Plotting the Next Move in Immuno-Oncology
Immuno-oncology (I-O) has changed our approach to cancer treatment by harnessing the body’s immune system to fight back. However, cancer has one big advantage: its evolutionary brakes are off, whereas the immune system must play by the rules. This has led to a cat-and-mouse game where cancer cells keep popping back up, inventing new ways to outmaneuver immuno-oncology therapies.
This article is posted on our Science Snippets Blog
A Moving Target
The immune system responds to invaders by creating a hostile environment, directing an army of immune soldiers to isolate, remove and destroy the threat, be it a virus or malignant cells. When faced with selective pressure, tumor cells rely on random mutations to gain fitness and survive. Sometimes the opposite strategy works; the tumor has too few mutations and is mistaken for a normal cell. In the end, the immune system often loses because it just can’t keep up.
I-O therapies work by blocking or stimulating specific pathways to give the immune system the upper hand. Immune checkpoints, for example, normally act to keep the immune system from going into overdrive. Cancer cells have learned to hack this process for their own protection. Checkpoint inhibitors targeting the programmed cell death protein 1 (PD-1) and cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) pathways are two examples where I-O strategies are successfully used to reactivate T-cell function against breast, cervical, lung and other cancers.
Unfortunately, many patients do not benefit from I-O therapies. Active research in the area aims to understand the interplay between immune systems and tumor biology to address this problem.
Meet the Resistance
Cancer resistance to I-O therapies is the most important challenge in the field today. Patients with primary resistance do not respond to I-O therapies. For instance, blocking the interaction between PD-1 and its ligand PDL-1 is an effective immunotherapy strategy for many tumors, but most patients have primary resistance to PDL-1 blockade. Of those without primary resistance, only 30-40% have an objective response.
Primary resistance can result from tumor intrinsic and tumor extrinsic factors. Tumor intrinsic factors are due to the biology of the tumor itself, while tumor extrinsic factors are related to the biology of the immune system:
- Tumor does not produce a specific antigen
- Tumor produces the antigen but doesn’t present it on the cell surface
- Tumor has mechanisms that shun T-cells or allow it to hide from T-cells
- Absence of T-cells that target tumor-specific antigens
- Presence of immunosuppressive cells
- Presence of inhibitory checkpoints
Patients with acquired resistance initially respond well to I-O therapies but regress over time, as seen in 25% of anti-PD-1 recipients. Some of the mechanisms behind acquired resistance mimic those of primary resistance:
- Loss of T-cell function
- Tumor downregulates antigen presentation, allowing it to hide from T-cells
- Tumor develops escape mutation variants
The Art of War
Investigating the drivers of resistance mechanisms will help bring the benefits of I-O therapies to more cancer patients. New research trends in I-O are shifting from static assays to dynamic, information-rich methods of analysis. Live-cell analysis is a powerful tool for these studies because it allows scientists to visualize and quantify complex cell biology over time and in a physiologically relevant way.
For instance, in a study looking at the role of PD-L1 expression by the tumor and immune cells in suppressing anti-tumor immune activity, the authors used the Incucyte® Live-Cell Analysis System to continuously monitor cell growth over a one-week period (Lau and Cheung 2017).
Here at Sartorius, our scientists have used Incucyte® Assays to quantify changes in cell surface checkpoint proteins in living breast cancer cells. In this study, they treated breast cancer cells with interferon gamma (IFN-γ) and monitored PD-L1 levels over 72 hours (Figure 1). At the highest concentrations of IFN-γ (50 ng/mL), they measured a threefold increase in PD-L1 labeling (~ 5 µm2/well) compared to vehicle control (~1.8 µm2/well).
The Incucyte® Live-Cell Imaging and Analysis System has a wide range of applications in I-O research, from simple cell health assays to co-culture assays for cell killing. One of its greatest benefits is that the system is non-destructive to cells. It can collect real-time phenotypic and kinetic data on cell health, morphology and function around the clock, directly from the culture hood.
Figure 1. Live-cell analysis of checkpoint dynamics on the Incucyte System.
FabFluor-488 was conjugated to anti-PD-L1 Ab (BioLegend) and added to MDA-MB-231 NucLight Red breast cancer cells in the absence and presence of IFNγ (+Incucyte Opti-Green background suppressor). Cell growth rate was consistent during this study.
Think Two Steps Ahead
In vitro cell-based assays will play a vital role in ongoing efforts to understand how immune-cell signaling pathways are regulated in tumors. Real-time live-cell analysis technologies, like the Incucyte® Live-Cell Analysis System, capture nuanced time-dependent and cell-specific changes in biology and help drive progress in every stage from basic research and drug screening to lead optimization and quality control (QC) manufacturing.
New artificial intelligence (AI) tools are also making an impact by enabling high-throughput analysis of cell images across disciplines, including oncology. A recent study published in the journal Nature Methods described LIVECell, a deep-learning dataset for label-free, quantitative segmentation of live cell images (Edlund 2021). Incidentally, this dataset was also developed using the Incucyte® System, because it can capture a large volume of high-quality images.
Conventional microscopy and cell analysis techniques have brought us this far. The future of immuno-oncology medicines will rely on data-rich tools that can reveal the deep interconnected networks that exist between cancer and immune cells.