13 markers on a flow panel should be good enough for anybody, right?

"My drug hits T cells, why look at B or NK cells?"

Answer: those cell types might be driving response, and that insight could be what gets your program to the next phase.

What you see and miss at each profiling depth

4-marker panel
Basic T cell check

What you see:

✓Basic T cell counts

What you miss:

✗Activation and proliferation profiling (e.g., HLA-DR, CD38, Ki-67)
✗Immunosuppressive and exhausted states (e.g., PD-1, TIGIT, LAG-3, CTLA-4)
✗Full myeloid and dendritic compartment (e.g., CD14, CD11c, CD123, cKit, CD33)
✗Regulatory T cells and γδ T cells (e.g., FoxP3, CD25, CD127, TCRγδ)

4 Markers: Parent populations only.

T cells
CD3
Helper T cells
CD4
Cytotoxic T cells
CD8
Leukocytes
CD45
Clinical impact:

Limited insight into immune responses. High risk of missing critical biomarkers that could predict treatment failure.

13-marker panel
Standard flow panel

What you see:

✓Naive vs memory T cell classification (e.g., CD45RA, CCR7)
✓Regulatory T cell detection (CD25, FOXP3, CD127)
✓Monocyte and NK cell profiling (CD14, CD56)

What you miss:

✗Checkpoint and exhaustion profiling (PD-1, TIM-3, TIGIT, CTLA-4)
✗Dendritic and rare myeloid populations (CD1c, CD123, CD141, CD11c, CD33)
✗Functional and proliferative states (Granzyme B, CD107a, Ki-67, T-bet, TCF1)
✗Tissue homing and chemokine receptor profiling (CXCR3, CCR5, CD69)

13 Markers: provide basic immune insights.

Example of a marker missed at lower resolution
Monocyte
CD14
Immunotherapy Relevance: The expression of CD14 can indicate the presence and activation state of monocytes, which can influence the effectiveness of immunotherapies. CD14+ monocytes can differentiate into dendritic cells and macrophages, essential for antigen presentation and initiation of immune responses.
Clinical impact:

Basic patient stratification possible. Can identify memory T cell subsets and regulatory populations, but lacks deeper MOA insights.

25-marker panel
Functional immune profiling

What you see:

✓Exhaustion and checkpoint markers (PD-1, TIM-3, LAG-3)
✓Dendritic and myeloid cell subsets
✓T-cell activation and memory profiling (CD45RA, CCR7)

What you miss:

✗Deeper checkpoint and suppression profiling (TIGIT, CTLA-4, PD-L1, FoxP3)
✗Functional and cytotoxic markers (Granzyme B, CD107a, Ki-67, T-bet, TCF1)
✗Rare or transitional immune subsets (e.g., Tregs, γδ T cells, LOX-1+ neutrophils)

25 Markers: reveal functional immune states.

Example of markers missed at lower resolution
Naïve T cells
CD45RA
Immunotherapy Relevance: Markers like CD45RA, CCR7, CD27 and CD28 allow you to find specialized T-cell subsets associated with better checkpoint inhibitor responses, like naive CD8 T-cell or high levels of memory CD4 T cells, particularly those with a Th1 phenotype.
Checkpoint Receptor
PD-1
Immunotherapy Relevance: PD-1 marks activated or exhausted T cells and is a direct target of checkpoint inhibitors like nivolumab. Its expression helps identify dysfunctional T cells in the tumor microenvironment and predict response to anti-PD-1 therapy.
Clinical impact:

Comprehensive immune profiling enables predictive biomarker identification. Can detect exhaustion pathways and activation states critical for immunotherapy success.

41-marker panel
Comprehensive immune profiling

What you see:

✓Exhaustion and checkpoint profiling (e.g., PD-1, TIM-3, LAG-3, CTLA-4)
✓Co-inhibitory checkpoint depth (e.g., TIGIT, PD-L1, CD86)
✓Cytotoxic function and transcriptional state (e.g., Granzyme B, Ki-67, T-bet, TCF1)
✓Chemokine receptor coverage (e.g., CXCR3, CCR5)
✓Full dendritic and myeloid resolution (e.g., CD141, CD123, LOX-1, FcεRI, cKit, CD33)
✓Regulatory and rare subsets (e.g., FoxP3+ Tregs, γδ T cells, CD161+ MAIT-like cells)

Comprehensive overview:

✓Exhaustion, activation, cytotoxicity, and tissue-residency, all covered

41 Markers: full immune insight, from exhaustion to cytotoxicity.

Example of a marker missed at lower resolution
Exhausted T cells
TIM3
Immunotherapy Relevance: Blocking TIM3 can stop T cells from getting tired and help those T cells to work better.
Clinical impact:

Complete immune landscape enables precision immunotherapy selection. Comprehensive biomarker panel for predicting response, resistance, and optimal combination strategies.

What this means for your trials

Case 1: Myeloid impact confirmed in healthy volunteer study

A $5B+ immunotherapy developer ran a 42-marker mass cytometry panel on 200 PBMC samples from 20 healthy volunteers in a Phase 1 trial.

  • Detected dose-associated changes in a myeloid subset linked to toxicity risk
  • Uncovered unexpected shifts in T cell subsets across timepoints
  • ~17X more resolution (858 vs. 52 subsets) compared to an 8-marker panel

Only detectable with 40+ marker profiling. These insights would've been missed with conventional flow.

Impact: Guided dose selection and validated MOA while revealing new immune dynamics.

Case 2: CD38⁺ exhausted T cells linked to ICB resistance

MGH and Teiko profiled blood from 85 melanoma patients on anti–PD-1 therapy, complementing tumor spheroid (PDOTS) data.

  • CD38⁺ CD8⁺ and CD4⁺ T cells were enriched in non-responders
  • Linked to disrupted NAD⁺ metabolism and T cell exhaustion
  • Supported use of CD38 blockade + NAD⁺ supplementation as a rescue strategy

Only visible with a 25+ marker panel capturing co-expression of exhaustion and metabolic markers.

Impact: Informed a targeted rescue approach by connecting blood-based immune features to resistance.

Stop wasting precious specimens

Unlock deeper immune insights by analyzing more markers, and ensure better patient stratification across your trial.

Want to get started? Drop us a message and we'll contact you with the details.

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