Significance of Single-cell Level Dual Expression of BCL2 and MYC Determined With Multiplex Immunohistochemistry in Diffuse Large B-Cell Lymphoma

ABSTRACTMultiplexed immune cell profiling of the tumor microenvironment (TME) in cancer has improved our understanding of cancer immunology, but complex spatial analyses of tumor-immune interactions in lymphoma are lacking. Here we used imaging mass cytometry (IMC) on 33 cases of diffuse large B cell lymphoma (DLBCL) to characterize tumor and immune cell architecture and correlate it to clinicopathological features such as cell of origin, gene mutations, and responsiveness to chemotherapy. To understand the poor response of DLBCL to immune check point inhibitors (ICI), we compared our results to IMC data from Hodgkin lymphoma (HL), a cancer highly responsive to ICI, and observed differences in the expression of PD-L1, PD-1, and TIM-3. We created a spatial classification of tumor cells and identified sub-regions of immune activation, immune suppression, and immune exclusion within the topology of DLBCL. Finally, the spatial analysis allowed us to identify markers such as CXCR3, which are associated with penetration of immune cells into immune desert regions, with important implications for engineered cellular therapies.SIGNIFICANCEThis is the first study to integrate tumor mutational profiling, cell of origin classification, and multiplexed immuno-phenotyping of the TME into a spatial analysis of DLBCL at the single cell level. We demonstrate that, far from being histo-pathologically monotonous, DLBCL has a complex tumor architecture, and that changes in tumor topology can be correlated with clinically relevant features. This analysis identifies candidate biomarkers and therapeutic targets such as TIM-3, CCR4, and CXCR3 that are relevant for combination treatment strategies in immuno-oncology and cellular therapies such as CAR-T cells.

Download Full-text

Mass Cytometry Based Classification of Inter- and Intra-Tumoral Heterogeneity in Diffuse Large B-Cell Lymphoma

Blood ◽

10.1182/blood.v126.23.3908.3908 ◽

2015 ◽

Vol 126 (23) ◽

pp. 3908-3908

Author(s):

Manabu Kusakabe ◽

Xuehai Wang ◽

Guillermo Simkin ◽

Justin Meskas ◽

Chaoran Zhang ◽

...

Keyword(s):

