More than 90% of of cancer related mortality is caused by metastasis. To
develop new therapeutic strategies it is vital to understand the initiation and
progression of metastasis. To identify and isolate metastasis initiating
tumour-cells scientists developed a fluorescence-activated cell sorting
(FACS)-based array. There are two types of metastasis-cells: metastasis-cells
from low-burden cells and metastasis-cells from high-burden cells. After being
transplanted, low-burden metastasis-cells showed that they have a considerable
amount of tumour initiating ability and could differentiate to produce
luminal-like cancer cells. When low-burden metastatic cells progress to
high-burden metastasis cells they get an increased proliferation and MYC
expression. This can be weakened with the use of inhibitors. This all supports
a hierarchical model in which metastasis is initiated by stem-like cells, and
can progress from low-burden to high-burden metastasis cells.


The human breast contains two kinds of epithelial lineages: the
basal/myoepithelial which contains stem-cells, and the luminal lineage which
contains progenitor cells and mature cells. The scientists used breast tissue
from the mammoplasty of three individuals. With the use of numerous statistical
analysis they concluded that basal/myoepithelial and luminal lineage is
different for everyone.They focused in this experiment on a particular subtype,
because this subtype is the most aggressive and there is no suitable treatment
for it. The patient-derived xenograft maintained the same properties in the
mice as in the patients and because of this it was suitable for the studies of
human metastasis.


To isolate the metastasis cells from the patient derived xenograft mice
they developed a new FACS based array. With this they were able to detect
metastatic cells in 70% of the patient-derived xenograft peripheral tissue from
the mice. The mice were analyzed when their tumours reached 20-25 mm in
diameter. The growth kinetics was consistent within each model.


Although the tumour of every animal had about the same diameter they all
had great variation in metastatic burden. The scientists also found out that
PCA plots for mice with low burden metastasis cells were further away from the
tumour they derived from than high burden metastasis cells. Other experiments
also showed that low burden metastasis cells liked to form clusters with each
other while high-burden metastasis cells liked to form clusters with primary
tumour cells. The scientists found out that low burden metastasis conserved
their basal/myoepithelial signatures. They had expressed higher levels of 22
basal/myoepithelial genes and expressed lower levels of 7 luminal genes.


By focusing on clustering only the metastasis cells the scientists
discovered incredible heterogeneity in differentiation, which correlated with
metastatic burden. Akin to the mammary gland metastatic cells organized into
two different clusters, where the low-burden cells were the most
basal/stem-like and the high-burden cells were the most luminal-like. The scientists
concluded the same conclusion with lung metastatic cells. Which means that it
is a conserved phenomenon in each model. There were some differences between
gene expression of lung metastatic cells of different models, but they were not
enough to cluster metastatic cells separately by patient derived xenograft


In order to investigate heterogeneity at protein level scientists performed
immunostaining for a basal and luminal gene. Tumour cells found in
micrometastatic from low-burden tissues had a high percentage for the basal
gene and luminal gene and tissues from high-burden tissues had a high
percentage for the luminal gene and were heterogeneous for the basal gene. This
suggest that differentiation status correlates with metastatic burden in


By means of single cell analyses scientists discovered that in the
low-burden metastatic cells had high levels of pluripotency genes. These genes
suggest that they are exploited embryonic programs for self-renewal and
maintenance. Low-burden metastatic cells also expressed higher levels of
typical EMT-markers, except for an EMT-marker which was typically found in
normal basal/stem cells. All these findings are consistent with previous
reports which show that EMT promotes stemness in mammary gland, and suggest
that low-burden metastatic cells utilize an EMT-program to make dissemination
easier. Further studies also revealed that genes involved in the DNA damage
response, chromatin modification, differentiation, apoptosis and the cell cycle
were differentially expressed in low-burden metastatic cells.


Because of the heterogeneity in metastatic cells scientist wondered if
stem-like cells directly give rise to luminal-like cells, or if the luminal
cells are originated from founder-cells. After an experiment the scientist
concluded that luminal-like cells can derive from cells that disseminate at the
early stages of primary tumour growth.


To test the growth and differentiation capacity of stem like metastatic
cells, scientists transplanted low-burden metastatic cells into mammary glands.
Interestingly 2 of 4 transplanted cells produced large tumour, while primary
tumour cells never produced tumours, even at 100 fold high numbers. This is
consistent with the previous reports which showed that PDX tumours are more
efficiently increased as fragments than dissociated cells. After single cell
analyses scientists concluded that low burden-metastatic cells have high tumour
initiating capabilities, and that they can give rise to luminal-like tumour
cells. This supports the hypothesis that stem-like metastatic cells give rise
to luminal metastatic cells.  


