Stefanie Jeffrey, MD (2) |
Alternatively, a tumor can be polyclonal in origin. In this case, multiple cells transform from
normal to malignant, leading to a tumor mass composed of genetically distinct
sub-populations of cells. (1) (Fig. 1)
Over the weekend, I came across a study conducted by a group
of Stanford scientist who have discovered that cancer cells shed by a single
tumor into the bloodstream are genetically diverse. Some cancer cells have turned on genes that make
them more adept at lodging themselves in new places, aiding in their ability to
metastasize to new organs (2). Other
cancer cells have an entirely different pattern of gene expression.
The senior author of the study is Stefanie Jeffrey, MD, professor of surgery and chief of surgical oncology research at the Stanford University School of Medicine. The research was published in PLoS ONE on May 7, 2012.
The senior author of the study is Stefanie Jeffrey, MD, professor of surgery and chief of surgical oncology research at the Stanford University School of Medicine. The research was published in PLoS ONE on May 7, 2012.
What are Circulating Tumor Cells (CTCs)?
Circulating tumor cells (CTCs) are rare cells found in the
blood of patients with solid tumors (3).
They are epithelial cells shed from the tumor itself, and are believed
to play an important role in cancer metastasis.
Previous studies have found the number of CTCs in blood to be tightly
linked with clinical outcome in patients with metastatic breast, prostate,
colorectal, and lung cancer (4, 5, 6, 7). Therefore, isolating CTCs and identifying their genetic makeup, may
provide us with necessary information to one day be able to target
these cells and slow cancer dissemination.
Since CTCs are accessible by an easy blood draw from the
cancer patient, extracting and genotyping CTCs would seem to be a fairly easy task. However, CTCs are present in the blood of
cancer patient’s amidst 5x109 (billions) red blood cells and 5x106
(millions) white blood cells per ml (3). Therefore, due to their rarity, separating
CTCs from blood cells is extremely difficult.
In this study, Jeffrey and her team focused on studying CTCs from breast cancer patients. Initially, the researchers collected blood samples from 50 participants: 20 primary breast cancer patients without detectable metastatic disease, and 30 metastatic breast cancer patients (3). All individuals were consented patients of the Stanford Breast Oncology Clinic.
In this study, Jeffrey and her team focused on studying CTCs from breast cancer patients. Initially, the researchers collected blood samples from 50 participants: 20 primary breast cancer patients without detectable metastatic disease, and 30 metastatic breast cancer patients (3). All individuals were consented patients of the Stanford Breast Oncology Clinic.
Isolating CTCs: MagSweeper
In order to overcome the challenge of extracting CTCs from
blood, Jeffrey in conjunction with a team of engineers, quantitative
biologists, genome scientists, and clinicians, developed a machine called the
MagSweeper. The MagSweeper uses an
immunomagnetic separation technology to extract live CTCs with very high purity
from the blood samples of patients with breast cancer (2).
To isolate CTCs, Jeffrey and her team capitalized on a
cell-surface protein present on epithelial cancer cells, but absent on
healthy blood cells (2). The protein is
called EpCAM (epithelial cell adhesion molecule). First, the scientists treated each blood
sample from their breast cancer patients with antibodies against human
EpCAM. Attached to the anti-EpCAM
antibodies were small magnetic beads.
Jeffrey then had the MagSweeper device scan each blood
sample twice. The MagSweeper is equipped with a magnetic rod, such that the
movement of the MagSweeper during each scan produces a force that attracts any
cell that has been bound by the anti-EpCAM-magnetic bead-antibody, while
releasing other blood cells. Captured
cells were then released into a buffer for analysis later (3) (Fig. 2).
Is the MagSweeper specific for
cancer cells?
To test whether the MagSweeper was
specific for epithelial cancer cells, the researchers ran a control. Jeffrey used the device to scan blood samples
from 45 patients without epithelial cancer: 25 healthy volunteers and 20
lymphoma patients. No cells were
captured, indicating that the MagSweeper was specific for epithelial cancer
cells only (3).
