Molecular Signatures of Chromosomal Instability Correlate With Copy Number Variation Patterns and Patient Outcome in IDH-Mutant and IDH-Wildtype Astrocytomas
Bibliographic record
Abstract
Chromosomal instability due to mutations in genes guarding the stability of the genome is a well-known mechanism underlying tumorigenesis and malignant progression in numerous cancers. The effect of this process in gliomas is mostly unknown with relatively little research examining the effects of chromosomal instability on patient outcome and therapeutic efficacy, although studies have shown that overall/total copy number variation (CNV) is elevated in higher histologic grades and in cases with more rapid progression and shorter patient survival. Herein, we examine a 70-gene mRNA expression signature (CIN70), which has been previously shown to correlate tightly with chromosomal instability, in 2 independent cohorts of IDH-mutant astrocytomas (total n = 241), IDH-wildtype astrocytomas (n = 228), and oligodendrogliomas (n = 128). Our results show that CIN70 expression levels correlate with total CNV, as well as higher grade, progression-free survival, and overall survival in both IDH-mutant and IDH-wildtype astrocytomas. In oligodendrogliomas, these mRNA signatures correlate with total CNV but not consistently with clinical outcome. These data suggest that chromosomal instability is an underlying factor in aggressive behavior and progression of a subset of diffuse astrocytomas. In addition, chromosomal instability may in part explain the poor response of diffuse gliomas to treatment and may serve as a future therapeutic target.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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 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".