The advent of liquid biopsy technologies has revolutionized our ability to monitor disease progression and treatment response non-invasively. Mass cytometry, with its high-dimensional capabilities, has emerged as a powerful tool in this field, offering unprecedented insights into circulating biomarkers. This chapter explores the application of mass cytometry to liquid biopsies, focusing on circulating tumor cells (CTCs), cell-free DNA, and extracellular vesicles.
Mass Cytometry Analysis of Circulating Tumor Cells
Circulating tumor cells provide a window into the molecular characteristics of tumors without the need for invasive tissue biopsies. Mass cytometry has significantly enhanced our ability to characterize these rare cells.
Gerdtsson et al. (2018) demonstrated the power of imaging mass cytometry (IMC) for multiplex protein detection on CTCs in their groundbreaking study published in Convergent Science Physical Oncology. They developed a method to simultaneously analyze 16 protein markers on individual CTCs, providing a comprehensive view of tumor cell heterogeneity in liquid biopsies. Intriguingly, this study used imaging mass cytometry to study liquid biopsies.
More recently, a study written by Payne et al. in Nature (2023) demonstrates the “feasibility of using mass cytometry to analyze circulating tumor cells (CTCs) from head and neck squamous cell carcinoma (HNSCC)” patients, enriched using the Parsortix microfluidic platform. CTCs were detected in 13 out of 14 HNSCC patients, with counts ranging from 2-24 CTCs/ml of blood. Using a 41-marker antibody panel, the researchers identified three main CTC subgroups: epithelial, early EMT, and advanced EMT, each with distinct phenotypic and signaling characteristics. Notably, the EMT status in CTCs did not correlate with the EMT profile of the primary tumor, suggesting independent adaptation of CTCs in circulation. Mass cytometry analysis outperformed bulk RNA sequencing in detecting CTCs and characterizing their phenotypes, revealing intra-patient heterogeneity that was not apparent in bulk analysis. This method provides a platform for high-dimensional proteomic characterization of CTCs at single-cell resolution, potentially enabling novel biomarker development and treatment stratification in HNSCC.
Profiling Cell-free DNA and Extracellular Vesicles
While mass cytometry is primarily used for cellular analysis, recent developments have expanded its application to cell-free DNA (cfDNA) and extracellular vesicles (EVs).
Cell-free DNA (cfDNA) and extracellular vesicles (EVs) are naturally present in the body of all individuals, including those without cancer. cfDNA results from normal cell turnover, while EVs are produced by cells for communication. However, in cancer patients, these components take on special significance. Cancer cells often release more cfDNA due to increased cell death and produce EVs with altered content. The key to using cfDNA and EVs in cancer diagnostics isn’t just detecting their presence, but rather identifying cancer-specific characteristics within them. This includes looking for elevated levels compared to healthy individuals, detecting specific genetic mutations associated with cancer, and monitoring changes in their composition over time. The challenge for researchers and clinicians is to develop sensitive and specific methods that can distinguish cancer-related molecules from the background of naturally occurring cfDNA and EVs. This approach allows for non-invasive monitoring of cancer progression and treatment response, potentially revolutionizing cancer care by providing valuable information without the need for repeated invasive biopsies.
Mass cytometry is typically used for analyzing cellular proteins, not cfDNA or EVs directly, but it some scientists might find a trick to go further in this area. However, single cell RNA sequencng is apropriate and several studies have already been published, as shown a review “Single-cell analysis of circulating tumour cells: enabling technologies and clinical applications”, by Radfar et al. in Trends in Biotechnology (2022).
Non-invasive Monitoring of Disease Progression
The application of mass cytometry to liquid biopsies has opened new avenues for non-invasive disease monitoring.
A landmark study by Krieg et al. (2019) in Nature Medicine, “High-dimensional single-cell analysis predicts response to anti-PD-1 immunotherapy”, demonstrated how single cell analysis of peripheral blood immune cells could predict response to immunotherapy in melanoma patients. This work highlighted the potential of liquid biopsies for personalized treatment selection.
Clinical Impact and Future Directions
The integration of mass cytometry with liquid biopsy technologies is transforming our approach to cancer diagnosis, monitoring, and treatment selection. These advances are bringing us closer to truly personalized medicine, where treatment decisions can be guided by real-time, comprehensive analysis of circulating biomarkers.
For instance, in a clinical setting, a patient with metastatic breast cancer might undergo regular liquid biopsies analyzed by mass cytometry. The high-dimensional profiling of CTCs could reveal the emergence of treatment-resistant cell populations before they become apparent on imaging studies, allowing for timely adjustments to therapy.
Moreover, the ability to simultaneously analyze multiple circulating biomarkers (CTCs, cfDNA, and EVs) provides a more complete picture of disease status. This multi-pronged approach could improve early detection of cancer recurrence and offer more accurate prognostic information.
As we continue to refine these technologies and develop new computational tools for data analysis, we are uncovering the wealth of information carried in our bloodstream. Each liquid biopsy becomes a snapshot of the body’s current state, telling a story of health and disease at a molecular level.
The field of liquid biopsies, enhanced by the power of mass cytometry, stands at the forefront of a new era in precision oncology. As we decode the messages carried by circulating biomarkers, we move closer to a future where cancer can be detected earlier, monitored more accurately, and treated more effectively. This journey of discovery, mapping the molecular landscapes of disease through a simple blood draw, is transforming our approach to cancer care, promising a future where treatments are truly personalized and guided by the most up-to-date information about each patient’s unique disease state.
Predicting the future isn't just for fortune tellers anymore - we're doing it with immunotherapy responses! Our journey into this crystal ball of cancer treatment started with our paper, "PD-L1 blockade engages tumor-infiltrating lymphocytes to co-express targetable activating and inhibitory receptors" (Beyrend et al., 2019, Journal for ImmunoTherapy of Cancer). Figure 3 in this paper was our first glimpse into the time machine, identifying T cell subsets that could predict immunotherapy responses. But we didn't stop there. Our recent paper, "OX40 agonism enhances PD-L1 checkpoint blockade by shifting the cytotoxic T cell differentiation spectrum" (Beyrend et al., 2023, Cell Reports Medicine), took this predictive power to the next level. We showed how combining OX40 agonism with PD-L1 blockade could reshape the T cell landscape, potentially improving treatment outcomes. Connecting these findings to liquid biopsies was like hitting the jackpot in the cellular casino. Suddenly, we could peek at these predictive cells with just a blood draw, potentially foreseeing treatment outcomes before they happen. Deciphering these cellular tea leaves wasn't easy. Many late nights were spent staring at flow cytometry plots, wondering if we were seeing patterns or just blurry dots. But when it all came together, it was like finally solving a Rubik's cube blindfolded. This work reminded me that in the world of cancer immunotherapy, sometimes the best way to fight is to listen closely to what the cells are telling us, and sometimes, to give them a little nudge in the right direction. They have stories to tell - we just need to learn how to hear them and how to help them write a better ending
