alexa Fluor 594 dye (Thermo
Fisher Scientific, USA), at a dilution 1:100 for CD109 for
1 hour at room temperature. After each staining period,
two 15 minutes washes were performed with PBS. To
stain the nuclei, the samples were incubated with DAPI
dye (Thermo Fisher Scientific, USA) at a dilution of 1:10
000 in PBS buffer for 1 hour. At the next stage aiming to
carry out microscopy on glass slides, vaseline strips with
a height of 4 mm were prepared with the further addition
of the mounting medium Fluoromount-G (Thermo Fisher
Scientific, USA), into which we placed the washed samples.
Then a unique glass lid was attached on top; the edges were
sealed with a transparent varnish.
A Leica STELLARIS confocal microscope (Leica, Germany)
was used for laser scanning confocal microscopy. In the
process of image obtaining, in all cases with a standard
layer thickness of 30 μm, shooting was carried out with a
step of 4.5 μm between layers. We used the ImageJ (NIH,
USA) and Imaris (Bitplane, Switzerland) software for the
volumetric rendering of z-stacks in three-dimensional
space21. Further, the threshold values were established for the fluorescent labels’ volume, ellipticity, and signal
quality for better differentiation of individual cells of the
neoplasm. Then, using ImageJ and Imaris, the quantitative
assessment of images was carried out to determine the
percentage of cells with specific marker positive expression
and the analysis of the spatial position of tumor cells,
primarily relative to the vessels’ walls and necrosis22.
The prepared tumor sections, placed on glass slides and
frozen at –80°C, were quickly transferred into a precooled
4% paraformaldehyde solution (Sigma-Aldrich,
USA). Further, we incubated all samples for 15 minutes
at 4°C. After that, slides were washed in 1xPBS solution at
room temperature five times for 2 min. Then slides were
dehydrated in 50% ethanol, 70% ethanol for 5 minutes, and
twice in fresh 100% ethanol at room temperature. After
excess liquid removal, the slides were dried in the air on
a flat surface for 5 minutes at room temperature. Then
slides were wholly immersed in a solution for pretreatment
with protease IV (Advanced Cell Diagnostics, Bio-Techne,
USA) and incubated for 30 minutes at room temperature.
RNA probes complementary to the DDIT3, ANXA2,
EGFR, PDGFRA, DLL3, and STMN2 messenger RNAs
were used (Advanced Cell Diagnostics Bio-Techne, USA).
DDIT3 was marked blue, ANXA2 was green, EGFR was
yellow, PDGFRA was orange, DLL3 was red, and STMN2
was dark red. To prepare the probes, we preheated them
for 10 min at 40°C in a water bath. A mixture of RNA
probes was prepared in tubes without RNase content. The
concentration of each probe in the solution was 1:50. Then
the slides were transferred from the pretreatment solution
to the 1xPBS solution at room temperature, washing them
and incubating them twice for 2 minutes. After that, we
transferred slides to a horizontal slide rack in a preheated
humidifying chamber, and 50 μL of the probe mixture was
pipetted onto each slide.
Next, probe hybridization was carried out for 2 hours at 40°C
in a sealed humidified chamber. After that, we removed the
hybridization solution excess from each slide and treated
it with 1x wash buffer at room temperature for 2 minutes
twice. Excess 1x wash buffer was then removed from
each slide, and the slides were transferred to a humidified
chamber. All slides were covered with amplification
solution AMP1 (Advanced Cell Diagnostics, Bio-Techne,
USA) and incubated in a humidified chamber for 30
minutes at 40°C. Afterwards, all slides were washed twice
in 1x wash buffer at room temperature. The amplification
solution AMP2 (Advanced Cell Diagnostics, Bio-Techne,
USA) was then added and incubated for 15 minutes at 40°C, followed by washing all slides twice in 1x wash buffer
at room temperature. At the next stage, amplification
solution AMP3 (Advanced Cell Diagnostics, Bio-Techne,
USA) was added and incubated for 30 minutes at 40°C,
followed by washing the slides twice in 1x wash buffer at
room temperature. Finally, Amplification solution AMP4
(Advanced Cell Diagnostics, Bio-Techne, USA) was added
and incubated for 15 minutes at 40°C. Then the slides were
washed twice in 1x wash buffer at room temperature. This
was followed by staining of cell nuclei with the addition
of 2 drops of DAPI (Thermo Fisher Scientific, USA) and
incubation for 30 seconds at room temperature. At the
next stage, we added 10 μL of Mowiol DABCO aqueous
mounting medium (Thermo Fisher Scientific, USA) to each
slide, and a coverslip was placed on each slide. Next, the
slides were placed in a dark room for 12 hours at 4°C to dry
All slides were then subjected to confocal microscopy,
followed by quantitative assessment of signals from all
studied messenger RNAs using ImageJ and Imaris software.
The SPSS Statistics 26.0 software (IBM, USA) was used
to carry out a statistical analysis of the obtained results.
We carried out intergroup comparisons using the Mann-
Whitney U-test in the case of abnormal distribution
of the trait, and Student’s t-test in the case of a normal
distribution of the trait. The character of the distribution
of the feature was determined using the Shapiro-Wilk test.