Does the MagSweeper alter gene
expression in cells?
To test whether the MagSweeper
itself altered gene expression levels in cells, the researchers measured the
expression of 15 genes in tumor cells derived from a primary breast cancer
cell-line, called MC47. Jeffrey compared
gene expression before and after the magnetic bead-antibody labeling step. She also compared gene expression before and
after the MagSweeper capture process. They
found that expression of the 15 genes did not change during labeling or
MagSweeper capture, indicating that the entire MagSweeper isolation process has
no effect on gene expression (3) (Fig. 3A).
Does the MagSweeper affect cell
viability?
To test whether the MagSweeper itself altered cell
viability, the researchers measured plating efficiency of tumor cells derived
from the same primary breast cancer cell-line used earlier, MC47. Plating efficiency is the percentage of cells
that produce viable colonies after seven days of growth. Once again, Jeffrey compared plating efficiency
before and after the magnetic bead-antibody labeling step, as well as plating efficiency
before and after the MagSweeper capture process. They found that plating efficiency did not
change during labeling or MagSweeper capture, indicating that the complete
MagSweeper isolation process has no effect on cell viability (3) (Fig. 3B).
Defining CTCs
To narrow down the EpCAM-captured cells (510 cells total) from the blood samples of their breast cancer patients, Jeffrey developed a series of criteria for defining CTCs.
To narrow down the EpCAM-captured cells (510 cells total) from the blood samples of their breast cancer patients, Jeffrey developed a series of criteria for defining CTCs.
First, the cells needed to express
three reference genes: actin, beta (ACTB), glyceraldehyde-3-phosphate dehydrogenase (GAPDH), and ubiquitin B (UBB).
The ACTB, GAPDH, and UBB genes were selected because their expression is commonly seen
in breast cancer cells. For example, UBB gene expression has been validated
in over 1,700 breast cancer samples (3).
After this initial screen, 63% (321/510) of the cells isolated by the
MagSweeper qualified for further analysis (3).
Next, the researchers ran the
captured cells through another set of criteria.
Jeffrey and her team selected cells that had: 1) no expression of the
white blood cell marker, CD45, 2)
expression of any of the following epithelial cell markers – KRT7 (keratin 7), KRT8 (keratin 8), KRT18
(keratin 18), and/or KRT19 (keratin 19). Recall that Dr. Jeffrey and her team
initially collected blood samples from 50 participants: 20 primary breast
cancer patients without detectable metastatic disease, and 30 metastatic breast
cancer patients. After this final
screen, however, the scientists were left with blood samples from only 35
patients: 14 with primary breast cancer and 21 with metastatic breast cancer
(3).
Since some patients had more
qualified-CTCs compared to others, the researchers randomly selected five CTCs
per patient (3).
Gene Expression
Once the researchers isolated their
CTCs of interest, their next goal was to obtain the genetic profile of each
individual cell. Stephen Quake, PhD,
Stanford engineer professor, invented real-time PCR microfluidic chips that
allowed them to measure expression levels of 87 cancer-related genes along with
the 3 reference genes (ACTB, GAPDH, and UBB) in individual CTCs at once
(2). In contrast to past studies where researchers
analyzed CTCs in groups and took their average gene expression, Jeffrey wanted
to look at circulating tumor cells one-by-one in order to detect differences
between individual tumor cells.
Jeffrey selected the 87 genes based
on published literature. They included
genes common in molecular pathways relevant to breast cancer, breast cancer
biomarkers, as well as genes associated with cancer signaling pathways,
epithelial-mesenchymal transition, cancer stem cells, and metastasis (3).
Is the real-time PCR microfluidic
chip accurate?
To test whether the real-time PCR microfluidic chips were
accurate in detecting gene expression levels, the researchers ran a
control. Jeffrey and her team analyzed tumor
cells from: three primary (CCdl054, CCdl672, CCdl675), and four metastatic
(T47D, MCF7, SKBR3, MDA-MB-231) breast cancer cell-lines. Used by breast cancer researchers and
pharmaceutical scientist worldwide, the genetics of these seven tumor
cell-lines are well-outlined, thereby allowing researchers to know if the chips
work well (2).
