Cancer Research: Bridging Science and Clinical Practice eBook

Foreword
Cancer is a leading cause of death worldwide. The good news is that death rates for many cancer types have been falling ‒ attributed to improved technologies for early detection, precision
genetics-based medicine and immunotherapies. However, the fight against cancer remains an
ongoing effort.
The World Health Organization predicts that in 2050, there will be over 35 million new cancer
cases – a shocking 77% increase from the 20 million cases estimated in 2022. Importantly, there
have been limited improvements in the standard of care for some cancer types targeting the
brain and pancreas, thus necessitating more research in those areas. Countries are also going to
suffer disproportionately from cancer burden depending on the risk factors that their populations are exposed to, including obesity, alcohol and tobacco consumption, and environmental
air pollution.
In this eBook, we will explore state-of-the-art research – from studying how different cells in
the tumor ecosystem communicate and contribute to cancer progression, leveraging the defensive nature of the immune system to fight cancer and the use of microchips for targeted drug
delivery to brain tumors.
A tumor is akin to a building with a complex and heterogenous mix of resident cells. There is
a continual change in the numbers and locations of the cells, and how these cells, e.g., cancer
cells, cancer-associated fibroblasts, immune cells and endothelial cells, interact influences drug
penetration and efficacy significantly.
While our immune system can perform surveillance and eliminate mutated cancer cells, these
cells are smart enough to trick protective immune cells into thinking that they are “normal”, or
even recruit suppressive immune cells to enable tumor growth. Immunotherapies, including
cancer vaccines, antibodies and chimeric antigen receptor T cells, can be used to enhance our
immune system’s protective functions against cancer. .
Among all cancer types, brain cancer is one of the most challenging, as the blood‒brain barrier
makes the delivery of drugs to the brain difficult. Intratumoral microdevices inserted into brain
tumors can help to screen drugs and identify the best combination to eliminate cancer. This
technology has broad implications for brain cancers caused by genetic mutations that can be
treated with nucleic acids-based medicine.
I hope you are as excited as me to start reading.
Andy Tay, PhD.
Prof. Andy Tay is a Presidential Young Professor at the National University of Singapore, where he leads the Tay lab.
His team focuses on pioneering cancer immunotherapy and tissue repair techniques, utilizing biomaterials and
nanotechnology to harness the power of the immune system. He currently serves on Technology Networks’ Scientific
Advisory Board.
Reveal the power of
the 6-base genome
Introducing duet multiomics
solution evoC
Distinguish 5-methylcytosine (5mC) and
5-hydroxymethylcytosine (5hmC) together with all
4 canonical bases to measure multiple modes of
biology from a single low-input DNA sample in a
single experiment.
Identify novel multimodal biomarkers,
and predict gene expression, chromatin
accessibility, and enhancer state, to gain
transformative insights into current
and future states of disease.
Learn more at biomodal.com
5 TECHNOLOGYNETWORKS.COM
Tumor Heterogeneity: Navigating
the Next Frontier in Cancer
Research
Alison Halliday, PhD
Over the last decade, scientific discoveries have led to huge
strides in understanding how cancer develops, which has
ushered in a new era of precision medicine. Thanks to
these advances in treatment, overall cancer survival rates
are improving – but huge challenges remain. Some types of
cancer are still extremely challenging to successfully treat.
Once the disease has spread, it is very hard to cure.
In recent years, there has been an increasing awareness
that cancer is difficult to eradicate because it is so
complex and genetically diverse – and continually
adapts and evolves. Patients can initially respond well
to treatment, only for their disease to return, more
resistant and aggressive.
“We used to think of tumors as a collection of similar
cells growing out of control,” says Dr. Simone Zaccaria,
group leader of the computational cancer genomics lab
at University College London Cancer Institute. “But in
the last decade or so, we’ve come to realize that a tumor
is a much more heterogeneous ecosystem composed of
different cell subpopulations – or subclones.”
