One of the major issues that researchers have confronted during oncology drugs development is the variability of drug efficacy and side effects between patients. Specifically, most clinical trials just result in a 3-5% success rate. Improved strategies for pre-clinical research aimed at identifying biomarkers and drug targets could help boost this sobering number. Conventional methods, including flow cytometry and mass cytometry as well as bulk RNA sequencing all have some limitations such as  constraining its use with only canonical gene markers or masking the heterogeneity of tumor microenvironment (TME) by averaging gene expression levels across cells.

Chromium Single Cell Immune profiling allows simultaneous analysis of T-cell receptor (TCR) sequences and gene expression profiles from the same individual cells, enabling researchers to measure clonal expansion and identify often overlooked immune cells in the tumor microenvironment. Remarkably, in this blog, we will highlight three additional studies that use our technology to:

• Standardize single cell analysis of frozen patient samples
• Increase the efficacy of tumor-infiltrating lymphocyte (TIL) therapy
• Expand treatment options for acute myeloid leukemia

The nucleus may hold the key to clinical insights in cancer

Single cell immune profiling has revolutionized our understanding of cancer heterogeneity. However, in the context of clinical trials, it can bring several difficulties to apply on patient samples. Typically, such analyses require large, fresh tissue samples, yet patient samples are often small, and immediate tissue processing for downstream profiling is essential, rendering standardized multicenter studies nearly impossible. Consequently, researchers often resort to analyzing small patient cohorts, limiting the ability to draw statistically significant conclusions applicable to a broader patient population. While nuclei isolation circumvents the issue of fresh tissue samples, single nuclei RNA sequencing (snRNA-seq) restricts the information obtained from single cell analyses. Utilizing whole cells as input enables the analysis of both whole transcriptome gene expression data and paired, full-length V(D)J transcript data, which is crucial for T-cell and B-cell receptor (BCR) analysis. However, TCR and BCR transcripts, even in immune cells, are typically expressed at low levels, worsening the issue in clinical settings where tissue samples are scarce.

Researchers from Columbia University recently reported in Nature Genetics that they captured the whole transcriptome and paired full-length TCR transcripts from snRNA-seq analysis of small, frozen tissue samples—such as core needle biopsies—routinely collected during clinical trials (3).

Figure 1. A Circos plot representing the results of matched T-cell receptor sequencing collected on a patient undergoing anti-PD1 therapy. Colors indicate time of collection (blue: pre-treatment, orange: on treatment, green: on-later), and connections indicate overlap of identical TCRs. These results demonstrate a striking diversification of T-cell clonotypes over time. CREDIT: Yiping Wang/CUIMC

When performing experiments to compare the two methods, analysis with snRNA-seq using either 3’ or 5’ chemistry of frozen tissue did not only draw comparable results to but sometimes also outperformed that of tissue-matched scRNA-seq of fresh tissue, 23% of cancer cells and up to 93%, respectively.

Researchers conducted a study to assess the effectiveness of single-nucleus RNA sequencing (snRNA-seq) using 5’ chemistry to evaluate changes in cellular composition of frozen biopsy samples derived from a clinical trial participant treated with pembrolizumab (anti-PD1 antibody MK-3475). They compared pre- and post-treatment samples and identified changing transcriptional profiles, including a population of cancer cells with a signature indicative of immunotherapy resistance post-treatment. Increased immune infiltration, with various T cell subtypes, was observed in post-treatment tumors. Additionally, they analyzed samples from a multicenter clinical trial testing the MEK inhibitor selumetinib, and discovered diverse cell populations with expected transcriptional signatures. The researchers are optimistic their snRNA-seq/TCR-seq method will prompt other clinical researchers’ interest in addressing questions about immuno-oncology. Particularly, the ability to work from frozen samples facilitate multi-institutional collaborations that will promote the discovery of biomarkers and drug targets. Besides, since this method only uses a small amount of tissue, the surplus may be retained for further studies, which is a win-win for researchers, clinicians, and, most importantly, our patients.

Turning tumor cells against themselves

Tumor infiltrating lymphocytes (TILs) therapy is a therapy in which T cells are isolated from patients’ tumor cells and in vitro cultured before transferring back into patients without the need to be genetically modified as opposed to CAR T cells. Although TIL therapy is just only in its nascent stage and has limited access for patients only via clinical trials, it has shown its potential to effectively treat melanoma, ovarian cancer, and NSCLC patients (5). Besides, combination therapy between TILs and immune checkpoint inhibitors such as the anti-PD1 drug nivolumab is applied in the hope of enhancing efficacy. However, one of the major challenges of this therapy is TILs often aren’t fully active and are eliminated long before they’ve left a lasting impact on the tumor. Researchers are working to modify and expand TILs before they deliver them back into patients by increasing their activity, amplifying their diversity, and upping their numbers.