The influence of the studied factors on patient survival was
determined using the Cox proportional hazards model. For
greater clarity of the dependence of the overall survival on
the tumor cell-population composition, the Kaplan-Meier
curves were plotted. For this, we divided all the cases into
two groups – with a high and a low level of quantitative
parameters under consideration. The average value of the
corresponding parameter was determined, and each case
was then ranked into one of the groups – into the high
group, if the parameter, in this case, is higher than the
average, and into the low group if the parameter, in this
case, is below the average. Differences were considered
significant at p<0.05.
|Early Stages of Pathogenesis
By sorting cells using flow cytometry, we isolated MesGSC
and PGSC from tumor samples of 48 patients with an
established diagnosis of GBM, IDH-wild type, after which
we separately placed MesGSC and PGSC in organotypic
adult brain hemisphere slice culture. After incubation in these cultures for 8 hours, it was shown that the number of
tumor cells was, on average, higher in cultures with MesGSC
overseeding than in cultures with initial PGSC overseeding
), and the difference was statistically significant
(p=0.034). Next, we evaluated how the qualitative
composition of GSC in these cultures changed after 8
hours of incubation using an immunofluorescence study. It
turned out that if in the culture with MesGSC inoculation,
there is an exclusive presence of MesGSC (n = 42), or their
significant predominance (n=6) in the overwhelming
majority of cases after 24 hours. In the culture with PGSC
inoculation, the cell composition is mixed; however, on
average, the prevalence of PGSC is revealed (Figure 1C,D
Click Here to Zoom
|Figure 1: A,B) Show the results of immunofluorescent staining to identify markers of mesenchymal glioma stem cells CD109 (red
marks) and proneuronal glioma stem cells CD133 (green marks) visualized by confocal microscopy in the organotypic adult brain
hemisphere slice culture with mesenchymal and proneuronal patient glioma stem cells inoculation respectively. C,D) illustrate the
average percentage of mesenchymal and proneuronal glioma stem cells after 8 hours of incubation of organotypic brain slice culture with
mesenchymal and proneuronal glioma stem cells, respectively. From now on, the mean values of the indicators on the graphs correspond
to the circle’s white center, and the circle’s diameter corresponds to the indicator’s ±σ. The results of immunofluorescent staining for the
detection of markers of mesenchymal glioma stem cells CD109 (red marks) and proneuronal glioma stem cells CD133 (green marks)
with confocal microscopy visualization in the organotypic rat subventricular slice culture after mesenchymal (E) and proneuronal (F)
glioma stem cells inoculation and 24 hours incubation are shown in Figures E,F respectively. For cases with mesenchymal (G) and
proneuronal (H) glioma stem cells inoculation, the results of the content percentage counting for each glioma stem cell type are shown
in Figures G,H, respectively. I,J) show the results of the percentage calculation of mesenchymal and proneuronal glioma stem cells after
incubation of tumor cell cultures under conditions of relative normoxia (I) and hypoxia (J).
In order to further study the early stages of gliomas development,
we placed the MesGSC and PGSC isolated from all
48 patients separately in the organotypic rat subventricular
slice culture to create the most realistic model of the potential
possible tissue environment for the early stages of GBM
development. In this case, we also obtained interesting results,
repeating those previously stated in the paragraph
above. After incubation for 24 hours, the number of tumor
cells in cultures with initial MesGSC inoculation exceeded
that in cultures with PGSC inoculation with statistical significance
(p=0.025). When typing tumor cells in cultures
with MesGSC inoculation, the predominance of MesGSC
was also observed, but already slightly less significant,
since MesGSC was observed exclusively only in 34 cases;
in the rest, this type of cell only prevailed. A predominance
of MesGSC on average was also observed in cultures with
PGSC overseeding, but it was not as significant as in the
case of MesGSC inoculation (Figure E-H).
We assumed that the observed results might be due to
the characteristics of the environment and the content of
oxygen and nutrients in it. In this regard, we re-seeded
PGSCs (n=48) in the organotypic adult brain hemisphere
slice cultures and placed them in an incubator at different
O2 levels (23). We showed that under normal conditions
when the O2 level is 3%, which corresponds to the oxygen
content in the peritumoral brain tissue according to studies,
there is a significant predominance of PGSC with only a
tiny amount of MesGSC after 24 h incubation (Figure 1I).
At the same time, incubation of similar cell cultures at an O2
level of 1% showed a significant predominance of MesGSC
in all cases (Figure 1J). The differences were statistically
significant (p<0.001 and p<0.001).
Thus, at the early stages of gliomagenesis, the predominance
of MesGSC is most likely, which can be explained by a
high degree of competition for nutrients and oxygen,
and, consequently, their relatively low availability at this
stage of neoplasm development. In this regard, switching to the mesenchymal phenotype of stem cells seems to be
an adaptive response that allows glioma-initiating cells to
survive at an early stage of pathogenesis. At the same time,
it is possible that the initially emerging tumor clone can
be represented as PGSCs, which then switch to MesGSC in
a competitive environment, and initially this clone can be
represented by MesGSC.
GSC in the Formation of a Tumor Node in Slice Culture
Next, we seeded MesGSC from all 48 patients on organotypic
adult brain hemisphere slice cultures to study the further
nature of changes in different types of GSC. After eight days
of incubation, we found the formation of macroscopically
detectable tumor nodes in the overwhelming majority of
cases (n = 44). We carried out a histological examination of
all slice cultures. We found typical histological gliomas in
42 cases with the presence of highly malignant tumor cells
forming different histological structures and the essential
histological criteria of GBM in the form of necrosis (Figure
2A) and proliferation of the vascular endothelium (Figure
Click Here to Zoom
|Figure 2: A,B) Show the pathohistological picture of glioblastoma grown after mesenchymal glioma stem cells inoculation in the
organotypic adult brain hemisphere slice culture and incubation for eight days. Crucial pathohistological characteristics - necrosis (A)
and proliferation of the vascular endothelium (B) - are presented. Figures C,D show the results of immunofluorescent staining to identify
markers of mesenchymal glioma stem cells CD109 (red marks) and proneuronal glioma stem cells CD133 (green marks) with confocal
microscopy visualization in the area of necrosis (C) and tumor vessels (D). Figures E,F show the average percentage of mesenchymal and
proneuronal glioma stem cells in the perinecrotic (E) and perivascular (F) zones.
