Hematological malignancies, such as lymphomas and leukemias, are characterized by their molecular heterogeneity that drives disease progression, resistance, and relapse, and contributes to poor prognoses especially in therapy-related cases. The expansion of dysfunctional clonal populations due to a variety of somatic driver mutations is further complicated by clonal evolution in response to selective pressure such as chemotherapy, which makes treatment challenging. Consequently, the development and application of effective therapy regimens is dependent on understanding the composition, function, and dynamics of immune cell populations within the tumor microenvironment and particularly in responses to treatment.

To better understand clonal dynamics within the tumor microenvironment, scientists are leveraging single-cell multiomic approaches to simultaneously measure and integrate multiple data modalities within the same cells, including transcriptomic, proteomic, genomic, and epigenetic data. By correlating these datasets across modalities, researchers can uncover subtle intra- and intercellular mechanisms, interactions, and relationships that may ultimately reveal clinically meaningful patterns.

Addressing the need for single-cell protein detection, we developed oligonucleotide-conjugated TotalSeq™ antibodies that enable robust single-cell protein analysis and integrate across a broad range of multiomic workflows. Explore our TotalSeq reagents.

Discover how researchers are using our TotalSeq reagents to accelerate cancer research by analyzing CAR T cell expansion and through identification of clonal signatures in lymphoma and leukemia. The inclusion of cell surface protein data in these multimodal applications is crucial to connecting genotype and phenotype, which is especially applicable to the genetic complexity of cancers. 

Tracking CAR T cell expansion in patients with relapsed-refractory diffuse large B-cell lymphoma

In a recent publication in Nature Communications, Cao et al. performed CITE-Seq using 10x Genomics 5’ Gene Expression assay and our TotalSeq-C antibodies to track CAR T cell expansion after infusion in multiple patients diagnosed with relapsed-refractory diffuse large B-cell lymphoma.¹ To further refine transcript-based clustering and annotation, Cao et al. leveraged protein expression data from 31 TotalSeq-C antibodies and cross-validated sequencing-based immunophenotyping assignments by flow cytometry. The longitudinal timepoints captured the successional shifts in dominant CAR T cell CD8+ composition, from an exhausted-like effector memory phenotype during the expansion phase following infusion to a more terminal effector phenotype during the persistence phase (Figure 1). These phenotypes are clonally derived from distinct precursor lineages so the phenotypic composition of the infusion product could be used to improve the effectiveness of CAR T cell therapies.

Figure 1. UMAPs depicting single-cell transcriptomes of CD8+ (a) and CD4+ (e) CAR T cells colored by cell cluster. Inset depicts distribution of transcriptomes across timepoints. Violin plots depicting normalized expression levels of key genes and proteins for annotating and phenotyping CD8+ (b) and CD4+ (f) CAR T cells. Stacked bar graphs depicting proportions of each CD8+ (c) and CD4+ (g) CAR T-cell phenotype at different timepoints.

Identification of clonal signatures in nonmalignant B and tumor cells in T-prolymphocytic leukemia

Hesselager et al. utilized the Mission Bio Tapestri platform and our TotalSeq-D Heme Oncology Cocktail to profile pathogenic mutations and clonal dynamics in longitudinal bone marrow and peripheral blood samples from patients diagnosed with T cell prolymphocytic leukemia (T-PLL) in this Blood Neoplasia article.² Targeted amplicon panels confirmed the presence of driver mutations in genes involved in regulating clonal hematopoiesis such as ATM, STAT5B, JAK3, and EZH2, and by integrating cell surface protein data, Hesselager et al. was able to identify nonmalignant B cells within a subset of patients that shared the same pathogenic mutations as malignant T-PLL cells. The shared mutations suggest that the populations derived from the same progenitor clone (Figure 2) and may be an important clue in unraveling the pathogenesis of T-PLL. 

1. Cao, Guoshuai, et al. “Two-Stage CD8+ CAR T-Cell Differentiation in Patients with Large B-Cell Lymphoma.” Nature Communications, vol. 16, no. 1, 2025, p. 4205, Nature.
2. Hesselager, Caroline, et al. “Single-Cell Sequencing Reveals Shared Clonal Signatures in Nonmalignant B and Tumor Cells in T-Prolymphocytic Leukemia.” Blood Neoplasia, vol. 2, no. 2, Mar. 2025, p. 100076, Science Direct.