As a tumor grows, it accumulates new DNA mutations,
which can give rise to clusters of genetically distinct cells.
Each of these subclones may exhibit varying behaviors
– such as how quickly they grow, how well they respond
to treatment and their ability to spread. This diversity
between cancer cells within the same tumor – known as
intra-tumor heterogeneity – offers an explanation for why
some patients relapse.
“Under selective therapeutic pressure, drug-resistant cells
may evolve – either as a result of the expansion of pre-existing
resistant clones or plastic adaption,” explains Dr. Marco Bezzi,
group leader of the tumor functional heterogeneity team at
The Institute of Cancer Research, London.
Recent advances in computational and experimental
technologies are empowering researchers to study
individual tumor cells and track their evolution in
unprecedented detail. This is opening new opportunities to
understand why some treatments fail – offering potential
avenues to devise novel strategies to prevent or overcome
resistance to treatment.
Precision medicine
In recent decades, cancer medicine has evolved from
the traditional one-size-fits-all approach to an era of
precision medicine, where therapies are targeted to
specific characteristics driving the growth and spread of
an individual’s cancer. Researchers around the world are
Cancer Research
Credit: iStock
6 TECHNOLOGYNETWORKS.COM
Cancer Research
busy characterizing the molecular variations between
tumors – known as inter-tumor heterogeneity – to enable
the delivery of precision medicine to more patients.
But intra-tumor heterogeneity also has significant
implications for precision medicine.
Traditionally, the gold standard for molecular diagnostics
has involved sequencing a small sample of cells from
a single biopsy collected from one region of a tumor.
However, if the tumor is highly heterogeneous, this
tiny fraction of cells is unlikely to capture a fully
comprehensive picture of the disease. As a result, a
potentially effective therapy could be overlooked if a
certain molecular variation isn’t detected – or conversely,
an unsuitable drug may be selected based on identifying a
characteristic that isn’t that widespread within the tumor.
In addition, the molecular profile of a person’s cancer is
likely to change over time – and so treatments may need
to be adjusted accordingly.
Developing ways to accurately determine tumor
heterogeneity – and to track its evolution – is a major goal
for precision medicine.
Large-scale DNA sequencing
Historically, the ability to analyze the DNA of different
subclones within tumors has been restricted. But this is
now changing thanks to recent advances in sequencing
technologies, computational methodologies and access
to high-quality patient samples collected in large-scale
clinical studies.
High-throughput DNA sequencing of bulk tumor
samples is one of the most widely used techniques for
investigating genetic heterogeneity and deciphering the
evolutionary relationships among cancer cells. However,
interpreting these datasets can prove challenging as each
sample comprises a blend of thousands to millions of
different cells from various subclones.
“My lab focuses on the design and development of
computational methods to separate this mixed signal into
the individual components arising from each of these
subclones,” explains Zaccaria. “We also design algorithms
to investigate spatial heterogeneity from multiple bulk
tumor samples and reconstruct tumor phylogenetic trees
to describe the history of tumor evolution.”
The emergence of single-cell technologies presents
exciting new opportunities to study tumor evolution
with unparalleled resolution. One of Zaccaria’s goals
is to create computational methods that can analyze
these datasets, unveiling the evolutionary histories and
migration patterns of metastatic cancer cells.
“If we can find out which subclones have the ability to
metastasize, we will gain insights into the mechanisms
that enable these cells to disseminate,” he explains.
“We hope this knowledge can then be used to develop
new therapies – or therapeutic strategies – aimed at
preventing the spread of cancer cells to other parts of the
body.”
Zaccaria’s research relies on high-quality sequencing data
sourced from patient tumor samples – either collected
from multiple regions of a primary tumor, matched pairs of
primary and metastatic tumors or longitudinal samples. He
is part of a large-scale multidisciplinary consortium called
TRACERx –TRAcking Cancer Evolution through therapy
(Rx) – which aims to decipher evolutionary trajectories in
certain cancer types. He also examines data from samples
collected through the PEACE – Posthumous Evaluation
of Advanced Cancer Environment – study, which enables
the collection of multiple metastatic tumors posthumously
collected from patients.