Another interesting question the scientists had was is stem-like cells were
present in tumour cells, or if they evolve after interaction with their
microenvironment. After a test the scientists concluded that primary tumours
contain a rare subpopulation of stem-like cells, and that the percentage
correlates with metastatic potential. Afterwards scientists wanted to know if
enrichment of this stem-like signature in primary tumours may be predictive of
distant metastasis in human patient data sets. After an analyses the scientists
found that 16 of 55 genes associated with stem-like metastatic cells were
significantly prognostic.


Previous work has shown that metastatic cells in different organs display
distinct gene expression signatures. Supervised clustering by target organ has
shown that metastatic cells in brain, bone marrow and peripheral blood had
differences in gene expression patterns. Brain metastatic cells were the most


CTC’s are very important for use as a ‘liquid biopsy’ for diagnosis and
prognosis. Most CTCs and bone marrow DTCs clustered with ‘intermediate’
metastatic cells, which may be because the cells were harvested from animals
with intermediate burden. However, 16.7% and 10.7%, showed a more
basal/stem-like signature, suggesting that these stem-like cells may represent
the true metastatic seeder cells.


We also observed a shift towards a more proliferative signature associated
with increased metastatic burden. Low-burden metastatic cells expressed higher
levels of rest and dormancy-associated genes. Higher-burden metastatic cells
appeared to enter the cell cycle, expressing lower levels of quiescence and dormancy-associated
genes and higher levels of cell-cycle-promoting genes.We also detected primary
tumour cells (22.2%) with this less-proliferative signature.


These findings prompted us to test whether blocking this switch from
dormancy into the cell cycle could inhibit metastatic progression. Since we
observed high levels of both MYC and CDK2 in more advanced stage metastatic
cells , we chose to test a CDK inhibitor that has been shown to induce
apoptosis in high MYC-expressing cancer cells via synthetic lethality. We
hypothesized that apoptosis would be induced in metastatic cells transitioning
into proliferation, since they appear to upregulate MYC. After testing this on
mice we found that by looking in high resolution at gene expression in single
metastatic cells, we have uncovered previously unrealized diversity in
differentiation and gene expression relating to the metastatic stage ,and
demonstrate that this approach can facilitate the identification of new
potential drug targets with efficacy against metastatic disease.


To begin with the analysis the researchers first gathered the cell lines
and the xenografts of the tumour tissues, which were grown and acquired
according to standard and ethical protocols. The xenografts were divided into
tumour fragments and propagated into the breasts of the mice. When the tumours
became palpable, that’s when the tumours were measured weekly to oversee their
growth rate. The tumour fragments were stored by freezing them in liquid
nitrogen. All animals from which xenografts were derived were euthanized at the
end, when the tumours had grown to about 20 to 25 mm in size. During the
resection experiment, tumours were usually removed when they reached the size
of about 10 to 12 mm. The animals on which resection was performed were brought
back to their colony and were warranted to grow metastases for 8 weeks, during
which lung tissue was gathered and analysed by fluorescence-activated cell
sorting (FACS) for human cells.


In order to measure the functional activity of metastatic cells, orthotopic
transplant experiments were performed on the animals. Particular metastatic
cells in the lymph nodes, as well as particular tumour cells from matched
animals, were segregated by FACS and combined from various animals. The sorted
cells were formed into pellets and inserted into a media. Diluted versions of
these were inserted into the breasts of 3.5-week-old mice and grafts were taken
after 4.5 months when the primary tumours became 20 mm in size.


After this began the dinaciclib treatment experiments, which were
administered when the tumours became palpable. The dinaciclib was primed and
acquired according to protocol. The mice were randomly appointed to treatments
when the tumour cells were transplanted and analysed with the help of the
single-blind design. In total, 49 animals were injected with the treatment
three times a week. Animals were measured twice a week to report primary tumour
growth. The mice were euthanized at the end of the treatment or earlier if the
tumour reached 20 mm in diameter. Animals which developed unfavourable effects
were ruled out of the study.


The microarray gene expression values were calculated using some form of
statistics program. Plasma membrane genes expressed greatly on all of the 15
tumour sample xenografts. The 12 initial patient tumour samples were ranked
from highest to lowest expression. The predicted value of every one of the 55
genes characteristics of low-burden metastatic cells was worked out by
Kaplan–Meier analysis.