First, the scientists extracted genetic material from
individual cell-line derived tumor cells.
Next, Jeffrey used the PCR microfluidic chips to simultaneously measure
expression of all 87 genes in each tumor cell.
Jeffrey and her team found that indeed, genes expressed in the tumor
cells reflected the known properties of the cell-line models. For example, 99% (48/49) of the cell-line
CTCs expressed the human epidermal growth factor receptor 2 (HER2) and the epidermal growth factor (EGFR) – consistent with expected breast
cancer biomarker patterns (3) (Fig. 4).
The results indicate that the PCR microfluidic chips are accurate at
detecting gene expression.
Next, Jeffrey and her team extracted genetic material from
individual CTCs derived from the blood samples of patients with primary and metastatic
breast caner. Once again, they used the
PCR microfluidic chips to simultaneously measure expression of all 87 genes in
each CTC. The researchers found that 31
out of the 87 genes tested, were commonly expressed in 15% of the CTCs
analyzed. The 31 genes were associated
with: 1) epithelial mesenchymal
transition - TGFb-1, FOXC1, CXCR4, NFKB1, VIM,
ZEB2; 2) metastasis – S100A9, NPTN, S1004A; 3) PI3K/AKT/mTOR
pathway – AKT1, AKT2, PIK3R1, PTEN;
4) apoptosis – BAX, CASP3, CD53, CD59; 5) cell
proliferation – RRM1, MAPK14; 6)
DNA repair – PARP1; 7) cell metabolism – SLC2A1, TFRC; 8) stem cell
phenotype – CD24, CD44 (3).
Further analysis of the 31 most
dominantly expressed genes showed two distinct groups of circulating tumor
cells. Cluster I was comprised of 21
CTCs from 13 patients, and Cluster II was comprised of 84 CTCs from 30 patients
(3). “Depending on which genes we used
to divide the CTCs into groups, there were as many as five groups, each with
different combinations of genes turned on and off,” Jeffrey explains (2) (Fig.
5).
The results indicate that solid tumors
contain a variety of genetically different cancer cells that may eventually get
shed into the bloodstream.
Applying this finding to clinical
medicine means that a single biopsy from a patient’s tumor may not be
sufficient nor representative of the entire population of cells within that
tumor. For example, one of the breast cancer
patients in this study had some CTCs positive for HER2, and some CTCs negative for the marker. When this particular patient was treated with
a therapeutic used for HER2-positive
cancers, the CTCs with HER-2 were
eliminated while the CTCs lacking HER2
remained in her bloodstream (2). Although
for many reasons it is physically impossible to biopsy every single metastatic
lesion a cancer patient may have, Jeffrey and her team believe CTC-blood draws
may offer a non-invasive means of studying the wide variety of molecular
changes that drive a cancer forward and help it to spread.
Gene expression in cell-line derived
tumor cells vs. patient derived CTCs
Lastly, Jeffrey and her team
compared the genetic makeup of CTCs from breast cancer patients with tumor
cells from the widely-used experimental cell-line models they studied
earlier. When the 31 most commonly
expressed genes were considered, the researchers found that none of the human
CTCs had the same gene patterns as any of the tumor cells from the cell-line
models. For example, CTCs from breast
cancer patients had higher expression of genes encoding growth factors and
their receptors compared to tumor cells from cell-lines. Furthermore expression of
genes encoding proteins that act as downstream effectors in cell cycle
progression and proliferation, were also higher in CTCs from breast cancer
patients compared to tumor cells from cell-lines (2) (Fig. 6).
The results indicate that human
derived CTCs have a different gene profile compared to cell-lines derived tumor
cells.
Applying this finding to the world
of cancer research is a bit scary, because tumor cells from these cell-lines
are what scientists worldwide are using to develop drugs as well as test
drugs. This means that drugs that appear
to be effective in tumor cells from cell-lines may not be effective at all
against human CTCs due to different genetic profiles.
