Understanding Cell-to-Cell Communication in Cancer
Whitepaper
Published: May 14, 2024
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Last Updated: May 30, 2024
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As we learn more about cancer, it appears that the communication pathways that cancer cells use between themselves, and with cells in their environment, are much more intelligent than once believed.
This article explores how we can find new ways to stop tumor growth and prevent drug resistance by targeting the language of cancer cell communication.
Download this article to learn more about how:
- Cancer cells propagate information
- Brain tumor cells communicate with healthy neurons
- Drug-resistant tumor cells communicate directly with immune cells
Understanding Cell-to-Cell
Communication in Cancer
Article Published: August 1, 2023 | Joanna Owens, PhD
Credit: iStock
For many years, tumors have been considered as masses of rogue cells growing
uncontrollably, brought about by aberrant cell signaling pathways. But as we learn
more about the disease, it appears that the communication pathways that cancer
cells use between themselves, and with cells in their environment, are much more
intelligent. Here, we explore how by targeting the language of cancer cell
communication, we can find new ways to stop tumor growth and prevent drug
resistance.
Cancer cells are a community with their own language
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“There’s probably two broad themes that have emerged in recent years that have
led us to think differently about cancer,” says Professor Chris Bakal at The Institute
of Cancer Research, London. “The first is the idea that cancer cells are not just
communicating with cells in their environment and between themselves, but are
communicating with normal cells in the body, such as cancer-associated fibroblasts
or neurons. The second idea is that cancer cells aren’t just growing uncontrollably
and oblivious to what’s around them, but are talking to each other in a more
strategic fashion, coordinating actions among themselves as a community.”
Bakal’s lab focuses on how cancer cells change their shape and how shape affects
their function. They specialize in using imaging technologies and developing
machine learning methods to quantify cell shape in different settings, whether it’s
the lab or the clinic. In a recent study,1 Bakal collaborates with Dr. Amanda Foust
and Professor Mustafa Djamgoz at Imperial College London. Foust had developed
a method for visualizing voltage fluctuation in cells, and the Bakal lab found a way
of processing this complex information so it could be quantified and compared.
Together, they observed that breast cancer cells were making different fluctuations
in voltage compared to healthy cells, and these were not random – they were very
predictable and looked in many ways like a signal.
Bakal and Foust are now exploring this observation further with melanoma cells. “A
lot of the cells we work on change their shape to look a lot like neurons, developing
synapses and other functions that neurons have,” he explains. “Melanoma cells
come from neural crest progenitors so it’s not that much of a stretch to imagine
that they can adapt in this way. Neurons have this incredible property, changing
their shape to make long extensions that ultimately form a network, so we initially
thought the changes in melanoma cell shape were to enable them to invade
surrounding tissue. But, although we still think this is important, we’re also starting
to consider that this change in shape might be a way for cancer cells to propagate
information like neurons.”
Unlike the relatively slow, soluble signal produced by a ligand being released from
a cell towards a receptor over a short distance, these electrical pulses offer a rapid
and distant transmission system, perhaps like the quorum sensing seen in bacteria
and electrical signals used by fungi. “It’s not inconceivable that there are similar
quorum sensing systems in communities of cancer cells, allowing them to tell each
other where nutrients are and coordinate their metabolism,” says Bakal. “If you
look across many different cancer cell types, there’s a limited number of distinct
electrical patterns. Once you start to get predictable classes of signal, you can
begin to see the building blocks of a code or language, where different patterns
might be received differently by different cells. If we can stop these signals, it
would dysregulate the community, rather like having an army without its general.
The challenge is, we might understand the language, but we don’t yet know what
the cellular response is.”
Brain tumor cells communicating with healthy neurons
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In the Hervey-Jumper lab at University of California, San Francisco, Dr. Saritha
Krishna has been exploring how glioblastoma cells influence neural activity in distal
sites within the brain.2 “We know from preclinical studies that there’s a strong
positive feedback loop between neurons and glioblastoma cells in the
microenvironment,” says Krishna. “We wanted to ask what this feedback loop
means for patients in terms of their cognitive function.”
The Hervey-Jumper team recruited volunteers awaiting surgery whose tumors had
infiltrated the brain region controlling speech and used intra-operative mapping
during surgery to capture brain activity during different language tasks. In addition
to finding neural activity in the specific brain areas responsible for language
processing, there was activation in broader regions of the brain unrelated to these
cognitive functions.
“This told us that the gliomas were remodeling wider neural circuits, so we set out
to understand why,” said Krishna. They collected tumor biopsies from regions with
high functional connectivity (HFC) to the rest of the brain and regions with low
functional connectivity (LFC) and ran a series of experiments looking at gene and
protein expression. The HFC regions were enriched for genes that form synapses
with other cells, including thrombospondin 1 (TSP1).