Then we studied the qualitative and quantitative distribution
of MesGSC and PGSC in different zones in GBM tissue
obtained from slice culture. Using immunofluorescence
and confocal microscopy, we identified the characteristic
patterns of distribution of these cells’ types; in particular,
we found that most often, PGSCs are found in the area
immediately around the vessels (Figure 2C), with MesGSC
in the area close to necrosis (Figure 2D).
In order to quantitatively calculate and confirm this regularity,
we conditionally identified several pathohistological
zones in the tumor tissue. We identified the perivascular
zone (PVZ); to conventionally outline its boundaries, we
empirically determined them at a distance of five cells from
the vascular wall in all directions (Figure 2C). Around this
zone, we empirically identified a transient vascular zone
(TVZ) for ten more cells. We have drawn similar conditional
zones around necrosis. Directly around the necrotic
detritus, we identified a perinecrotic zone (PNZ) extending
from the necrotic zone by ten cells in each direction (Figure
2D). Further, for another 20 cells, we outlined a transient
necrotic zone (TNZ). The rest of the tumor areas outside
the above zones were conditionally included in the intermediate
Quantitatively, we have shown that the content of MesGSC
has the highest precision in the TNZ, in which the content
of PGSC practically tends to zero (Figure 2E). At the same
time, the most significant number of PGSCs is concentrated
in the PVZ, within which MesGSCs practically do not occur
(Figure 2F). The differences in the content of the considered cell types in both TNZ and PVZ were statistically significant
(p<0.001 for both cases).
Distribution of GSC Types in the Nude Mice Model
Next, we decided to confirm our findings using the nude
mice model. For this purpose, we randomly selected 38
MesGSC samples from different patients and transplanted
them into the brains of MesGSC nude mice. After six weeks
of incubation, we performed an MRI scan on all mice to
confirm sufficient tumor growth (Figure 3A). All animals
survived to 6 weeks, and then samples of the grown tumors
were taken from them. We initially subjected all tumor
samples to histopathological examination. As a result,
we identified a typical pathological picture of GBM with
characteristic features (Figure 3B).
Click Here to Zoom
|Figure 3: A) Shows magnetic resonance imaging of a nude mouse brain in T2 mode six weeks after implantation of mesenchymal
glioma stem cells culture. The corresponding histopathological picture is shown in (B); it clearly shows the classic signs of glioblastoma,
in particular the zone of necrosis (marked with the letter “n”) and the zone of the vascular endothelium proliferation (marked with
the letter “v”). (C,D) show the typical distribution of mesenchymal and proneuronal glioma stem cells in the perivascular zone (PVZ)
and transient vascular zone (TVZ) (C), as well as the perinecrotic zone (PNZ) and transient necrotic zone (TNZ) (D). In this case, we
performed immunofluorescent staining with visualization by confocal microscopy to identify markers of mesenchymal glioma stem cells
CD109 (red marks) and proneuronal glioma stem cells CD133 (green marks). (E,F) show the mean percentages of mesenchymal and
proneuronal glioma stem cells in TNZ (E) and PVZ (F). (G) shows the average percentage of different glioma stem cells in organotypic
slice culture after mesenchymal glioma stem cells inoculation and incubation under normoxic conditions. (H) shows the average
percentage of different glioma stem cells in organotypic slice culture after implantation of proneuronal glioma stem cells and incubation
under hypoxic conditions.
To identify MesGSC and PGSC markers, we carried out
an immunofluorescent study with confocal microscopy
and revealed a similar picture with slice culture. It has
been shown that in the PVZ, PGSCs are dominant (Figure
3C). In addition, the prevalence of MesGSC in the TNZ
was revealed, also mainly found in this zone (Figure 3D).
A quantitative calculation confirmed these suggestions.
MesGSC made up a significant proportion of cells in the
TNZ, with an almost complete absence of PGSCs markers
in this zone (Figure 3E). At the same time, PGSCs were
quantifiable in the PVZ with a negligible amount of
MesGSCs in the zone (Figure 3F). These differences in
TNZ and PVZ were statistically significant in both cases
considered (p<0.001 for both cases).
Then we decided to study the features of changes in different
types of stem cells in GBM. For this, we carried out sorting
of MesGSC and PGSC from tumors previously excised in
mice using flow cytofluorometry. We seeded these stem cells
types separately from all 38 animals on primary organotypic
slice cultures and incubated them for 24 hours under
different O2 conditions. Considering the previous results,
we decided to incubate primary organotypic slice cultures
with MesGSC cells in an environment with an increased
O2 content of up to 3%, but PGSC, on the contrary, under
a sharply reduced condition O2 content to 1%. As a result,
we found that in the culture with the initial over-seeding of
MesGSC, kept under normal oxygen partial pressure, there
was a significant predominance of PGSC (Figure 3G). At
the same time, a pronounced predominance of MesGSC
was revealed in the culture with PGSC overseeding at the
beginning, which was in hypoxic conditions (Figure 3H).
Moreover, the differences revealed in both cases were
statistically significant (p=0.007 and p=0.005).
Thus, we have demonstrated the presence of histopathological
zones typical for different types of stem cells and showed the pathogenetic mechanisms of the formation of
these stem pools. Their appearance is directly related to
the availability of nutrients and oxygen and the dependent
switching of stem phenotypes. When unfavorable hypoxic
conditions are formed, a switch to MesGSC occurs, while
good oxygen and nutrient conditions contribute to the
transition to the PGSC stem subtype.
