Gain deeper insights into clonal dynamics that affect disease progression and therapeutic resistance with single-cell bioinformatics

This figure illustrates the clonal landscape of two patients with precursor plasma cell neoplasms (MGUS/SMM), as characterized using the Cohort Analysis pipeline. Each row represents a layer of multi-omic data resolved at the single-cell level, and each column represents a genetically distinct clone identified within the sample.

The analysis integrates:

• Clonal Abundance Over Time: The top section shows the relative abundance of each clone at different time points, highlighting clonal evolution and disease dynamics.
• VDJ Clonotypes: Immunoglobulin heavy and light chain usage per clone reveals lineage relationships and clonal expansions.
• Structural Variants and Copy Number Alterations: Detected chromosomal aberrations (e.g., del 1p, gain 1q) and focal copy number changes in oncogenes (e.g., MYC, TP53) provide insight into genomic instability and malignant potential.
• Somatic Mutations: Clone-specific mutations in key driver genes (NRAS, KRAS, TENT5C) are shown with their specific amino acid changes and zygosity.
• Surface Protein Expression: A panel of prognostic markers (e.g., CD19, CD56, BCMA, CD138) is profiled at the single-cell level, linking immunophenotype to genotype across clones.

This multi-dimensional view enables deep characterization of disease heterogeneity and clonal evolution, offering insights into progression risk, therapeutic target expression (e.g., BCMA), and potential for relapse. The Cohort analysis Pipeline on Mosaic is uniquely suited to resolve these complex relationships, empowering translational research and precision medicine in hematologic malignancies.

Overview:

Learn more about how Cohort Analysis is powered by Mosaic.

The diagram illustrates the clonal structure of hematopoietic cells, highlighting the genetic heterogeneity present at the single-cell level. Each node represents a genetically distinct clone, annotated with its specific genomic alterations and the proportion of total cells it comprises.

Key Observations:

• Clone 1 (Wildtype):
  Representing 4.62% of the total population, this clone has no detectable somatic alterations and serves as the ancestral cell population.
• Clone 2 (13q-, X-):
  An early subclonal population (4.46%) with deletions in chromosome 13q and loss of the X chromosome.
• Clone 3 (75.4%):
  The dominant clone, harboring multiple chromosomal gains and losses (1+, 2+, 3+, 6-, 8+, 12+, 14+, 16+, 20+, 21+), suggesting complex karyotypic evolution. This clone likely drives the MGUS phenotype.
• Clone 5 (10.04%):
  Contains a 2q deletion and a NRAS Q61H mutation, indicating activation of oncogenic signaling pathways.
• Clone 6 (3.14%):
  Exhibits chromosomal imbalances on chromosomes 1 and 8, along with NRAS loss of heterozygosity (LoH), which may reflect subclonal adaptation or resistance mechanisms.
• Clone 4 (2.21%):
  Features 1p LoH, potentially impacting tumor suppressor genes in this region.
• Clones 7 and 8:
  Minor populations with 11q- (0.1%) and 11p+ (0.03%) respectively, indicating additional low-frequency events.

Interpretation:

This clonal map reveals a branched evolution pattern, where a wildtype progenitor gives rise to progressively complex subclonal populations. The high frequency of Clone 3 suggests strong clonal dominance, while subclones with NRAS mutations may indicate early oncogenic events contributing to disease progression. These findings underscore the value of single-cell DNA analysis for early detection and monitoring of clonal dynamics in precursor conditions like MGUS.

This clonal phylogenetic tree illustrates the evolutionary relationships and genomic alterations present in a patient sample at Timepoint-2 (Diagnosis), as resolved using the Mission Bio Tapestri® single-cell DNA sequencing platform.

Each branch represents a distinct genetically defined clone, annotated with:

• Percentage of cells in the total population (clonal fraction)
• Copy number changes (e.g., 13q deletion, 1p-/1q+)
• Point mutations (e.g., NRAS Q61H)
• Loss of heterozygosity (LoH) in key genomic regions

The visualization highlights:

• A dominant clone (Clone 6) comprising 89.2% of the sample, harboring multiple chromosomal alterations and NRAS LoH, suggesting clonal selection and expansion.
• Several minor subclones (e.g., Clones 1, 2, 3, 5) with discrete structural variants and mutations, indicating early diversification.
• A clear evolutionary trajectory from early wild-type or singly altered clones to the complex, aberrant dominant population.

Tapestri-powered single-cell phylogenetic reconstruction enables high-resolution insight into tumor heterogeneity and clonal fitness, supporting therapeutic risk stratification and molecular monitoring strategies.

This figure showcases data from 16 patients with monoclonal gammopathies, including MGUS and smoldering multiple myeloma (SMM), analyzed using the Mission Bio Tapestri® Mosaic Cohort Analysis pipeline. Each patient’s sample is deconvoluted into genetically distinct clones, with integrated insights across DNA, protein, and structural features.

Key data layers include:

• Clonal Architecture:
  Clonal fractions indicate the prevalence of each clone within a sample, revealing subclonal complexity and dominance patterns.
• Genomic Features:
  Includes immunoglobulin clonotypes (IGH, IGK, IGL), structural variants (e.g., del(1p), gain(1q), del(13q)), focal copy number variations (e.g., TP53, MYC), and somatic mutations (e.g., NRAS Q61H, KRAS G13D).
• Surface Protein Expression:
  Expression of 13 immunophenotypic markers (e.g., CD138, CD56, BCMA, GPRC5D) is profiled per clone, enabling functional linkage of genotype to phenotype and identification of therapeutic targets.

Overall significance:

This cohort analysis highlights the ability of Mission Bio’s single-cell multi-omics and single-cell bioinformatics to resolve disease heterogeneity, map clonal evolution, and assess clinically actionable features, supporting precision oncology efforts in plasma cell malignancies.