Integrated single cell analysis reveals co-evolution of malignant B cells and the tumor microenvironment in transformed follicular lymphoma
Bibliographic record
Abstract
Abstract Follicular lymphoma (FL) is the most common indolent form of non-Hodgkin lymphoma. Histological transformation of FL to a more aggressive form of lymphoma occurs with a linear incidence of 2-3% per year and is associated with poor outcome. Divergent clonal evolution and an altered tumour microenvironment (TME) have both been implicated in the transformation process. However, the phenotypic consequences of this evolution and its implication in reshaping the TME remain unknown. To address this knowledge gap we performed single cell whole genome (scWGS) and single cell whole transcriptome sequencing (scWTS) of paired pre/post transformation samples of 11 FL patients. We further performed scWTS analysis of additional 11 FL samples from patients that had not undergone transformation within 7 years. Our comprehensive single cell analysis revealed the evolutionary dynamics of transformation at unprecedented resolution. Computational integration of scWGS and scWTS allowed us to identify gene programs upregulated and positively selected during evolution. Furthermore, our scWTS analysis revealed a shifting TME landscape, with an exhausted CD8 T cell signature emerging during transformation. Using multi-color immunofluorescence we transferred these findings to a novel TME based biomarker of transformation, subsequently validated in 2 independent cohorts of pretreatment FL samples. Taken together, our results provide a comprehensive view of the combined genomic and phenotypic evolution of malignant cells during transformation, and the shifting cross-talk between malignant cells and the TME. Graphical abstract
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".