Proxe: A Public Repository of Xenografts to Facilitate Studies of Biology and Expedite Preclinical Drug Development in Leukemia and Lymphoma
Bibliographic record
Abstract
Abstract To expedite the translation of biologic discoveries into novel therapeutics, there is a pressing need for panels of in vivo models that capture the molecular complexity of human disease. While traditional cell lines and genetically engineered mouse models are useful tools, they are insufficient to assess the broad diversity of human tumors within a context that recapitulates in situ biology. Patient-derived xenografts (PDXs), generated by transplanting primary human tumor cells into immune-deficient NOD.Cg-Prkdcscid/Il2rgtm1Wjl/SzJ (NSG) mice, surmount some of the limitations of these traditional platforms and have been increasingly utilized as tools for preclinical investigation. However, the infrastructure required to generate, bank, and characterize PDX models limits their availability to only a few investigators. To address this issue, we established a repository of PDX models of leukemia and lymphoma, which we have named the Public Repository of Xenografts (PRoXe). At the time of this writing, PRoXe contains 213 independent lines that have been passaged through mice once (P0), 123 of which have been repassaged in a second generation (P1) or further repassaged. The repository encompasses AML, B- and T-ALL, and B- and T-cell non-Hodgkin lymphoma (NHL) across a range of cytogenetic- and molecularly-defined subtypes (Table 1). PRoXe is extensively annotated with patient-level information, including demographics, phase of treatment, prior therapies, tumor immunophenotye, cytogenetics, and molecular diagnostics. PDX lines available for distribution are characterized by immunophenotyping, whole transcriptome sequencing (RNAseq), and targeted exon sequencing of ~300 genes. To confirm fidelity of engrafted tumors to their corresponding clinical samples, lymphomas were morphologically assessed in P0 mice by H&E and, when pathologic adjudication was required, by immunohistochemistry. Xenografted leukemias were compared to their original tumors immunophenotypically. Unsupervised hierarchical clustering was performed on 132 of these lines based on transcriptome sequencing data and demonstrated 94% concordance between classification of the PDX lines by RNA expression and by the annotated clinical-pathologic diagnoses. Discordant cases highlighted unusual variants, such as B-ALL with aberrant expression of myeloid markers and a follicular lymphoma that underwent blastic transformation in the mouse. Multiple lines have been luciferized and confirmed to home to bone marrow, spleen, and liver. Existing lines from PRoXe have already been shared with more than ten academic laboratories and multiple industrial partners. All of the data referenced here are freely available through a customized web-based search application at http://proxe.org, and lines can be requested for in vitro or in vivo experiments. We are actively expanding the size of PRoXe to allow for large pre-clinical studies that are powered to detect differences across genetically defined subsets. Thus, we are happy to host additional lines from outside investigators on PRoXe and thereby expand the availability of these valuable reagents. Finally, we have made the source code for PRoXe (in R Shiny) open-access, so that other investigators can establish their own portals. Table 1. WHO diagnostic entities encompassed within PRoXe at P1 or later, or P0 or later for B-ALLs. WHO Classification - number of lines per diagnostic entity AML, Other Myeloid, and Ambiguous Lineage [n=32] ALL [n=107] AML - recurrent gene mutations 6 B-ALL - NOS 44 AML - MDS-related changes 5 B-ALL - MLL-rearranged 11 AML - NOS 4 B-ALL - BCR-ABL 10 AML - MLLT3-MLL 2 B-ALL - hyperdiploidy 9 Acute myelomonocytic leukemia 1 B-ALL - TEL-AML1 8 Acute monocytic leukemia 1 B-ALL - E2A-PBX1 3 AML unable to classify 2 B-ALL unable to classify 1 Blastic plasmacytoid dendritic cell neoplasm 8 T-ALL 21 Mixed phenotype, MLL rearranged 1 B/myeloid acute leukemia 1 Myelodysplastic syndrome 1 Mature B cell neoplasms[n=11] Mature T and NK cell neoplasms [n=4] DBLCL - NOS 4 Angioimmunoblastic T-cell lymphoma 1 Mantle cell lymphoma 3 Adult T-cell leukemia/lymphoma 1 Extranodal marginal zone lymphoma 1 Extranodal NK/T-cell lymphoma 1 B-cell lymphoma, unclassifiable, with features intermediate between DLBCL and BL 3 SŽzary syndrome 1 Disclosures Konopleva: Novartis: Research Funding; AbbVie: Research Funding; Stemline: Research Funding; Calithera: Research Funding; Threshold: Research Funding. Etchin:Karyopharm: Research Funding. Lane:Stemline Therapeutics, Inc.: Research Funding. Stone:Abbvie: Consultancy; Novartis: Research Funding; Celator: Consultancy; Amgen: Consultancy; Celgene: Consultancy; Agios: Consultancy; Sunesis: Consultancy, Other: DSMB for clinical trial; Merck: Consultancy; Karyopharm: Consultancy; Roche/Genetech: Consultancy; Pfizer: Consultancy; AROG: Consultancy; Juno: Consultancy.
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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 | 0.007 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.023 | 0.013 |
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".