Genomic and Molecular Properties of Relapsed CNS Lymphoma Using Novel Primary Meningeal Lymphoma Cell Lines and Intracranial Xenografts,
Bibliographic record
Abstract
Abstract Abstract 3477 Background: There is a paucity of molecular information regarding the phenotype of relapsed aggressive CNS lymphoma, a condition for which there are few effective treatment options and, as a consequence, patient survival is often short. To test our hypothesis that the molecular properties of CNS lymphoma at relapse are distinct from those at diagnosis we pursued two parallel lines of investigation: 1) the genomic analysis of relapsed aggressive CNS lymphomas in comparison to newly diagnosed specimens and 2) the generation of novel CNS lymphoma cell lines derived from recurrent meningeal lymphomas isolated from the cerebrospinal fluid. We hypothesize that this approach will facilitate the identification of the underlying molecular determinants of tumour progression, novel genome-based biomarkers and therapeutic targets. Methods: We compared genome copy number using high-resolution array comparative genomic hybridization (array-CGH) and used bioinformatics to study a carefully selected cohort of tumours comprised of 10 newly-diagnosed primary CNS lymphomas (large B-cell) and 7 relapsed/refractory CNS lymphomas (5 large B-cell, 2 of transformed histology). We evaluated copy number aberrations that occurred in the tumour cohort as a whole as well as those that occur predominantly in relapsed cases. In addition, we established five novel lymphoma cell lines from relapsed cases, three of which were derived from meningeal lymphomas isolated from the cerebrospinal fluid and expanded upon intracranial implantation in NSG mice as patient-derived xenografts. Results: There was a trend for an increase in the proportion of copy number losses involving the short arm of chromosome 6 as well as overall gains on chromosome 12 among the relapsed cases. Significant DNA copy number gains for STAT6 were noted in 4/7 relapsed cases. We observed a significant number of deletions present in between 50–90% of newly diagnosed tumors that were absent in CNS lymphomas at relapse, suggestive of complex genomic remodeling during tumour evolution. In addition, a region with potential prognostic implications was identified at chromosome 19p.13.3 that was deleted in 57% of relapsed tumors but not in newly diagnosed cases. Three of the five relapsed large cell cases exhibited significant deletions, including one focal homozygous deletion, at chromosome 4q23.3–4q23.5, a region not previously shown to be deleted in large cell lymphoma (Lenz et al., PNAS, 2008). Both chromosomes 14 and 22 have copy number aberrations that occur in > 80% of all tumours as well as high frequency focal aberrations that appear linked to either good or poor prognosis. Significantly, the MTAP and CDKN2A genes at 9q21 are homozygously co-deleted in 18% of poor prognosis or relapsed patients. Notably, each of the orthotopic xenografts exhibited an ABC immunophenotype and were diffusely infiltrative with meningeal tropism. In fact, CNS metastasis to the meninges was recapitulated when the lymphoma cells were implanted in flank and spontaneously metastasized to brain, within three months post injection. In vitro chemotaxis assays demonstrated responsiveness of human meningeal lymphoma cells to CXCL-13 and SDF-1, chemokines postulated to contribute to the CNS tropism of NHL. Importantly, genomic aberrations identified in the parent tumours were retained when the relapsed meningeal lymphomas were serially passaged by intracranial implantation as xenografts, as evidenced by array-CGH. Conclusions: We believe that this study represents the first analysis of the biologic and genetic properties of relapsed CNS lymphoma. This analysis provides the first direct evidence that chemokines previously shown to be expressed in the CNS lymphoma microenvironment direct chemotaxis of meningeal lymphoma cells isolated from patients. This result is suggestive of a molecular mechanism which may be essential to CNS tropism. In addition, we have established the first in vivo model system of CNS lymphoma which retains the genomic properties of relapsed, refractory disease and which has significant potential for preclinical testing of novel therapeutic strategies. Supported by Leukemia and Lymphoma Society and NIH Grant CA13908301. 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 | 0.000 | 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 | 0.000 | 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".