Abstract 991: Development and characterization of patient derived xenografts from central nervous system metastasis reveal minor clone expansion linked with aggressive tumor behavior
Bibliographic record
Abstract
Abstract Despite recent advances in cancer therapy, options for central nervous system metastasis (CM) remain limited and patient outcomes are dismal. The lack of tumor models that reflect the heterogeneity and complexity of human CM tumors is a barrier to understanding the underlying biology and to developing novel therapies. Here, we report the development and characterization of 39 patient derived xenograft (PDX) models of CM tumors with histological subtypes representing the disease spectrum. The PDX models successfully grew both in the flank and brains of mice, and retained their histology regardless of the site of implantation. Brain metastasis also formed in 5/12 models after intra-cardiac injection. Multi-omic analysis of the PDX tumor and the patient-matched CM tumor showed that PDXs largely retained the molecular profiles of the tumor from which they were derived, including the retention of aberrations in key driver genes and signaling pathways. PDXs differed primarily from the ungrafted patient tumors by a downregulation in immunity-related pathways, which was expected due to the use of an immuno-compromised host, arguing for the validity of using the flank as a site of implantation. Integrated analysis of mutations and gene expression changes in CM revealed an upregulation of neuronal signaling and DNA damage response, and downregulation of calcium signaling and inflammation. We also assessed the clonal evolution of the PDX from the original patient CM by tracing variant allele frequencies in copy number neutral regions. We found that the PDX tumors were heterogeneous and comprised of multiple tumor clones that were either unique or in common with the original tumor, and displayed evidence of clonal expansion. Two PDXs that underwent phylogeny assessment showed evidence of minor clone expansion. One such PDX was a tumor from a Her2+ breast cancer (CM13), which largely did not molecularly resemble its matched patient tumor but was confirmed to have some shared expressed variants. The PDX was nearly copy number neutral, which included loss of the Her2 amplicon, and had few mutations compared with its parent tumor. Most noteworthy, is that CM13 displayed unique molecular patterns, aggressive growth and was highly metastatic in vivo. From the flank, it led to multiple metastases, including micrometastasis in the brain. This suggests that minor clone takeover may confer tumor aggressiveness and potentiate brain metastasis. The large and diverse repertoire of PDXs developed and characterized in this study provides a new set of tools that will help deepen our understanding of CM and improve preclinical testing for CM therapies. Our data also show that expansion of minor clones could confer aggressive tumor behavior and may be important in tumor evolution in PDX models and human cancers. Citation Format: Ben Yi Tew, Christophe Legendre, Tim Triche, Gerald C. Gooden, Kyle N. Johnson, Rae Anne Martinez, Emanuel F. Petricoin, Mariaelena Pierobon, Joyce O'Shaughnessy, Cindy Osborne, Mark A. Schroeder, Daniel J. Ma, Mark Bernstein, Jann N. Sarkaria, Steven A. Toms, Bodour Salhia. Development and characterization of patient derived xenografts from central nervous system metastasis reveal minor clone expansion linked with aggressive tumor behavior [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 991.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".