Different Cell Populations
To assess the distribution of different populations of
tumor cells in tissue niches of GBM, 38 MesGSC samples
from different patients were again randomly selected and
implanted into the brains of nude mice. Then we incubated
the tumor for eight weeks and performed MRI for all mice
to confirm sufficient tumor growth (Figure 4A). Thirty-six
animals survived eight weeks; after the indicated incubation
period, samples of ingrown neoplasms were taken from
all surviving mice. At first, all samples underwent a
pathohistological examination, which showed a typical
pathohistological picture of GBM in all cases (Figure 4B),
and the samples were advanced to the next stage of work.
Click Here to Zoom
|Figure 4: A) shows magnetic resonance imaging of the nude mouse brain in T2 mode eight weeks after mesenchymal glioma stem cells
culture implantation. A typical histological pattern is shown in (B), with critical features of glioblastoma, including a zone of necrosis
(marked with the letter “n”) and a zone of vascular endothelium proliferation (marked with the letter “v”). C,D show a typical pattern
of the distribution of primary cell populations in the perinecrotic zone (PNZ) and transient necrotic zone (TNZ) (C), as well as in the
perivascular zone (PVZ) and transient vascular zone (TVZ) (D). Using multimeric fluorescent in situ hybridization, increased expression
of DDIT3 messenger RNA to determine the MES1 cell population (blue label), increased expression of ANXA2 messenger RNA to
determine the MES2 cell population (green label), increased expression of EGFR messenger RNA to determine the AC-like cell population
(yellow label), increased expression of PDGFRA messenger RNA for OPC-like cell population determination (orange label), increased
expression of DLL3 messenger RNA for determination of NPC-like 1 cell population (red label), and increased expression of STMN2
messenger RNA to determine the NPC-like 2 cell population (dark red label) using confocal microscopy. The corresponding colors have
coded the percentage of these cell populations in TNZ (E), PNZ (F), PVZ (G), and TVZ (H). (I,J) show the visualization of the primary
marker messenger RNAs for identifying cell populations using multimeric fluorescent in situ hybridization and confocal microscopy in
the intermediate zone (I), as well as the average percentage of cell populations in this zone, including hybrid cell populations with the
expression of several marker messenger RNAs (J).
Further, for all 36 samples, multiparametric FISH was
performed using probes to the messenger RNA DDIT3
to identify the MES1 cell population, ANXA2 to isolate
the MES2 cell population, EGFR to determine the AClike
cell population, PDGFRA to detect the OPC-like cell
population, DLL3 to detect NPC-like 1 cell population, and
STMN2 to identify NPC-like 2 cell population. We found
that the MES1 cell population is most common in the TNZ,
with this population being predominant in the indicated
pathological niche (Figure 4C-E). In PNZ, representatives
of the MES2 cell population are most often detected; the
bulk of this type of cell is concentrated in PNZ (Figure
Cells from the OPC-like cell population were characterized by
preferential localization in the PVZ of the pathohistological
niche, in which they were the most frequent cell population
(Figure 4C, D, G). Nevertheless, we detected representatives
of the NPC-like 1 cell population with a high frequency in
this zone (Figure 4C, D, G). This type of cell predominates
in the neighboring TVZ, where NPC-like 2 cells were also
found in slightly smaller numbers, for which this zone
is the main one (Figure 4C, D, H). Finally, in the IZ, a
rather heterogeneous picture was observed representing
different cell populations, and primarily the AC-like cells
predominated (Figure 4C, D, I). However, there were also
significant numbers of representatives of the MES1 cell
population, in addition to mixed transitional cell variants
in the form of AC-like+MES1 and OPC-like+AC-like cell
populations (Figure 4C, D, J).
Influence of Cell Populations on Survival
Finally, we decided to evaluate the clinical significance of the
revealed patterns of different cell populations’ distribution
in the tissue niches of GBM. Using regression analysis,
we evaluated the effect of the different cell population
percentages, including MesGSC, PGSC, MES1, MES2, AClike,
OPC-like, NPC-like 1, and NPC-like 2, on the overall
population survival. The content of each cell population
was assessed separately in those pathohistological zones where they predominated. It was shown that the content
of MesGSC in TNZ (p<0.001), PGSC in PVZ (p<0.001),
OPC-like in PVZ (p<0.001), NPC-like 1 in TVZ (p<0.001),
and MES1 in TNZ (p=0.005) significantly impact the
overall survival (Figure 5A-E,G). In the multiparameter
model, we demonstrated the highest predictive value by the
combination of MesGSC content in TNZ, PGSC content
in PVZ, and NPC-like 1 in TVZ (p<0.001); the predictive
value of this model was the highest among all possible
variants (Figure 5F,G).
Click Here to Zoom
|Figure 5: Kaplan-Meier curves of overall survival of patients with high and
low levels of mesenchymal glial stem cells in the transient necrotic zone
(A), proneuronal glial stem cells in the perivascular zone (B), OPC-like
cell population in the perivascular zone (C), NPC-like 1 cell population in
the transient vascular zone (D), and MES1 cell population in the transient
necrotic zone (E). In addition, using multimeric regression analysis, it
was possible to determine the most prognostically valuable complex of
cell-population parameters in the form of a combination of mesenchymal
glioma stem cells content in TNZ, proneuronal glioma stem cells content
in PVZ, and NPC-like 1 cell population content in TVZ, for which the
Kaplan-Meier curves are shown in (F). In addition, all the resulting curves
were summarized in (G).
In this study, we traced the development of GBM from
patient-derived glioma stem cells to a full-fledged tumor
with typical pathohistological and molecular properties.