“When we co-cultured these TSP-expressing HFC cells with neurons, they started to
rapidly proliferate and, in a 3D culture system, the tumor cells integrated
extensively in the neuron organoids. By contrast, the LFC cells seemed to care less
about being near neurons and showed minimal neuron integration,” Krishna
added. When TSP1 was exogenously added to the LFC cells, they started to behave
like the HFC glioma cells, suggesting that TSP1 is critical for this neuron–glioma
interaction.
Having established that glioblastoma cells had these neuronotrophic properties,
Krishna and her colleagues looked at whether this resulted in the increased
hyperactivity they saw in the brains of glioblastoma patients: “Again, we found that
in the presence of the HFC cells, the neurons were hyperexcitable. We think that
these HFC glioblastoma cells are literally integrating into neural circuits.”
Based on these findings, the team has already tested a cheap and readily available
anti-convulsant drug, gabapentin, and was able to successfully disrupt the
glioblastoma–neuronal communication in preclinical models. “We are still in the
early stages, but this gives us hope that this drug, which is already used in brain
tumor patients to control seizures, might also limit tumor expansion. In the future,
it might also be possible to use neuromodulation techniques to target the
hyperexcitable neurons in the tumor microenvironment and spare the healthy
neurons. I’m hopeful that this finding could be beneficial to patients.”
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It’s not only healthy surrounding tissues that cancer cells are influencing with
communication tactics. There is growing evidence that tumors can gain the ability
to signal directly to non-cancer cells within the tumor microenvironment. Dr. Jason
Griffiths, an associate professor at Department of Medical Oncology and
Therapeutics Research, City of Hope National Medical Center and the University of
Utah, Salt Lake City, studies the ecology of cancer and the phenotypic evolution
that we see within tumors. His lab uses single-cell molecular data to look within the
tumors of patients enrolled on clinical trials before, during and after treatment.
“We know that as cancer cells evolve and acquire resistance to therapy, one way in
which they do this involves altering communication with non-malignant cells in the
tumor microenvironment (TME),” said Griffiths. “However, the specific interactions
between malignant and non-malignant cells that cause this drug resistance remain
widely unknown.”
In a recent study they profiled more than 400,000 single cells from serial biopsies
of estrogen receptor-positive breast cancer tumors in patients being treated with
either endocrine therapy alone or in combination with ribociclib, a cell cycle
blocking drug.3 They used single-cell RNA sequencing to determine the gene
expression profile of each cell and an immune cell classifier to understand the
immune composition of the different tumor biopsy samples.
Once they had identified the cell types, they used an extended version of the
expression profiling method to measure cell interactions. “We looked at ligand and
receptor gene expression in each cell, and then applied a statistical analysis
method to tell us how much each of these different subpopulations of cells are
signaling to one another. This produced an overall network map of how strongly
these cell types are communicating,” Griffiths explained. Next, they compared the
networks of communication between resistant and responsive tumor types. “What
we were able to see from this network analysis is that the resistant tumor cells
lacked normal communication with immune cells but were sending lots of
immunosuppressive signals to macrophages,” said Griffiths. “We know cancer cells
can alter the phenotypes of macrophages and myeloid cells, and there's a lot of
talk about the role of cancer-associated fibroblasts and endothelial cells that can
support the growth of the cancer by producing networks of capillaries that
provides resources. What was unclear before doing this study was which of these
cell types play these roles.”
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Griffiths is now looking more closely into the mechanism of immune suppression
in tumors treated with ribociclib: “We’ve been using in vitro systems where we can
co-culture tumor cells and macrophages to understand more about the social
communication aspect, and we’re moving into spatially resolved analyses, where
we try to preserve the spatial orientation of the cells and look at how those cell
interactions play out in a tissue. But the most important thing we discovered is that
tumors that don’t respond to ribociclib lack activated T cells, which suggests
ribociclib has a dual role: stopping proliferation by blocking the cell cycle, but also
having a negative effect on anti-cancer T cells. This tells us that patients who have
not responded well to ribociclib might benefit from additional therapy to reactivate
their immune system.”
References:
1. Quicke P, Sun Y, Arias-Garcia M, et al. Voltage imaging reveals the dynamic
electrical signatures of human breast cancer cells. Commun Biol. 2022;5(1):1178.
doi: 10.1038/s42003-022-04077-2
2. Krishna S, Choudhury A, Keough MB, et al. Glioblastoma remodelling of human
neural circuits decreases survival. Nature. 2023;617(7961):599-607. doi:
10.1038/s41586-023-06036-1
3. Griffiths JI, Cosgrove PA, Castaneda EM, et al. Cancer cells communicate with
macrophages to prevent T cell activation during development of cell cycle therapy
resistance. bioRxiv 2022.09.14.507931; doi: 10.1101/2022.09.14.507931. This article
is a preprint and has not been certified by peer review.
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