Integrated comprehensive high-throughput kinomics profiling and whole exome sequencing of penile squamous cell cancer (PSCC).
Bibliographic record
Abstract
383 Background: Molecular drivers in penile squamous cell cancer (PSCC), an orphan malignancy, remain unclear. The Cancer Genome Atlas (TCGA) is not studying PSCC and the Catalogue of Somatic Mutations in Cancer (COSMIC) investigators have reported only targeted analyses of PSCC. We report the first integrated analyses of comprehensive kinomics and whole exome sequencing (seq) in tumors from patients (pts) with PSCC . Methods: We performed integrated functional kinomics profiling and comprehensive exome-seq of two frozen tissue samples from men with PSCC with a matched normal tissue procured from the Cooperative Human Tissue Network (CHTN). Kinomic profiling was performed using the PamStation 12 high-content phospho-peptide substrate microarray system (PamGene International). The protein tyrosine kinome and serine/threonine kinome PamChips were used to measure global kinase activity by detecting phosphorylation of various peptides through FITC-labeled antibodies. Upstream kinase prediction was performed using a scoring algorithm that incorporates the phosphonet database (www.phosphonet.ca). Exome capture was performed with the Agilent SureSelect v5 kit and whole exome-seq was done on the Illumina HiSeq2000 with paired end 100bp chemistry. Results: In the single patient, paired kinomics analysis comparing the tumor sample to adjacent normal tissue, the HER family (EGFR, ERBB2, 3 and 4), AXL, TYRO3 and SYK kinases were the most active. When combining the two tumors in an unpaired analysis against the normal sample, the HER (EGFR, ERBB2, 3 and 4), MER, FRK, and FAK, kinases showed increased activity. When comparing whole exome-seq of the two PSCC samples with normal, among the affected genes were CCDC181, ZNF717, MUC4, HGC6.3, NOTCH1, STK11, SIRPB1, SKA3, PDE6B, FAT1, CACNA2D1, USP17L11, MNT, and CEP89. We are evaluating 10 PSCC tumors and matched normal tissue by kinomics and whole exome-seq and will present these complete data and analysis at the conference. Conclusions: In our preliminary analysis of pts that underwent the first reported integrated kinomics and whole exome-seq performed in PSCC, we identified multiple potential therapeutic targets in tumors.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".