What is the path that GBM takes until the appearance of
clinical manifestations and diagnosis? According to our
and published data, MesGSC can act as the initial link in the
pathogenetic process. At the initial stage, the development
of a tumor occurs in conditions of fierce competition for
the necessary plastic and energy substrates between early
clones of tumor cells and brain cells. In this regard, the pool
of tumor cells is mainly represented by MesGSCs, which are
the most resistant to unfavorable metabolic conditions (24,
25). Further, MesGSCs gradually spread in the brain tissue
from the site of their initial localization, infiltrating the
surrounding brain due to the high degree of mobility and
the ability to lyse the extracellular matrix, which prevents
their free movement (14, 15). In addition, MesGSCs can
produce angiogenesis factors, stimulating the germination
of new blood vessels and, thus, improving their nutrition
and making metabolic conditions more favorable for
further development (25-28).
The appearance of favorable metabolic shifts leads to shifts
in the molecular and functional state, within which MesGSC
switches to a different stem profile and becomes PGSC. In
conditions of sufficient oxygen and nutrient levels, PGSCs,
using, among other things, aerobic glycolysis as the most
effective mechanism of catabolism, actively proliferate,
giving rise to new cell populations. At the same time, based
on the features outlined above, it is not surprising that most
cells of this type are localized around the vessels (29, 30).
The perivascular pool, according to the literature, is not
only an ideal metabolic niche that maintains a sufficiently
high content of nutrients but is also in a kind of paracrine
stimulation connection with the vascular endothelium,
which produces factors stimulating stem cell proliferation
(for example, NO).
Gradually, with an increase in the number and density
of cells in this zone, due to the intensive proliferation of
PGSCs, cells supply in the perivascular histological niche
deteriorates. On the one hand, this tendency is due to an
increased need for nutrients and oxygen because of cell
quantity increase. On the other hand, we can also explain it
by the peculiarities of tumor vessels in the neoplasm tissue.
Newly formed vessels in GBM are defective due to many
factors, and, providing up to a specific limit the increasing
need of tumor cells for blood supply, reaching the limit of
their functional capabilities. They quickly begin to undergo
various pathological changes; in particular, there is an increase in endothelial thrombogenicity and the appearance
of blood clots in the vessels, which severely disrupt blood
flow (31, 32). The combination of the considered factors
causes a pronounced decrease in the supply of cells with
oxygen and nutrients in this zone, a deterioration in
the cells’ existence conditions, and acidification of the
environment. The latter is an important signal recognized
by cells due to the expression of aberrant ion channels
ASIC1a and ASIC3 (33, 34).
Cells under the most unfavorable metabolic conditions and
having the least resistance to hypoxia die and form a zone
of necrosis. Cells with a higher resistance, primarily PGSCs,
actively begin to move from an unfavorable metabolic zone.
At the moment, probably under the influence of negatively
changed conditions, the molecular profile of these cells is
shifted again, and they are modified into MesGSCs, which
can survive better under hypoxic conditions (35, 36). An
essential role in such a switch can be played by aberrant
ion channels, which are likely to act not only as a sensor
that increases cell motility but also as a participant in
more global molecular shifts up to the transition to a
mesenchymal state. MesGSCs then repeat the pathogenetic
circle described above, again migrating to more favorable
metabolic niches and promoting their creation, producing
angiogenesis factors, and then again switching back to the
PGSC molecular profile.
The most crucial property of tumor stem cells of both
subtypes is their ability to proliferate actively. At the same
time, the descendants of these subtypes have a gradually
decreasing proliferative potential up to the non-proliferating
cell pool, but molecular plasticity is preserved to a certain
extent (37, 38). This is reflected in the differentiation of
the descendants of glioma stem cells into non-stem cells
in the four central populations. As mentioned above, one
of the most important is MES-like cells, which have a
mesenchymal molecular profile and two main subtypes of
MES1 and MES2. Cells of both subtypes are, apparently,
descendants of MesGSC, while, judging by the data of
molecular studies, the differentiation of subtypes occurs
under the influence of such a functional factor as hypoxia.
The MES1 subtype is hypoxia-independent, while the MES2
subtype shows pronounced signs of a response to hypoxia.
Taking into account our data on the localization of cells
of both subtypes, it is likely that MesGSCs produce finitely
differentiated mesenchymal clones of cells constituting
the MES1 subtype during migration already in the zone of
relatively favorable metabolic conditions; perhaps, part of
the MES1 cells migrate to this zone together with MesGSC. In
this zone, which we named TNZ, the metabolic parameters are more favorable in comparison with the tissue site
immediately around the necrosis, which we named PNZ;
within the TNZ, the effect of hypoxia is not so acute, which
is reflected in the molecular properties of MES1 subtype
cells and is confirmed by their predominance in this zone.
At the same time, some of the MesGSC offspring remain in
unfavorable metabolic conditions that have developed in
PNZ; their molecular profile demonstrates a pronounced
hypoxic component. They form the MES2 subtype, which,
according to our data, prevails in the PNZ.
PGSC proliferating under favorable metabolic conditions
give rise to NPC-like and OPC-like cell populations. Due to
favorable conditions of existence, these cell populations are
distinguished by extremely high proliferative activity. The
highest proliferation activity is observed precisely in the
OPC-like population. At the same time, NPC-like is divided
into two subtypes as NPC-like 1 and NPC-like 2. NPC-like
1 is in many ways a transitional subtype between NPC-like
and OPC-like cell populations, containing in its molecular
profile the features of both populations. At the same time,
the proliferative activity of this subtype is exceptionally
high and is inferior to that only in the OPC-like population.
NPC-like 2 has a greater degree of neuronal differentiation
and, although high in general still lower than OPC-like and
NPC-like 1 cell proliferation activity (18). The considered
data, along with our results, demonstrate that, apparently,
the PGSC offspring in the zone of the most favorable
metabolic parameters, which develops directly around the
vessels and is called PVZ by us, mainly differentiate into an
OPC-like cell population.
