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Multiple processes in cancer are mediated by enzymes
.
High-fidelity enzyme activity analysis methods are essential
for understanding the pathological role of enzymes in cancer.
Researchers at MIT's Koch Institute for Integrative Cancer Research, recently published a study in Nature Communications, have developed a suite of enzyme-targeting nanotools that can monitor cancer progression and treatment response in real time, map enzyme activity to precise locations within tumors, and isolate relevant cell populations for analysis
.
background
The different processes of tumor progression depend not only on changes in the abundance of biomolecules, but also on changes
in the activity of biomolecules.
Therefore, methods to quantitatively track protein activity in the cellular, tissue, and living environment are critical
to advancing the understanding of cancer biology and designing the next generation of precision cancer drugs.
While the omics revolution has allowed us to perform high-throughput analyses of the genome, epigenome, transcriptome, and proteome, it has largely stopped exploring the level of protein activity—a unique regulatory axis that is often closest to the activated biological function
.
While single-cell transcriptomics allows us to determine intratumor heterogeneity, and in situ localization of proteins and nucleic acid sequence techniques are beginning to allow us to study tumors in a spatial context, similar techniques for spatial analysis of single cell and enzyme activity remain largely unexplored
.
Methods of analyzing enzyme activity at the organism, tissue, and cellular scales can yield new biological insights and open avenues
for the diagnosis and treatment of cancer.
In recent years, there has been a push to develop biosensors that can measure the activity of biomolecules in vivo, thereby generating synthetic signals
that can be read noninvasively.
For example, molecular sensors of nanoparticle and enzyme activity in vivo have enabled noninvasive detection of cancer, while active uptake of glucose has been used for functional imaging
of cancer metabolism.
However, this in vivo reading largely treats the body as a black box, sacrificing information for spatial localization within the tumor microenvironment (TME), making it impossible to resolve phenotypic heterogeneity at the single-cell level, reducing biological interpretation
.
Therefore, there is still a need for methods
that can generate and unify molecular activity measurements across biological scales.
Research highlights
The authors propose a comprehensive set of methods to analyze specific protease activity in cancer at the organismal, tissue, and cellular scales and apply these methods to study treatment response
in Alk-mutated lung cancer models.
Using multiplex protease-responsive nanosensors and machine learning, they analyzed the in vivo protease activity kinetics of a mouse model of Alk-mutated non-small cell lung cancer (NSCLC) in an in vivo environment, and found a significant dysregulation—enhanced cleavage of S1 peptide, and found that it quickly returned to healthy levels
after targeted treatment with ALK inhibitor arilatinib.
They established a multiplex assay for tissue spatial localization of protease activity of the target peptide substrate to determine that S1 cleavage occurs in tumor vessels
through direct tissue localization of protease activity.
To link protease activity to other measurement modes at the cellular scale, they designed an activity-based cell sorting that successfully isolated and characterized cells with proteolytic activity using peptide probes and flow cytometry to sort individual cells based on associated enzyme activity, revealing the proangiogenic phenotype
of S1 lysed cells.
Spatial and single-cell analysis links treatment-reactive activity characteristics to pericytes and endothelial cells in tumor angiogenesis, suggesting a dynamic cross-dialogue
between cancer cells and TME cells.
These methods for detecting protease activity across scales can generate rich functional data on the tumor microenvironment that can be translated into cancer diagnosis and treatment, providing a framework
for functional, multiscale characterization of protease dysregulation in cancer.
"We hope this new toolkit can be equally useful in the clinic as it is in the lab," said Sangeeta Bhatia, senior author
of the study.
"As further developments develop, clinicians can use nanosensors to tailor treatment to a patient's specific cancer and monitor cancer progression and treatment response, while researchers can use them to better understand the molecular biology of cancer and develop new tools to
diagnose, track, and treat disease.
"
Track tumors in real time
For several years, Bhatia's lab has been developing noninvasive urine tests to detect cancer, including colon, ovarian and lung cancers
.
This test relies on nanoparticles interacting
with tumor proteins called proteases.
Protease is an enzyme that acts like molecular scissors to cleave proteins and break them down into smaller components
.
Proteases help cancer cells escape tumors
by cutting off the extracellular protein network of fixed cells.
The surface of the nanoparticles is wrapped with peptides (short protein fragments)
that target cancer-associated proteases.
When the nanoparticles reach the tumor site, the peptides are cut off and release biomarkers that can be detected in the urine
.
In the current study, the researchers tested whether they could not only use this technique to detect cancer, but also accurately and sensitively track the development of cancer and its response
to treatment over time.
The team created a combination of 14 nanoparticles designed to target overexpressed proteases
in non-small cell lung cancer induced in mouse models.
When these nanoparticles encounter enzymes that regulate abnormally in the tumor microenvironment, they release barcoded polypeptides
.
Each nanosensor tracks different patterns of protease activity, which changes
significantly as the tumor progresses.
After using targeted drug therapy for lung cancer, the researchers were able to quickly detect signs of
tumor regression in as little as three days.
Cell atlas and populations
While existing nanosensor technology can be used to track tumor progression and general treatment response, it alone does not reveal specific cellular processes at work
.
"Like many tools that can be used to assess molecular markers of cancer, our urine reporter treats the human body as a black box," Kirkpatrick said
.
"While we got some information about disease states, we also wanted to learn more about the cells or proteins
that cause diseases to behave in specific ways.
"
After identifying the nanosensors of interest, the researchers mapped the active locations
of enzymes acting on these sensors in the tumor microenvironment.
They tuned the nanoprobes to leave fluorescent markers when separated from the nanosensors, assigning different labels
to different proteases.
After applying the nanoprobes to lung tissue samples, they looked for patterns
in how the tags were distributed.
One of the marks produced a strange spindle-like pattern that turned out to belong to the tumor's vascular system
.
The researchers localized protease activity to specific types of cells: vascular endothelial cells, which are responsible for vascular arrangement, and pericytes, which regulate vascular function and are actively recruited in angiogenesis, one of the classic hallmarks of
cancer cell growth.
Angiogenesis allows tumor cells to absorb existing blood vessels and stimulate the formation of new blood vessels to obtain the nutrients needed for tumor formation and development
.
Using nanoprobes to label and classify cells based on their enzyme activity, the team identified populations associated with the vascular system that exhibit high expression
of genes associated with angiogenesis.
The researchers also found evidence of signaling between pericytes and endothelial cells, which together make up angiogenic vessels
in vascular tissue.
Observation of signs
In future work, the team will attempt to identify specific proteases active in pericytes and analyze their role in
angiogenesis.
Armed with this knowledge, they hope to develop a formulation of a therapy that can be offered to patients, disrupting the recruitment and formation
of blood vessels associated with tumor growth.
Ultimately, the team hopes to noninvasively monitor multiple important features
of cancer patients simultaneously with a combination of nanoprobes.
Other features of cancer include proliferation signals, avoidance of growth inhibitors, genomic instability, resistance to cell death, metabolic dysregulation, and activation
of invasion and metastasis.
Because cancer alters protease activity in all of these processes, the team's nanoprobes can be designed to target these different processes, with the goal of providing a comprehensive picture
of the disease driven by tumor activity.
The approach will help
researchers studying key biological phenomena in cancer models, as well as clinicians seeking non-invasive monitoring of cancer progression and choosing treatments for patients.