All solid tissues and the brain were dissociated for FACS. The tissues were
cut up and placed in culture medium. They were then broken down for 45 min at
37 °C. The suspensions that arose were then inserted into a solution of DNase
for 3 min at room temperature, after which they were washed and dissociated
again. After this peripheral blood, supernatant and bone marrow were collected,
cells were pelleted for 5 min and leftover erythrocytes in peripheral blood,
lung and tumour samples were lysed for 5 min at room temperature. All unused
samples were directly filtered and stored by freezing them in liquid nitrogen.


The tissues from the reduction mammoplasty were washed three to five times,
cut into small fragments and digested overnight in a solution. The digested fragments
were then pelleted for 3 min, frozen and then stored in liquid nitrogen.


The antibodies for several particular human antigens were bought
commercially. Both human and mouse antibodies were stained. After 15 min of
lying on ice, the stained cells were washed to get rid of excess antibodies and
put back into the medium. The cells were then flow sorted and analysed. Dead
cells were eliminated and contaminating human or mouse haematopoietic and
endothelial cells were excluded. The complete tissue sample in the single-cell
multiplex qPCR experiments was run through the flow cytometer. A steady number
of live cells were found in the tissues of all of the animals. The results of
mice which deviated by more than one standard deviation were excluded from the


Single-cell gene-expression experiments were carried out with microfluid
chips. Single cells were sorted using FACS into distinctive wells. The
experiments were done according to protocol. Each well was prefilled with a
solution. After the sorting process, the PCR plated were frozen and or placed
into the thermocycler to go through the process of combined reverse
transcription and target-specific amplification. Exonuclease reaction solution
was subsequently added to remove unincorporated primers. Each well was then
diluted. A bit from each sample was then dropped into a separate plate and
mixed with another solution. Individual primer assay mixes were made in yet
another plate. The chips were primed before the samples and assays were mixed
into them. The chips were then evaluated thoroughly.


All of the single-cell PCR data were analysed using a statistical analysis
software. In its entirety, 268 mammary cells from reduction mammoplasties as
well as 441 metastatic and 523 primary tumour cells from the xenografts of the
mice were analysed. The results of the analyses were developed into Ct values,
which were then further generated into statistical language.


In regular mammary cell experiments, the Ct values were standardized by
deducting the average value of the basal/stem-cell population per gene and per
array. In the mice xenograft experiments, the Ct values were standardized by
deducting the average primary tumour expression per gene as well as the average
value of the basal/stem-cell population per gene and per array. Low quality
samples were found and withdrawn from additional analysis.


Various statistical tests were performed in order to determine gene
expression differences between earlier established populations. For regular
mammary cell experiments, a threefold comparison was initiated between
basal/stem, luminal, and luminal progenitor cells. This generated an array of
49 differentially expressed genes. To find out of which population each gene is
an aspect of, pair-wise tests were executed. When comparing metastatic cell
experiments to that of primary tumour cells, only the pair-wise tests were
executed. Threefold comparisons were executed to compare lung metastatic cells
from the three xenografts from the mice and fivefold comparisons were executed
to compare metastatic cells from each tissue. These analyses were done with a
variety of statistical programs.


In order to find passages which were represented in a greater fashion in
the set of significantly differentially expressed genes that they would have
been by just chance, an enrichment analysis of Biological Process gene ontology
terms was executed using several statistical programs.


For both histological analysis and immunofluorescent analysis, the tissues
were suspended overnight in paraformaldehyde and processed paraffin embedding.
The tissues were stained with haematoxylin and eosin for histological analysis.
In order to commence the immunofluorescent analysis, the tissues were stained
using immunofluorescent staining. The immunofluorescent staining was used upon
lung tissues with low and high metastatic burden.

On the sections with paraffin-embedded tissue immunostaining was carried
out by using a citrate buffer and heating the sections in a pressure cooker for
8 min. Several human genes were stained with the help of a three-step method.
First, the primary antibodies were incubated overnight, which was then followed
by one-hour incubations along with detecting antibodies after which a
fluorescent binding biotin was added. MYC and phospho-histones were found by
following a two-step method, in which the overnight staining of antibodies was
followed up by a one-hour incubation along with detecting antibodies. The
number of positive nuclei was counted for tumour, high burden, and low burden cells,
after which the significance was calculated by a statistical analysis software.


