Abstract P21: Single Cell Resolution Spatial Modeling Uncovers Survival-associated Phenotypes in Diffuse Large B Cell Lymphoma
Bibliographic record
Abstract
Abstract Diffuse large B-cell lymphoma (DLBCL) is the most common aggressive lymphoma and overexpression of the oncogenes MYC, BCL2 and BCL6 impacts patient outcomes. We demonstrated using single-cell resolved analysis that cells with unique co-expression of high MYC and BCL2 but lacking BCL6 (M+2+6-) were consistently correlated with poor survival compared to other combinations. Here we present a follow-up study evaluating M+2+6- spatial patterns and their relationship to survival, tumour processes, and the immune microenvironment. We measured oncogene co-expression at single-cell resolution through multiplexed fluorescent immunohistochemistry (mfIHC) in four cohorts of DLBCL (n=449). Spatial point patterns were derived from multispectral images, upon which Gibbs modeling was applied. This analysis uncovered a ‘dispersed’ spatial phenotype exhibited by M+2+6- cells, which stratified DLBCL cohorts for survival. Bulk/single-cell transcriptomic analyses of DLBCL samples enriched with the ‘dispersed’ phenotype identified several genes, such as LAG3 and IFI27, that are implicated in migration, cell adhesion, and invasion- suggesting that this spatial phenotype is associated with tumour invasiveness. Single cell analysis revealed unique communication pathways IL10 and SEMA3 between this phenotype and immune cells. IL10 promotes aggressiveness and proliferation in DLBCL and SEMA3 and is a regulator of RAC1 that influences cell migration. Digital Spatial Profiling (DSP) analyses were also performed, applying the protein-based nCounter method (29 immune markers) to 110 DLBCL samples, and the Whole Transcriptome Atlas (WTA) panel (18,000 genes) to CD3+ enriched regions of 47 DLBCL samples. Analysis of patients enriched in the ‘dispersed’ phenotype revealed an immune cold microenvironment, enriched in Tregs and exhausted CD4+ and CD8+ T cells. Taken together, we postulate that the M+2+6- associated ‘dispersed’ spatial phenotype is associated with tumor cell invasiveness and an immune cold microenvironment composition, all contributing towards the poor prognosis associated with this spatial phenotype. Citation Format: Shruti Sridhar, Michal Marek Hoppe, Min Liu, Patrick Jaynes, Yanfen Peng, Sanjay De Mel, Limei Poon, Esther Hian Li Chan, Joanne Lee, Chandramouli Nagarajan, Nicholas F. Grigoropoulos, Soo-Yong Tan, Susan Swee-Shan Hue, Shaoying Li, Joseph D. Khoury, Pedro Farinha, Anja Mottok, David W. Scott, Gayatri Kumar, Kasthuri Kannan, Wee Joo Chng, Yen Lin Chee, Siok-Bian Ng, Claudio Tripodo, Anand D. Jeyasekharan. Single Cell Resolution Spatial Modeling Uncovers Survival-associated Phenotypes in Diffuse Large B Cell Lymphoma [abstract]. In: Proceedings of Frontiers in Cancer Science; 2023 Nov 6-8; Singapore. Philadelphia (PA): AACR; Cancer Res 2024;84(8_Suppl):Abstract nr P21.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".