Nevertheless, in the same PVZ, there is a noticeable
proportion of NPC-like 1 cells, which, despite neuronal
differentiation, also actively compete for nutrients and
oxygen with the OPC-like population, partially acquiring
the features of this population. Cells of NPC-like subtype
2 are content with somewhat less favorable conditions in
the neighboring TVZ, allowing them to proliferate actively,
but to a somewhat lesser extent than cells in PVZ. This
pattern is well confirmed by our data, demonstrating the
predominance of OPC-like cells in PVZ and the presence
of a significant proportion of NPC-like 1, while in TVZ the
predominant type was just NPC-like 1.
At the same time, cells in two metabolically favorable tissue
zones continue to maintain a certain level of molecular
and cellular plasticity. A part of NPC-like cells strives to
penetrate from TVZ into PVZ to improve their living
conditions. Hence, a mixed cell population is observed,
which simultaneously contains OPC-like and NPC-like
cell populations. Cell plasticity also manifests itself in the
appearance of transitional cell variants, differentiating
in the astrocytic direction and forming an AC-like cell
population. In this population, cells are present, and can
originate from many sources, primarily from MesGSC
and PGSC, and probably at the moment when they are
close or directly in a state of transition into each other.
As a result, tumor cells with molecular signs of astrocytic
differentiation are formed, possessing a moderate
proliferative activity and, accordingly, located in a zone
equidistant from both necrosis and vessels, which we
called IZ. It is curious that these cells also retain molecular
functional plasticity and various transformations (34). In
particular, the increase in the hypoxia zone leads to the
mesenchymal molecular program expression in some of
the cells of this population and the appearance of hybrid
variants between AC-like and MES-like cell populations.
Such hybrids can also be associated with the transition
from the neighboring zone to more favorable conditions
of some of the MES1 subtype cells. At the same time, part
of the OPC cells of the cell population, for many reasons,
is displaced into less favorable conditions and acquires
the features of hybrid differentiation with astrocyte-like
molecular traits. In addition, it should be noted that the
processes of a phenotypic shift towards the AC-like cell
population are widespread not only in IZ but also in TNZ
and PVZ, although to a lesser extent.
Thus, in the framework of this study, we tried to model
and describe in general terms the carcinogenesis and
progression of GBM. Our work emphasizes the importance
of the issues of intratumoral heterogeneity since they are the
key to understanding the fundamental principles of tumor
development. A detailed description of these patterns can
become the basis for creating new practical approaches
to diagnosing and treating GBM. Our work creates a
conceptual basis for further study of the characteristics of
cellular and molecular processes of carcinogenesis.
Conflict of Interest
The authors declare no conflict of interest.
World-Class Research Center “Digital biodesign and personalized
healthcare,” Sechenov First Moscow State Medical University,
This work was financed by the Ministry of Science and Higher
Education of the Russian Federation within the framework of state
support for the creation and development of World-Class Research
Centers “Digital biodesign and personalized healthcare” №075-15-
Availability of Data and Materials
The datasets used and/or analyzed during the current study are
available from the corresponding author on reasonable request.
Concept: NPV, MGR, PVN, GDN, Design: NPV, MGR, PVN,
KVM, Data collection or processing: NPV, MGR, PVN, KVM, WL,
KM, Analysis or Interpretation: NPV, MGR, KVM, TPS, Literature
search: NPV, MGR, VM, WL, KM, Writing: NPV, MGR, GDN,
KVM, Approval: NPV, MGR, KVM, TPS.
1) Ostrom QT, Patil N, Cioffi G, Waite K, Kruchko C, Barnholtz-
Sloan JS. CBTRUS Statistical report: Primary brain and other
central nervous system tumors diagnosed in the United States in
2013-2017. Neuro Oncol. 2020;22:iv1-iv96.
2) Ostrom QT, Cioffi G, Gittleman H, Patil N, Waite K, Kruchko
C, Barnholtz-Sloan JS. CBTRUS Statistical Report: Primary brain
and other central nervous system tumors diagnosed in the United
States in 2012-2016. Neuro Oncol. 2019;21:v1-v100.
3) Shergalis A, Bankhead A 3rd, Luesakul U, Muangsin N, Neamati
N. Current challenges and opportunities in treating glioblastoma.
Pharmacol Rev. 2018;70:412-45.
4) Thorne AH, Zanca C, Furnari F. Epidermal growth factor
receptor targeting and challenges in glioblastoma. Neuro Oncol.
5) Nadeem Abbas M, Kausar S, Wang F, Zhao Y, Cui H. Advances
in targeting the epidermal growth factor receptor pathway by
synthetic products and its regulation by epigenetic modulators as
a therapy for glioblastoma. Cells. 2019;8:350.
6) Eskilsson E, Røsland GV, Solecki G, Wang Q, Harter PN, Graziani
G, Verhaak RGW, Winkler F, Bjerkvig R, Miletic H. EGFR
heterogeneity and implications for therapeutic intervention in
glioblastoma. Neuro Oncol. 2018;20:743-52.
7) Bonnay F, Veloso A, Steinmann V, Köcher T, Abdusselamoglu
MD, Bajaj S, Rivelles E, Landskron L, Esterbauer H, Zinzen RP,
Knoblich JA. Oxidative metabolism drives immortalization of
neural stem cells during tumorigenesis. Cell. 2020;182:1490-507.
8) Mao XG, Hütt-Cabezas M, Orr BA, Weingart M, Taylor I, Rajan
AK, Odia Y, Kahlert U, Maciaczyk J, Nikkhah G, Eberhart CG,
Raabe EH. LIN28A facilitates the transformation of human neural
stem cells and promotes glioblastoma tumorigenesis through a
pro-invasive genetic program. Oncotarget. 2013;4:1050-64.