A complex ecosystem
While genomic alterations in cancer cells drive some of
the functional differences among subclones, this is only
part of the story. Tumor cells don’t exist in isolation but
instead live within a complex ecosystem of immune cells,
stromal cells, the extracellular matrix, blood vessels and
many other factors. The tumor microenvironment can
significantly influence the behavior of individual cancer
cells, even those that are genetically identical.
“The diversity in the cancer ecosystem adds another level
of complexity to tumor heterogeneity,” explains Bezzi.
“For example, different tumors can have completely
different immunological profiles – and this can play an
important role in how they respond to treatments like
immunotherapies.”
Bezzi’s research is focused on deconstructing tumor
heterogeneity, evolution and drug resistance in prostate
cancer. “We can see differences in the genetic profiles of
patient tumors even at the early stages of the disease – and
over time, they acquire more and more genetic diversity,”
he says.
His laboratory work was previously limited to studying
prostate cancer cell lines grown in culture, as well as
genetically engineered mouse models. However, he
acknowledges these systems did not accurately reflect
the diversity of genetics and the complexity of the tumor
microenvironment found in human cancers. “While it’s
possible to discover important biological mechanisms
using these models, they may not apply to all tumors –
limiting the opportunities to translate discoveries into
wider patient benefits,” he says.
7 TECHNOLOGYNETWORKS.COM
Cancer Research
In response to this challenge, Bezzi is leveraging the
latest advances in cell culture technologies. He is aiming
to create a biobank of lab-based mini-tumors – or 3D
organoids – representing the diverse genetic profiles found
in prostate tumors. These mini-tumors exhibit many of the
features found in tumors in vivo, but are not possible to
recreate using standard 2D cell culture.
“If we can manage to do this at a reasonable scale, we are
likely to find commonalities among the different genetic
profiles,” says Bezzi. “Using this strategy, we hope any new
mechanisms we discover that are potentially targetable will
have a better chance of wider clinical relevance to more
patients.”
Bezzi’s team is using these organoids to carry out a variety
of ex vivo experiments – as well as transplanting them
into immunocompetent mice to study how they grow and
develop in the body and their interactions with the tumor
microenvironment. Additionally, they have developed a
barcoding system that enables them to follow individual
cells over time – for example, to understand how different
cells within a tumor are related to each other, or to track
how they move within the body.
Living with cancer: A new treatment paradigm
Cancer cells develop, adapt and evolve within a complex
interconnected ecosystem. Unraveling the complexities
of tumor heterogeneity and evolution holds the potential
to revolutionize treatment, leading to better long-term
outcomes for patients.
“Some cancers remain extremely challenging to treat, such
as those that have spread to other parts of the body or show
high rates of relapse,” says Bezzi. “In these cases, we need
to start thinking about cancer as a chronic disease that we
can control rather than eradicate.”
Implementing this paradigm shift will require
understanding and treating the tumor as an ecosystem,
leveraging the inherent competition between subclones.
“Cancer will continuously evolve whatever you throw at it,
so we need to reach a point where we can predict what will
happen next,” says Zaccaria. “If we can stay one step ahead
of the disease, we can then select the right treatment that
will keep it in check – and we may have patients who live
with cancer rather than die from it.”
About the interviewees:
Simone Zaccaria is group leader of the Computational Cancer
Genomics (CCG) laboratory at the UCL Cancer Institute. His
research focuses on the design and development of algorithms
and mathematical models to analyze tumor sequencing data for
understanding different cancer evolutionary processes.
Marco Bezzi leads the Tumor Functional Heterogeneity team at
The Institute of Cancer