Metastasis is a process in which cancer cells spread to other sites within
the body. Metastatic cancer, also known as advanced cancer or stage IV cancer,
is defined as the spread of cancer from a primary tumour to the rest of the
body. This type of cancer is the main cause of fatality (about 90% of deaths)
in cancer patients due to the fact that it cannot be fully cured.


In order for metastasis to develop the cancer cells must first break away
from the primary tumour and travel through the circulatory and lymphatic
systems. Then it must avoid being destroyed by immune attacks initiated by the
white blood cells and erupt at beds of the capillary kind. After this, the metastasis
can infest into distant organs and proliferate. Metastatic cancer cells also
have the ability to create a new environment in which harmful secondary tumours
can cultivate.


While it is still unknown what exactly the origin is of these metastatic
cancer cells there definitely have been multiple hypotheses made about this
exact question. Many hypothesise that metastatic cells emerge during a process
in which epithelial cells go through a number of gene mutations which
eventually transforms it into a mesenchymal tumour cell. Other theories state
that metastatic cells stem from several collections of stem cells. Another
theory prevails that tumour-associated macrophages are the primary cause of
metastasis, due to the fact that it has the ability to set up a pre-metastatic
alcove and encourages tumour inflammation. The last theory states that
metastatic cancer cells appear due to inability to take up enough oxygen and/or
expel enough carbon dioxide in myeloid cells.


Metastatic cancer doesn’t just spread sporadically, instead, depending on
the type cancer, it will spread to specific sites in the body. For example,
with breast cancer the metastasis has the urge to spread mostly to the liver,
lungs, bones, and brains, while pancreas cancer has the tendency to spread to
the peritoneum, lungs and liver.


While metastatic cannot be cured yet, it can be treated in order to prolong
the life of the patient and improve their wellbeing. Typically this treatment
aims at slowing the growth of the metastasis and relieving the symptoms the
patient may experience due to the metastasis. The type of treatment depends on
the type of cancer, the size of the metastasis, where the metastasis started,
the location of the metastasis and several other factors that may intervene
with the condition of the patient or the metastasis.


Treatment for metastatic cancer typically includes systemic therapy or
therapeutics which are ingested or injected into the bloodstream. The most
common form of these therapeutics is chemotherapy or hormone therapy. Other
treatments to reduce the effects of metastasis are treatments such as radiation
therapy, biological therapy and/or surgery.

Breast Cancer to the Brain: A Clinical Primer for Translational Investigation

treatment for primary breast cancer becomes more and more effective there is a
lack of clinical advancement in the area of brain metastasis from breast
cancer. In order to broaden the spectrum of brain metastasis treatments, we
must first focus on the subtype of breast cancer, the evolution of breast
cancer subtypes as metastases form, and the general medical condition of the

for brain metastasis are currently scarce and not effective enough with a
maximum life expectancy of 16 months after the start of the treatment. While
surgically removing any lesions will definitely improve the patient’s
condition, there is a large chance of tumour recurrence unless the surgery is
followed up with radiotherapy. While radiotherapy is successful in targeting
and removing cancer cells throughout the whole brain, there have been reports
of significant cognitive decline due to the exposure of radiation to the brain
tissue. Lastly, while medical therapeutics may have the ability to rid of
cancer cells with little to no harmful side effects many chemotherapeutic
agents are unable to pass the blood brain barrier and reach the tumour.

In conclusion, in order for brain metastasis to be more
successfully treated we must focus on discovering new therapeutics that can
cross the blood brain barrier and target tumour cells.

Jammed Cells Expose the Physics of Cancer

In 1995 Peter
Friedl had a startling discovery: coordinated cells which the had been growing
in his lab started clustering together and started moving through a network of
fibers which were meant to mimic the human body.

His discovery
was important for the research about jamming, a process where different cells
pack together so tightly that they become one unit. Cells in a tumor or tissue
can change their own mechanical properties because of their mechanical
microenvironment, using genetic programs and other feedback loops, and if
jamming is to provide a solid conceptual foundation for aspects of cancer, it
will need to account for this ability.

Theories for
how cancer might behave mechanically have only been researched as theories for
solids or theories for fluids, however a small group of scientists have
suspected that a combination of sticky epithelial cells, which make up the bulk
of solid tumors, and thinner, more mobile mesenchymal cells that are often
found circulating solo in cancer patients’ bloodstreams could cause a phase
transition . Scientists also found that a phase transition between jammed and
unjammed states could fluidize and mobilize tumor cells as a group without
requiring them to transform from one cell type to a drastically different one.



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