The human immune system can identify and eliminate billions of pathogens and maintain surveillance against emerging threats. Yet, cancer cells often evade this defense system, growing unchecked despite being recognized as abnormal.
This is done through immune checkpoints, molecular conversations between immune cells and their targets that act as regulatory brakes. Cancer cells hijack these conversations, telling immune cells to stand down. Understanding checkpoint interactions has revolutionized cancer treatment, but a critical challenge has limited its success: researchers often don’t know which cellular conversations are actually taking place within individual tumors or how to map them at scale.
How Checkpoints Work
Immune checkpoints operate through receptor-ligand interactions. The most studied one involves PD-1 on T cells and PD-L1 on target cells. When PD-1 binds to PD-L1, it reduces T cell activation and cytokine production, protecting against autoimmunity in healthy tissue. Another checkpoint, CTLA-4, is upregulated following T cell receptor stimulation. These regulatory mechanisms are essential for immune balance, but cancer exploits them for immune escape.
When Cancer Hijacks the Conversation
However, many tumors upregulate PD-L1 expression, creating a molecular disguise that tells T cells to stand down. The result is immune exhaustion, and T cells become functionally impaired, unable to eliminate cancer. This explains why high immune infiltration doesn’t guarantee better outcomes. The function of T cells matters more than their mere presence.
Checkpoint Inhibitor Therapy and Its Limits
Checkpoint inhibitors block these inhibitory conversations. Antibodies targeting checkpoints release the brakes on T cell responses, transforming outcomes in melanoma, lung cancer, and other malignancies.
However, response rates vary significantly. Not all tumors respond to checkpoint blockade. Some tumors lack T cell infiltration, meaning blocking checkpoints has nothing to activate. When PD-1 is blocked, cancer cells may upregulate alternative checkpoints like TIM-3, LAG-3, or TIGIT, maintaining exhaustion through different pathways.
This adaptive resistance highlights a critical need: observing multiple checkpoint interactions simultaneously. Understanding response or resistance requires seeing the full landscape of cellular conversations at high-plex to get the full picture.
Why High-Plex Matters
Most researchers today infer checkpoint interactions indirectly through RNA sequencing or protein co-staining—methods that can’t directly confirm whether receptor-ligand pairs are actually engaged. A tumor may simultaneously engage in PD-1, LAG-3, and TIM-3 interactions, but without direct visualization of these molecular conversations, researchers are essentially predicting which checkpoints are active. Mapping multiple checkpoint interactions directly in tissue reveals these networks and shows how they change during treatment.
Mapping Multiple Conversations
At Moleculent, we’re developing tools to directly decode these cellular conversations automatically, mapping a multitude of checkpoint interactions simultaneously in their spatial context. This reveals patterns that predict therapeutic response and resistance—patterns invisible to indirect methods.
Our high-plex approach is essential as checkpoints form complex networks. A tumor expressing PD-L1 might also express LAG-3 or TIM-3 ligands, making PD-1 blockade alone insufficient. Mapping which cellular interactions are present reveals the underlying tumor biology that drives immune evasion and treatment resistance.