A newly developed single-cell sequencing approach, dubbed CIPHER-Seq, is designed to capture a more complete picture of immune cell behavior—an advance that could sharpen how researchers study responses to immunotherapy and mechanisms of resistance. The technique is described in a paper in Nature Scientific Reports.
Co-senior investigator Justin Taylor, MD, from the Sylvester Comprehensive Cancer Center at the University of Miami described the method as an effort to bridge a longstanding gap in single-cell analysis: the inability to simultaneously measure intracellular immune activity alongside gene expression and surface markers in the same cells.
“The main difference…is we’re trying to also look at the intracellular proteins,” Taylor said. “A lot of current approaches can measure proteins on the surface of the cell and RNA, but they can’t go inside the cell without disrupting the RNA.”
That limitation has been particularly consequential in immuno-oncology, where understanding immune cell function—especially cytokine production—is critical. Cytokines, which are typically secreted outside the cell, are central to defining T cell activation states and functional subtypes, but are difficult to capture alongside RNA using standard workflows.
CIPHER-Seq, or Cytokine Intracellular Protein High‑throughput Expression with RNA sequencing, addresses this by introducing a carefully optimized permeabilization step that allows antibodies to enter the cell without degrading RNA. At the same time, the protocol uses the Golgi stop reagent to trap cytokines inside cells, enabling their measurement.
“So instead of just what type of cell,” Taylor explained, “you can ask how they’re activated—are they secreting cytokines?”
Five layers of data in a single assay
The platform integrates five distinct data layers: cell surface markers, RNA sequencing, intracellular proteins, cytokines, and sample multiplexing via hashing antibodies. This multiomic approach builds on earlier technologies such as CITE-seq but extends them into intracellular territory.
Technically, the method relies on commercially available reagents and widely used sequencing platforms. Antibodies from multiple vendors can be used, and no proprietary components are required—an intentional design choice to encourage adoption.
“We’re not trying to sell it,” Taylor said. “There’s nothing proprietary about the protocol…you can buy all the reagents separately. It’s really about how we put them together and optimize the timing.”
Timing, in fact, proved critical during development. Excessive permeabilization can degrade RNA or induce cellular stress, while insufficient exposure prevents antibodies from entering the cell. The team iteratively optimized these conditions to preserve both RNA integrity and intracellular protein detection.
Reducing technical artifacts
Beyond enabling new measurements, CIPHER-Seq may also improve data quality by reducing technical artifacts. In benchmarking experiments using identical donor samples, the researchers observed that standard single-cell workflows induced higher levels of stress-related gene expression—signals that could be mistakenly attributed to biological processes.
“When we compared CIPHER-Seq to other methods…we found less stress,” Taylor said. “The same sample, same donor—just different processing. The other assays showed higher mitochondrial and metabolic stress markers.”
This finding has particular relevance for cancer studies, where cellular stress is often interpreted as a hallmark of disease or treatment response. If assay-induced stress is not accounted for, it could confound conclusions about tumor biology or immune activation.
“If you’re doing research on cancer patients getting immunotherapy, and one of your readouts is stress on the T cells,” Taylor added, “you might attribute that to the cancer—but maybe that’s from your technique.”
Applications in immuno-oncology
The primary envisioned applications for CIPHER-Seq lie in immuno-oncology, including studies of checkpoint inhibitors, CAR T-cell therapies, and bispecific antibodies. By enabling detailed profiling of T-cell subsets based on cytokine production, the method could help clarify how immune cells behave in different therapeutic contexts.
One potential use case, not yet demonstrated in the current study, would involve analyzing peripheral blood samples from patients before and after immunotherapy to compare immune activation states between responders and non-responders.
“That would be kind of the ideal use case,” Taylor said. “You could compare T cells in responders versus non-responders, or look at patients who develop resistance.”
Such analyses could ultimately help identify biomarkers of response or resistance, informing the development of targeted interventions.
“The whole point is to try to improve outcomes for patients,” he said. “If you can identify a resistant T cell marker, then you might develop a treatment targeting that.”
Why single-cell resolution matters
A key rationale for the approach is the need to detect rare immune cell populations that may drive treatment outcomes. Bulk sequencing methods average signals across many cells, potentially masking critical subsets.
“When you do bulk sequencing, it’s a mixture of all the cells,” Taylor noted. “You might miss rare subsets—and for immunotherapy, those rare cells might be very important.”
Path to clinical translation
While CIPHER-Seq is currently positioned as a research tool, Taylor sees a plausible path toward clinical application, drawing parallels to earlier sequencing technologies that were once considered impractical.
“When I started, people said whole genome sequencing would never work in patients,” he said. “And the same for RNA sequencing—that it was too unstable. But now both are routine.”
He anticipates similar skepticism around single-cell approaches but believes those barriers may also fall.
“Right now, people might say single-cell sequencing is too expensive or too technical,” Taylor said. “But I think that will change.”
For now, the team’s priority is encouraging adoption within the research community. By publishing the full protocol and relying on accessible reagents, they hope other groups will apply, refine, and extend the method.
“Our hope is that people start using it,” Taylor said. “Maybe they optimize it further for their own applications.”
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