Abstract A51: Advances in the etiology and therapeutics of a lethal childhood cancer, fibrolamellar hepatocellular carcinoma
Bibliographic record
Abstract
Abstract Introduction: Fibrolamellar hepatocellular carcinoma (FLC) is a liver cancer affecting adolescents and young adults without underlying liver disease. Patients with FLC are often diagnosed with advanced-stage disease and have a poor 5-year survival. Recently we have made advances in both understanding the etiology of FLC as well as developing therapeutics. We have found that the bulk of the genome lacks recurrent single-nucleotide or structural variants (inversions, amplifications) with the exception of a deletion in one copy of chromosome 19. This results in a fusion of the first exon of the heat shock protein, DNAJB1, with the 2nd through 10th exons of PRKACA, the catalytic subunit of protein kinase A. Expression of this fusion in the livers of mice, either by CRISPR or transposon, is sufficient to phenocopy the disease. The kinase activity of the fusion protein is essential for transformation, but equivalent expression of the native kinase is not sufficient. Results: Etiology: We have tested the ability of the native kinase and fusion oncokinase to phosphorylate potential substrates in human liver. We have found a discrete set of substrates that are phosphorylated in human liver for which we are now testing, which are critical for the pathogenesis of this cancer. Therapeutics: We have purified the fusion oncokinase without a tag and used a high-throughput screen to find inhibitors. We have found inhibitors in the nanomolar range for which we are using structural analysis to inform our medicinal chemistry. Additionally, we have developed several “never-in-plastic” patient-derived xenograft (PDX) models that retain expression of the driver, histology, transcriptome, and proteome of the original human tumor. We have also screened for compounds that induce tumor cell death and tumor regression in FLC PDXs. Conclusion: Subtle changes in the kinase substrate profile of the fusion kinase provide new leads for therapeutics for FLC. The ability to find inhibitors of the kinase in the nanomolar range, as well as the ability to screen for inhibitors of the PDX, offers the first hope for treatment against this lethal tumor. Citation Format: Gadi Lalazar, Melissa Jarmel, Ruisi Wang, Michael Tomasini, David Requena, Denise Ng, Sanford M. Simon. Advances in the etiology and therapeutics of a lethal childhood cancer, fibrolamellar hepatocellular carcinoma [abstract]. In: Proceedings of the AACR Special Conference on the Advances in Pediatric Cancer Research; 2019 Sep 17-20; Montreal, QC, Canada. Philadelphia (PA): AACR; Cancer Res 2020;80(14 Suppl):Abstract nr A51.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.003 |
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".