‘Cut from the same cloth’: Shared microsatellite variants among cancers link to ectodermal tissues-neural tube and crest cells
Bibliographic record
Abstract
// Enusha Karunasena 1, * , Lauren J. Mciver 1, * , Jasmin H. Bavarva 1 , Xiaowei Wu 2 , Hongxiao Zhu 2 , Harold R. Garner 1 1 Virginia Bioinformatics Institute, Medical Informatics and Systems Division, Virginia Tech, Blacksburg, VA 24061, USA 2 Department of Statistics, Virginia Tech, Blacksburg, VA 24061, USA * These authors have contributed equally to this work Correspondence to: Enusha Karunasena, e-mail: enusha.karunasena@gmail.com Harold R. Garner, e-mail: garner@vbi.vt.edu Keywords: microsatellite, glioma, medulloblastoma, melanoma, neuroblastoma Received: April 07, 2015 Accepted: June 05, 2015 Published: June 17, 2015 ABSTRACT The pluripotent cells of the embryonic ectodermal tissues are known to be a precursor for multiple tumor types. The adaptability of these cells is a trait exploited by cancer. We previously described cancer-associated microsatellite loci (CAML) shared between glioblastoma (GBM) and lower-grade gliomas. Therefore, we hypothesized that these variants, identified from germline DNA, are shared by cancers from tissues originating from ectodermal tissues: neural tube cells (NTC) and crest cells (NCC). Using exome sequencing data from four cancers with origins to NTC and NCC, a ‘signature’ of loci significant to each cancer ( p -value ≤ 0.01) was created and compared with previously identified CAML from breast cancer. The results of this analysis show that variant loci among the cancers with tissue origins from NTC/NCC were closely linked. Signaling pathways linked to genes with non-coding CAML genotypes revealed enriched connections to hereditary, neurological, and developmental disease or disorders. Thus, variants in genes from tissues initiating from NTC/NCC, if recurrently detected, may indicate a common etiology. Additionally, CAML genotypes from non-tumor DNA may predict cancer phenotypes and are common to shared embryonic tissues of origin.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".