9) Fischer U, Backes C, Raslan A, Keller A, Meier C, Meese E. Gene
amplification during differentiation of mammalian neural stem
cells in vitro and in vivo. Oncotarget. 2015;6:7023-39.
10) Ladran I, Tran N, Topol A, Brennand KJ. Neural stem and
progenitor cells in health and disease. Wiley Interdiscip Rev Syst
Biol Med. 2013;5:701-15.
11) Barthel FP, Johnson KC, Varn FS, Moskalik AD, Tanner G,
Kocakavuk E, Anderson KJ, Abiola O, Aldape K, Alfaro KD, Alpar
D, Amin SB, Ashley DM, Bandopadhayay P, Barnholtz-Sloan
JS, Beroukhim R, Bock C, Brastianos PK, Brat DJ, Brodbelt AR,
Bruns AF, Bulsara KR, Chakrabarty A, Chakravarti A, Chuang
JH, Claus EB, Cochran EJ, Connelly J, Costello JF, Finocchiaro
G, Fletcher MN, French PJ, Gan HK, Gilbert MR, Gould PV,
Grimmer MR, Iavarone A, Ismail A, Jenkinson MD, Khasraw
M, Kim H, Kouwenhoven MCM, LaViolette PS, Li M, Lichter
P, Ligon KL, Lowman AK, Malta TM, Mazor T, McDonald KL,
Molinaro AM, Nam DH, Nayyar N, Ng HK, Ngan CY, Niclou SP,
Niers JM, Noushmehr H, Noorbakhsh J, Ormond DR, Park CK,
Poisson LM, Rabadan R, Radlwimmer B, Rao G, Reifenberger
G, Sa JK, Schuster M, Shaw BL, Short SC, Smitt PAS, Sloan AE,
Smits M, Suzuki H, Tabatabai G, Van Meir EG, Watts C, Weller
M, Wesseling P, Westerman BA, Widhalm G, Woehrer A, Yung
WKA, Zadeh G, Huse JT, De Groot JF, Stead LF, Verhaak RGW;
GLASS Consortium. Longitudinal molecular trajectories of
diffuse glioma in adults. Nature. 2019;576:112-20.
12) Körber V, Yang J, Barah P, Wu Y, Stichel D, Gu Z, Fletcher
MNC, Jones D, Hentschel B, Lamszus K, Tonn JC, Schackert
G, Sabel M, Felsberg J, Zacher A, Kaulich K, Hübschmann D,
Herold-Mende C, von Deimling A, Weller M, Radlwimmer B,
Schlesner M, Reifenberger G, Höfer T, Lichter P. Evolutionary
trajectories of IDHWT glioblastomas reveal a common path of
early tumorigenesis instigated years ahead of initial diagnosis.
Cancer Cell. 2019;35:692-704.e12.
13) Zhou D, Alver BM, Li S, Hlady RA, Thompson JJ, Schroeder
MA, Lee JH, Qiu J, Schwartz PH, Sarkaria JN, Robertson KD.
Distinctive epigenomes characterize glioma stem cells and their
response to differentiation cues. Genome Biol. 2018;19:43.
14) Chandran UR, Luthra S, Santana-Santos L, Mao P, Kim SH,
Minata M, Li J, Benos PV, DeWang M, Hu B, Cheng SY, Nakano
I, Sobol RW. Gene expression profiling distinguishes proneural
glioma stem cells from mesenchymal glioma stem cells. Genom
15) Ma Q, Long W, Xing C, Chu J, Luo M, Wang HY, Liu Q, Wang RF.
Cancer stem cells and immunosuppressive microenvironment in
glioma. Front Immunol. 2018;9:2924.
16) Shi Y, Guryanova OA, Zhou W, Liu C, Huang Z, Fang X, Wang
X, Chen C, Wu Q, He Z, Wang W, Zhang W, Jiang T, Liu Q,
Chen Y, Wang W, Wu J, Kim L, Gimple RC, Feng H, Kung HF,
Yu JS, Rich JN, Ping YF, Bian XW, Bao S. Ibrutinib inactivates
BMX-STAT3 in glioma stem cells to impair malignant growth
and radioresistance. Sci Transl Med. 2018;10:eaah6816.
17) Couturier CP, Ayyadhury S, Le PU, Nadaf J, Monlong J, Riva G,
Allache R, Baig S, Yan X, Bourgey M, Lee C, Wang YCD, Wee
Yong V, Guiot MC, Najafabadi H, Misic B, Antel J, Bourque
G, Ragoussis J, Petrecca K. Single-cell RNA-seq reveals that
glioblastoma recapitulates a normal neurodevelopmental
hierarchy. Nat Commun. 2020;11:3406.
18) Neftel C, Laffy J, Filbin MG, Hara T, Shore ME, Rahme GJ,
Richman AR, Silverbush D, Shaw ML, Hebert CM, Dewitt
J, Gritsch S, Perez EM, Gonzalez Castro LN, Lan X, Druck N,
Rodman C, Dionne D, Kaplan A, Bertalan MS, Small J, Pelton K,
Becker S, Bonal D, Nguyen QD, Servis RL, Fung JM, Mylvaganam
R, Mayr L, Gojo J, Haberler C, Geyeregger R, Czech T, Slavc
I, Nahed BV, Curry WT, Carter BS, Wakimoto H, Brastianos
PK, Batchelor TT, Stemmer-Rachamimov A, Martinez-Lage
M, Frosch MP, Stamenkovic I, Riggi N, Rheinbay E, Monje M,
Rozenblatt-Rosen O, Cahill DP, Patel AP, Hunter T, Verma IM,
Ligon KL, Louis DN, Regev A, Bernstein BE, Tirosh I, Suvà ML.
