The power of RNA and multi-omic analysis in drug development
What is single-cell sequencing?
Single-cell sequencing leverages cellular barcodes and next-generation sequencing to reveal high-definition expression data across thousands of individual cells from complex biological samples. The resulting large-scale transcriptomic and proteomic data enable researchers to:
- Subset rare or diseased cell types to an unprecedented level of detail
- Reveal differences in dynamic cell states across subjects, time points, or treatment conditions
- Discover new cellular features that can serve as predictive biomarkers in the clinic
CellCarta is a Certified Service Provider on the 10X Genomics Chromium X platform and a member of 10X Genomics’ Global CRO program.
The Chromium platform provides multiple types of omics readouts for a better understanding of drug mechanism and patient responses throughout the stages of drug development. CellCarta performs the following types of single cell sequencing:
| RNA whole transcriptome | Proteins 100+ antibody panels | TCR and/or BCR clonality & repertoire |
|
|---|---|---|---|
| scRNA-seq single cell RNA sequencing | ✅ | ||
| CITE-seq Cellular Indexing of Transcriptomes and Epitopes sequencing | ✅ | ✅ | |
| Repertoire profiling | ✅ | ✅ | |
| Immune profiling | ✅ | ✅ | ✅ |
When can single-cell sequencing be used in drug development?
The high resolution of single-cell sequencing provides features that can be missed by lower plex single-cell platforms such as flow cytometry, or non-single-cell methods such as bulk RNAseq. Deep single-cell datasets are primarily useful in the discovery and exploratory research phases of development.
Discovery
- Characterize potency and detailed off-target activity of drug candidates in diverse cell types to guide lead selection
- Uncover novel biomarkers that can be tested in upcoming pre-clinical and clinical trials
Pre-clinical animal studies
- Measure detailed pharmacodynamic effects of drug candidates in vivo for the first time
- Prioritize the most promising biomarkers to carry forward into human clinical studies
Early clinical studies
- Measure pharmacodynamics in humans to confirm dose-dependent mechanism of action
- Develop patient selection or stratification hypotheses by identifying biomarkers that predict response to the therapeutic
- Inform which biomarkers should be deployed using simpler and more scalable platforms for late stage clinical studies.
Reverse translation
- Retrospective analysis to identify patient sub-groups that might have responded differently to the therapeutic based on their molecular profiles
- Improve the understanding of disease by profiling patient samples and identifying novel disease subtypes
What applications can benefit from single-cell RNA sequencing?
Single-cell sequencing finds applications in a broad range of therapeutic fields. Here are some examples:
| Immunotherapy: | checkpoint inhibitors, cell therapy, engineered cytokines, T cell engagers, T cell activators. Single-cell sequencing characterizes the many different immune cell types in blood, scanning for signs that the treatment induced or blocked meaningful aspects of an immune response. |
| Cell Therapy: | CAR-T, TCR-T, CAR-NK, CAR-macrophage. Provides insight into patient responses to cell therapy by mapping features that relate to a patient’s immune cells, the manufactured cell product before infusion and the functional state of the cell product over time post-infusion. |
| Protein Degrader | PROTACS, molecular glues, ADC degraders. Casts a wide mechanistic net to differentiate conventional inhibitors of protein functions from degraders that affect both function and scaffolding. |
| Vaccines: | infectious diseases, cancer, tolerizing for autoimmunity and allergy. Details the cellular immune response, informs vaccines response durability, helps compare multiples vaccine types targeting the same pathogens, and detects bystander immune cell activation, |
What single-cell sequencing services do CellCarta offer?
Sample types
CellCarta supports the handling and analysis of various sample types from assay validation through sample analysis. Cryopreserved PBMCs are the most common samples to work with, however lysed whole blood, fresh PBMCs, cell lines, and fixed samples can also be analyzed.
Chromium X workflows
At CellCarta, we use the Chromium X platform to deliver advanced genomic insights on samples through the following workflows:
- 5’ Single Cell Immune Profiling. Provides whole transcriptome data (scRNA-seq) on up to about 29,000 genes including non-coding RNA. Detection of protein markers (CITE-seq) can be added to the workflow, which also enables sample multiplexing by hashtag. TCR and BCR repertoire sequencing can be added to the workflow to study immune repertoire diversity and clonal frequencies. Antigen mapping can be performed to understand the specificity of T cells and B cells (pilot testing required).
- 3’ Single Cell Gene Expression. Provides whole transcriptome data with the option to add protein expression data. Results are similar to those from the 5’ workflow, and we typically recommend using 5’ for new projects.
- Flex Fixed RNA Profiling. Provides the most sensitive and cost-effective option for whole transcriptome analysis using RNA probes. Up to about 19,000 genes detected. Offers integrated sample multiplexing. Compatible with fixed cells and FFPE tissue, enabling batching of samples fixed at multiple sites or on different days. Detection of protein markers can be added to the workflow. Not compatible with TCR/BCR repertoire sequencing.
A typical workflow generates data on 10,000 cells per sample but can be customized (up or down) to meet the needs of each study. Sequencing read depth can also be tailored based on the need to detect low abundance transcripts.
All single-cell RNA sequencing assays can be supported with several upstream immunology services, including:
- Cell culture
- Compound treatment
- FACS-based cell sorting
- Magnetic enrichment
- Dead cell removal
How does CellCarta deliver data from single-cell sequencing studies?
At CellCarta, we prioritize an immunology-first approach to data analysis. We utilize our cloud-based CellEngine software, to mirror a traditional flow cytometry analysis. This allows immunologists to analyze data using familiar, interactive visualization tools. Researchers can use population gating guided by tSNE and UMAP clustering to identify cell types, then visualize individual genes, proteins, or gene signature scores on a per-cell basis using histograms, dot plots, and contour plots. They can perform secondary analysis using bar charts, line graphs, and heatmaps to look across patients, time points, or treatment conditions.
In addition to the interactive report created in CellEngine, CellCarta can provide a range of study deliverables:
- Raw FASTQ files
- Summary QC report
- 10X cell ranger outputs (web summary, Loupe, and H5 files)
- Slide decks
- Written reports
Custom bioinformatics services are also available.
Our experts can help you tailor your single-cell sequencing approaches to generate the most relevant and actionable insights at each stage of the drug development process.
Contact us today to discuss how we can support your research goals and accelerate the development of more effective personalized therapies.