Defining Functional Heterogeneity In Acute Lymphoblastic Leukemia
Bibliographic record
Abstract
Abstract Despite high survival rates for children with acute lymphoblastic leukemia (ALL), only 40% of adult patients will achieve long-term disease-free survival, and relapses in both pediatric and adult ALL are often fatal. Most current therapies are directed at molecular markers or dominant pathways present in the bulk of neoplastic cells, yet recent studies have identified many genetically distinct subclones co-existing within a single neoplasm. The functional properties and clinical relevance of these neoplastic subclones remain undefined. Genome wide copy number analysis of matched diagnostic and relapse ALL samples identified that in 50% of patients, the clones present at relapse are not the dominant clones at diagnosis, but have evolved from an ancestral pre-leukemic clone (Mullighan et al., 2008). In order to investigate the functional consequences of clonal evolution in disease progression and therapy resistance, we performed limiting dilution analysis of 3 diagnostic and 14 paired diagnostic/relapse samples from adult and pediatric B-ALL patients of varying cytogenetics, by transplantation into immune-deficient mice (xenografts). In one patient, the leukemia-initiating cell (LIC) frequency was 7.65 fold higher in the relapse sample than at diagnosis, while another patient showed the reverse with a 5.81 fold higher LIC frequency in the diagnostic sample. Two patients showed no significant differences in LIC frequency from diagnosis to relapse. LIC frequency varied from 1 in 14.2 to 1 in 4802 CD19+ blast cells. Interestingly, in 50% of the paired patient samples, transplantation of cells from the relapse sample gave rise to greater leukemic dissemination to the spleen and/or central nervous system of recipient mice in comparison to the diagnostic sample, despite similar levels of engraftment in the bone marrow. This data suggests that although the LIC frequency in B-ALL remains high and relatively static between diagnosis and relapse, relapse cells acquire increased invasive properties. To investigate the clonal composition of 3 diagnostic B-ALL samples, we undertook copy number variation (CNV) analysis of xenografts generated at both limiting and high transplanted cell doses. In all 3 samples, we detected subclones in the xenografts that were distinct from the predominant clone in the primary patient sample. We performed network analysis on these subclones and identified differentially enriched pathways, including differential expression of anti-apoptotic and apoptosis regulation pathways, providing evidence of putative functional differences. These results support the existence of functionally diverse subclones within diagnostic samples as well as functional diversity between the subclones present at diagnosis and relapse. Ongoing in depth genomic analysis of the diagnosis/relapse paired samples will add to our understanding of the functional role of the subclones identified at diagnosis in the establishment of disease relapse. In summary, these experiments will provide further insight into the functional heterogeneity present in B-ALL and the drivers of lymphoid leukemogenesis that lead to therapy failure and disease relapse. Disclosures: Danska: Trillium Therapeutics/Stem Cell Therapeutics: Research Funding.
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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 | 0.000 | 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".