An integrative model of cellular states, plasticity, and genetics for
glioblastoma. Cell. 2019;178:835-49.e21.
19) Bernstock JD, Mooney JH, Ilyas A, Chagoya G, Estevez-Ordonez
D, Ibrahim A, Nakano I. Molecular and cellular intratumoral
heterogeneity in primary glioblastoma: Clinical and translational
implications. J Neurosurg. 2019;23:1-9.
20) Spinelli C, Montermini L, Meehan B, Brisson AR, Tan S, Choi
D, Nakano I, Rak J. Molecular subtypes and differentiation
programmes of glioma stem cells as determinants of extracellular
vesicle profiles and endothelial cell-stimulating activities. J
Extracell Vesicles. 2018;7:1490144.
21) Malta TM, de Souza CF, Sabedot TS, Silva TC, Mosella MS,
Kalkanis SN, Snyder J, Castro AVB, Noushmehr H. Glioma CpG
island methylator phenotype (G-CIMP): Biological and clinical
implications. Neuro Oncol. 2018;20:608-20.
22) Cengiz P, Zafer D, Chandrashekhar JH, Chanana V, Bogost
J, Waldman A, Novak B, Kintner DB, Ferrazzano PA.
Developmental differences in microglia morphology and gene
expression during normal brain development and in response to
hypoxia-ischemia. Neurochem Int. 2019;127:137-47.
23) Cikla U, Chanana V, Kintner DB, Covert L, Dewall T, Waldman
A, Rowley P, Cengiz P, Ferrazzano P. Suppression of microglia
activation after hypoxia-ischemia results in age-dependent
improvements in neurologic injury. J Neuroimmunol.
24) Beppu T, Kamada K, Yoshida Y, Arai H, Ogasawara K, Ogawa A.
Change of oxygen pressure in glioblastoma tissue under various
conditions. J Neurooncol. 2002;58:47-52.
25) Chen F, Rosiene J, Che A, Becker A, LoTurco J. Tracking
and transforming neocortical progenitors by CRISPR/Cas9
gene targeting and piggyBac transposase lineage labeling.
26) Huizer K, Zhu C, Chirifi I, Krist B, Zorgman D, van der Weiden
M, van den Bosch TPP, Dumas J, Cheng C, Kros JM, Mustafa
DA. Periostin Is Expressed by Pericytes and Is Crucial for
Angiogenesis in Glioma. J Neuropathol Exp Neurol. 2020;79:863-72.
27) Hardee ME, Zagzag D. Mechanisms of glioma-associated
neovascularization. Am J Pathol. 2012;181:1126-41.
28) Siddiqi F, Chen F, Aron AW, Fiondella CG, Patel K, LoTurco JJ.
Fate mapping by piggyBac transposase reveals that neocortical
GLAST+ progenitors generate more astrocytes than Nestin+
progenitors in rat neocortex. Cereb Cortex. 2014;24:508-20.
29) Caspani EM, Crossley PH, Redondo-Garcia C, Martinez S.
Glioblastoma: A pathogenic crosstalk between tumor cells and
pericytes. PLoS One. 2014;9:e101402.
30) Colwell N, Larion M, Giles AJ, Seldomridge AN, Sizdahkhani
S, Gilbert MR, Park DM. Hypoxia in the glioblastoma
microenvironment: Shaping the phenotype of cancer stem-like
cells. Neuro Oncol. 2017;19:887-96.
31) Ahir BK, Engelhard HH, Lakka SS. Tumor development and
angiogenesis in adult brain tumor: Glioblastoma. Mol Neurobiol.
32) Onishi M, Kurozumi K, Ichikawa T, Date I. Mechanisms of
tumor development and anti-angiogenic therapy in glioblastoma
multiforme. Neurol Med Chir (Tokyo). 2013;53:755-63.
33) Sheng Y, Wu B, Leng T, Zhu L, Xiong Z. Acid-sensing ion
channel 1 (ASIC1) mediates weak acid-induced migration of
human malignant glioma cells. Am J Cancer Res. 2021;11:997-
34) Tian Y, Bresenitz P, Reska A, El Moussaoui L, Beier CP, Gründer
S. Glioblastoma cancer stem cell lines express functional acid
sensing ion channels ASIC1a and ASIC3. Sci Rep. 2017;7:13674.
35) Lin YT, Wu KJ. Epigenetic regulation of epithelial-mesenchymal
transition: Focusing on hypoxia and TGF-β signaling. J Biomed
36) Wang JQ, Yan FQ, Wang LH, Yin WJ, Chang TY, Liu JP, Wu KJ.
Identification of new hypoxia-regulated epithelial-mesenchymal
transition marker genes labeled by H3K4 acetylation. Genes
Chromosomes Cancer. 2020;59:73-83.
37) Lan X, Jörg DJ, Cavalli FMG, Richards LM, Nguyen LV, Vanner
RJ, Guilhamon P, Lee L, Kushida MM, Pellacani D, Park NI,
Coutinho FJ, Whetstone H, Selvadurai HJ, Che C, Luu B, Carles
A, Moksa M, Rastegar N, Head R, Dolma S, Prinos P, Cusimano
MD, Das S, Bernstein M, Arrowsmith CH, Mungall AJ, Moore
RA, Ma Y, Gallo M, Lupien M, Pugh TJ, Taylor MD, Hirst
M, Eaves CJ, Simons BD, Dirks PB. Fate mapping of human
glioblastoma reveals an invariant stem cell hierarchy. Nature.
38) Driessens G, Beck B, Caauwe A, Simons BD, Blanpain C.
Defining the mode of tumour growth by clonal analysis. Nature.