Single Cell Mass Cytometry for Phenotypic Analysis of Diffuse Large B-Cell Lymphoma
Bibliographic record
Abstract
Abstract Diffuse Large B-cell Lymphoma (DLBCL) is the most common histologic subtype of non-Hodgkin Lymphoma (NHL). Despite its improved outcome with R-CHOP chemotherapy, 40% of patients still suffer with relapsed or refractory disease. Further investigation is needed to understand the complexity of DLBCL. Time-of-flight mass cytometry (CyTOF) is a recently developed technology that combines traditional flow cytometry with mass spectrometry and supports analysis of up to 30-40 parameters simultaneously at the single cell level with minimal spectral overlap (Bendall et al, Science 2011). In this study, we sought to develop a CyTOF method for phenotypic analysis of DLBCL to obtain high resolution profiles of the malignant clone(s) represented in individual tumor samples and resolve any underlying population substructure that might be informative in understanding the clinical and biologic heterogeneity of this disease. We designed a two-tube assay for this study. Tube #1 contained 35 cell surface markers including CD45, CD19, CD20, CD22, CD79B, IgM, IgD, Ig Kappa, Ig Lambda, CD5, CD10, CD23, CD43, CD38, CD138, CD44, CD21, CD24, CD40, CD72, CD80, CD45RA, CD49D, CD49F, CD62L, CD25, CD27, CD30, CD127, CD184, CD194, CD200, CD34, HLA-DR, and CD3. Tube #2 contained 37 markers in total including 17 cell surface markers overlapping with Tube #1 plus an additional 20 intracellular markers (BCL2, BCL6, IRF4/MUM1, LMO2, MYC, MCL1, MEF2B, KAT3B/P300, CBP, FOXP1, RUNX1, Ikaros, EZH2, BMI1, NOTCH1, CARD11, IkBa, phospho-Rb, Ki67, and CyclinD2). Metal-conjugated antibodies were purchased from DVS Sciences or unconjugated antibodies labeled in-house using DVS MaxPar metal labeling kits. Data were acquired using a DVS CyTOF2 instrument. We examined both fresh and viably frozen single cell suspensions from diagnostic lymph node biopsy samples received for flow cytometric analysis at the BC Cancer Agency. We used SPADE (spanning-tree progression analysis of density-normalized events) for initial data analysis. We first performed preliminary validation studies including cross-comparison of mass cytometry (CyTOF2) vs. flow cytometry (BD Canto2) datasets and fresh vs. previously frozen cell suspension material. Although individual marker intensities using matched antibody clones were in general lower by CyTOF, eight-parameter surface staining results were qualitatively comparable between the two platforms. Also there were essentially no differences observed in CyTOF staining profiles between fresh and previously frozen samples. Preliminary clustering analysis of cell populations using SPADE revealed clear separation between normal and malignant B cell populations as well as apparent substructure to the malignant population in a subset of DLBCL samples. These findings suggest intratumoral heterogeneity can be resolved by high dimensional CyTOF analysis. Ongoing efforts will focus on determining if phenotypically defined subsets show enrichment for subclonal mutations. Disclosures No relevant conflicts of interest to declare.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".