In 2022, researchers detailed a unique strategy to increase the efficacy of TIL therapy in Molecular Therapy (5). They infected patient tumor cells with a herpes simplex virus 1 (HSV1)-based oncolytic-virus-encoding effector T-cell regulator OX40L and cytokine IL12 to transform the cells into antigen-presenting cells (APCs)—whose primary function is to activate T cells. When they treated patient-derived xenograft and syngeneic mouse tumor models with both the oncolytic virus and TILs, the tumor regressed.

Figure 2. Tumor cells transform into APCs through oncolytic-virus-mediated expression of OX40L and IL12 in tumor cells. The APCs go on to activate tumor-specific T cells. CREDIT: Ye K, et al. An armed oncolytic virus enhances the efficacy of tumor-infiltrating lymphocyte therapy by converting tumors to artificial antigen-presenting cells in situ. Mol Ther 30: 3658–3676 (2022), (CC BY 4.0).

The authors infected primary oral cancer cells isolated from four patients with oncolytic virus and validated their transformation into APCs by co-culture with TILs isolated from the corresponding patient. They confirmed that the tumor cells expressed T-cell binding receptors normally found on APCs, including CD80 and CD86, using quantitative real-time PCR and flow cytometry.

They also used the Chromium Single Cell Immune Profiling kit to conduct scRNA-seq and scTCR-seq and capture a full picture of the TCR repertoire and transcriptome of TILs cocultured with mock- or oncolytic-virus-infected tumor cells. After molecular deconvolution of TCR clonotypes and their corresponding activation status, they confirmed that tumor cells infected with oncolytic viruses contained more activated TILs. Notably, IFN-γ-positive T cells or active T cells were two- to three-fold higher in oncolytic-virus-infected tumor cells than mock-virus-infected tumor cells.

This new oncolytic-virus/TIL combination therapy is a promising candidate for a future clinical trial, especially considering the growing excitement around cancer vaccines. In fact, the backbone of the oncolytic virus used in this study contains the same backbone as T-Vec and teserpaturev, which have been approved for the treatment of melanoma and glioma, respectively (5).

Targeting tumors with a patient’s own T cells

Allogeneic stem cell therapy, the sole curative treatment for acute myeloid leukemia (AML), confronts challenges due to donor matching difficulties and patient comorbidities. Researchers explore alternatives, like harnessing patients’ own T cells against AML. However, PD-1 inhibitors, effective in solid tumors, disappoint in AML. MD Anderson researchers investigate biomarkers of response or resistance in AML patients treated with azacitidine and nivolumab. Using Chromium Single Cell Immune Profiling, they identify T-cell clonality differences between responders and nonresponders. Responders show expanded T-cell repertoires and a CD8+ cytotoxic T cell population expressing Granzyme K (GZMK), linked to improved survival. Their findings suggest GZMK as a potential biomarker for therapy efficacy. Chromium Single Cell Immune Profiling offers promising insights into cancer drug resistance, further enhanced by Barcode Enabled Antigen Mapping (BEAM) technology, facilitating high-resolution profiling of antigen-specific B and T cells.

Summary

In short,  Single cell Immune Profiling unravels the innate and adaptive immune system of tumor microenvironment (TME) in a multiomics approach to gain deeper insights into  cancer pathogenesis and progression, test an efficacy of promising therapeutics against cancer as well as determine specific clones and potential novel gene markers indicative of improved success rate of immunotherapies such as tumor-infiltrating lymphocyte (TIL) therapy.

References:

1. Wong CH, et al. Estimation of clinical trial success rates and related parameters. Biostatistics 20:273–286 (2019). doi: 10.1093/biostatistics/kxx069
2. Yamawaki, TM. et al. Systematic comparison of high-throughput single-cell RNA-seq methods for immune cell profiling. BMC Genomics 22, 66 (2021). doi: 10.1186/s12864-020-07358-4
3. Wang Y, et al. Multimodal single-cell and whole-genome sequencing of small, frozen clinical specimens. Nat Genet 55: 19–25 (2023). doi: 10.1038/s41588-022-01268-9. https://www.eurekalert.org/news-releases/977061
4. Ye K, et al. An armed oncolytic virus enhances the efficacy of tumor-infiltrating lymphocyte therapy by converting tumors to artificial antigen-presenting cells in situ. Mol Ther 30: 3658–3676 (2022). doi: 10.1016/j.ymthe.2022.06.010
5. https://www.mdanderson.org/cancerwise/what-is-tumor-infiltrating-lymphocyte-til-therapy–6-things-to-know.h00-159460056.html
6. Daver N, et al. T-cell-based immunotherapy of acute myeloid leukemia: current concepts and future developments. Leukemia 35: 1843–1863 (2021). doi: 10.1038/s41375-021-01253-x
7. Abbas HA, et al. Single cell T cell landscape and T cell receptor repertoire profiling of AML in context of PD-1 blockade therapy. Nat Comms 12: 6071 (2021). doi: 10.1038/s41467-021-26282-z

Source: Single cell immune profiling fuels biomarker discovery in clinical cancer samples