Lymph Node ◽

B Cells ◽

B Cell ◽

Single Cell ◽

Cell Lymphoma ◽

B Cell Lymphoma ◽

Cell Populations ◽

Mass Cytometry ◽

Large B Cell Lymphoma ◽

Large B Cell

Abstract Background: Recent work in both hematologic malignancies and solid tumors has supported the notion that human cancers exhibit marked intra-tumoral heterogeneity (ITH). Results from next generation sequencing (NGS) studies support that subclonal DNA mutations underlie genotypic ITH within a single tumor since the majority of sequence variants are present in only 5-50% of reads for a given tumor sample, and single cell analyses have shown that individual tumor subclones may be ancestrally related in a complex branching hierarchy, suggesting that therapy failures and progressive disease likely arise by Darwinian selection for more aggressive or therapy resistant clones. It has become increasingly clear that it will be important to understand the multi-clonal structure of tumors in order to treat them more effectively. In this study, we sought to use time-of-flight mass cytometry (CyTOF) to explore clonal phenotypic substructure in diffuse large B-cell lymphoma (DLBCL), a diagnostic entity notorious for clinical heterogeneity. Methods: We examined viably frozen single cell suspensions from diagnostic lymph node biopsy samples received for flow cytometric analysis at the BC Cancer Agency. We have thus far acquired CyTOF data from 25 cases of DLBCL using a two-tube, 40-parameter panel encompassing a total of 58 different markers including both surface and intracellular antigens that were selected to reveal heterogeneity within the malignant B-cell population. For each sample acquisition, we included "spiked-in" control cells from pooled reactive (non-malignant) lymph node samples to control for staining variation between antibody/reagent lots and also run-to-run CyTOF instrument drift, facilitated by a CD45 antibody "barcoding" approach. We analyzed the data using a combination of viSNE, Isomap, and PhenoGraph analysis packages. Results: Analysis of individual tumor samples readily distinguished between malignant and residual normal B-cell populations, and also revealed distinct subpopulations among malignant cells of varying degrees of relatedness to one another. These subpopulations were then sorted from one another by conventional FACS from parallel vials of cryopreserved cells using lower dimensional sorting strategies derived from the 40-parameter CyTOF data. Sorted subpopulations will be analyzed by targeted amplicon sequencing for single nucleotide variants identified from whole exome sequencing data obtained from unsorted material to explore the hypothesis that these may represent genotypic subclones.  Analysis of multiple tumor samples at once yielded several observations. First, B-cells from reactive lymph nodes and non-malignant B-cells within patient lymphoma specimens reproducibly cluster atop one another, indicating highly similar if not identical phenotypic profiles. Second, the majority of patient DLBCL tumors form cohesive individual clusters, separate and distinct from one another, suggesting that the 40-dimensional panel defines cell populations with sufficient resolution such that each patient's tumor can be uniquely identified. Third, individual DLBCL tumors do not aggregate in tight proximity with one another to the extent that we observe among patient follicular lymphoma (FL) samples, suggesting DLBCL represents a broader diversity of phenotypic classes. Fourth, there is local, but loose aggregation of ABC versus GCB subtypes, but there are also clear outliers and areas of intermingling between ABC and GCB tumors, as defined by immunohistochemistry. Finally, a subset of DLBCL tumors exhibit minor subpopulations that map apart from their corresponding "parent" tumor populations, but yet overlap one another, raising the possibility of divergent evolution away from (or alternatively convergent evolution towards) a common tumor archetype. Conclusions:  Taken together, these observations support that novel information can be derived from CyTOF data with important implications for our understanding of both intra- and inter-tumoral heterogeneity in DLBCL. Disclosures Scott: Celgene: Consultancy, Honoraria; NanoString: Patents & Royalties: Inventor on a patent that NanoString has licensed.

Download Full-text

Cell type-specific Pathways Associated with Diffuse Large B-cell Lymphoma Metastasis Related to Neuro-Diseases

10.21203/rs.3.rs-265607/v1 ◽

2021 ◽

Author(s):

Ashmita Dey ◽

Ujjwal Maulik

Keyword(s):

Central Nervous System ◽

Nervous System ◽

B Cell ◽

Single Cell ◽

Cell Lymphoma ◽

B Cell Lymphoma ◽

Cell Types ◽

Large B Cell Lymphoma ◽

The Impact ◽

Large B Cell

Abstract Background: With the advancement of single-cell sequencing, it’s become rapid emergency to detect the cell-specific changes of Diffuse Large B-cell Lymphoma metastasis that leads to the central nervous system disorder. Results: In this study, single-cell RNA-seq of Peripheral blood mononuclear cell from a human sample is curated and cell types related to lymphocytes are identified. Subsequently, the potential markers of Diffuse Large B-cell Lymphoma are found. It is noticed that LEF1, TCF7 and CD79A/B markers of different cell types show an important role in this disease formation, progression and metastasis processes. To understand the impact of markers, associated pathways are studied in details by establishing a pathway semantic network. Moreover, this association validated the channel through which the pathways are triggered within the cell environment and resulted in metastasis. The connection between Diffuse Large B-cell Lymphoma metastasis and other central nervous system disorders is demonstrated by constructing a disease network. Conclusion: The study reveals how cell types are responsible for the pathway shifts. Furthermore, this information provides a cell-specific channel of triggering the progression of central nervous system diseases among Diffuse Large B-cell Lymphoma patients.

Download Full-text

Single Cell Mass Cytometry for Phenotypic Analysis of Diffuse Large B-Cell Lymphoma

Blood ◽

10.1182/blood.v124.21.2976.2976 ◽

2014 ◽

Vol 124 (21) ◽

pp. 2976-2976 ◽

Cited By ~ 1

Author(s):

Manabu Kusakabe ◽

Guillermo Simkin ◽

Justin Meskas ◽

Chaoran Zhang ◽

Daisuke Ennishi ◽

...

Keyword(s):

B Cell ◽

Single Cell ◽

Cell Lymphoma ◽

B Cell Lymphoma ◽

Surface Markers ◽

Cell Surface Markers ◽

Mass Cytometry ◽

Phenotypic Analysis ◽

Large B Cell Lymphoma ◽

Large B Cell

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.

Download Full-text