Conclusion
Ultimately, Jeffrey’s findings are
the first to show the extent of the genetic differences between tumor
cells. By looking at tumor cells
one-by-one, the scientists discovered that even in an individual patient, tumor
cells that make it into blood vary drastically.
The fact that CTCs are thought to play an important role in
tumor metastasis along with the fact that these cells are accessible by an easy
blood draw, could be the key to tracking tumors and detecting early metastasis
in patients. The genetic variation found
in individual tumor cells could also change the way tumors are treated – in
that maybe a more diverse combination of chemotherapeutics to treat each cell
type present may be required. Lastly,
the significant differences in gene expression found between tumor cells
derived from cell-lines and CTCs derived from human patients could change the
way cancer research, specifically in regards to therapeutic development, is
conducted.
Question & Thoughts
After reading
the paper, a few questions and thoughts came to mind:
1) After reading the Hallmarks of Cancer:
The Next Generation, the findings of Jeffrey’s team are really not
surprising. In their article, Hanahan
and Weinberg outline genome instability and mutation as an enabling
characteristic of tumor cells. We know
from Dr. Islas’ telomerase lecture that cancer cells actually want to
acquire mutations, especially those that are advantageous for survival and growth. This is evidenced by the phenomenon termed,
“delayed telomerase activation,” in which cancer cells will actually wait until
their genome has generated enough tumor-promoting mutations before activating
expression of telomerase. Hanahan and
Weinberg attribute this enabling characteristic of cancer cells to the fact that
“certain mutation genotypes confer selective advantage on subclones of cells,
enabling their outgrowth and eventual dominance in a local tissue environment”
(8). Therefore, the genetic variance
seen in each individual circulating tumor cell in this study could very well be
a prime example of cancer cells generating genomic instability so that they are
able to more easily metastasize and invade other areas of the body.
2) Do cancer cells turn genes on and off at random? Or do cancer cells select their genetic profiles, by knowing which genes will be most advantageous turned on
or off?
Possible Answer: Although I do not know the exact
answer to this question, it seems most likely that mutations will occur at
random. If you think about it, cancer
cells only care about one thing – that is dividing, and diving fast. Tumor cells are not concerned about how
“pretty” that division is, so long as it happens fast. Rapid division means careless DNA replication,
which ultimately means increased chances of mutation during each cell
cycle. This can easily lead to a tumor
being genetically diverse. Therefore,
once again, the genetic variance of each individual tumor cell that Jeffrey and
her team saw really is not surprising. Overtime, we would expect natural
selection to occur – selecting for cancer cells with the most “harmful” genetic
profile, selecting for those cancer cells with the perfect combination of genes
turned off and on.
3) The real-time PCR microfluidic chip
used to measure gene expression in this study is very similar to the gene
expression array Dr. Islas discussed in class. Researchers use these functional genomic
tools to survey the expression levels of many genes in a tissue
preparation. Computerized analysis
following the expression arrays then makes it possible to identify certain
genes that may be over- or under-expressed compared to normal cell counterparts. Similar to what was done by Jeffrey in this
study, once a genetic profile of a tumor cell is known, researchers can then
use this information to divide or stratify cancers into groups having certain
biological properties. Dr. Islas took
this genetic profiling of cells a step further when he mentioned the use
of personalized medicine. This means
that once the genetic profile of tumor cells, such as CTCs are known,
clinicians may one day be able to tailor drugs and a design a treatment plan
that is specific against an individual patient’s cancer.
4) The previous question, question #3, leads
to the following question: What happens if the gene profiles of CTCs constantly
change?
If ever
blood draws detecting CTCs actually becomes a clinical diagnostic tool, I
suspect that physicians will have the tests repeated every so many months in
order to make sure the patient has not developed any significantly new forms of
CTCs.
5) This may be useful information for
groups interested in doing their cancer project on cancer metastasis.