RADT-23. MOLECULAR PROFILING OF GLIOMAS: INSIGHTS INTO RADIONECROSIS AND PSEUDOPROGRESSION THROUGH NEXT-GENERATION SEQUENCING
Bibliographic record
Abstract
Abstract BACKGROUND Gliomas, the most common primary tumors of the CNS, presenting diagnostic and therapeutic challenges due to their heterogeneity. Next-generation sequencing (NGS) enhances diagnostic precision by identifying genetic alterations, guiding accurate diagnosis and personalized treatment strategies. Post-treatment complications such as radionecrosis and pseudoprogression present additional diagnostic difficulties, often mimicking tumor recurrence. This study aimed to evaluate the association between genetic alterations detected by NGS and treatment-related complications. METHODS This retrospective study analyzed data from electronic medical records at a Brazilian Radiation Therapy Department (2018-2023). The study included patients with gliomas who underwent surgical resection followed by adjuvant radiochemotherapy and subsequently developed complications such as radionecrosis and pseudoprogression. Genetic alterations detected by the HSL 500 (NGS) test were evaluated for their association with these complications using Fisher’s Exact Test. RESULTS Out of 192 patients treated for glioma, 46 (23.96%) experienced treatment-related complications, with 20 patients having available NGS test results. Among these, eight cases were identified as pseudoprogression, fifteen as radionecrosis, with three patients presenting both conditions. All 20 patients with NGS results were diagnosed with high-grade gliomas, eight of whom underwent reirradiation, resulting in two cases of radionecrosis post-reirradiation. Although no statistically significant association was found between genetic alterations and radionecrosis or pseudoprogression, specific mutations were prevalent in each group. In radionecrosis cases, the most common mutations were TERT promoter (c.1-124C>T) (n=9, p=0.613) and EGFR amplification (n=8, p=1.0). In pseudoprogression, frequent mutations included TERT promoter (c.1-124C>T) (n=6, p=0.642), EGFR (n=5, p=0.67), PTEN (n=4, p=1.0), NF1 (n=2, p=0.537), and P53 (n=2, p=0.197). CONCLUSION Molecular testing for glioma characterization is crucial for diagnosis and prognosis, aiding in understanding treatment-related complications. Strategies to avoid radionecrosis and pseudoprogression are vital to improve patient quality of life, especially in high-grade gliomas. Further studies are needed to confirm these trends and explore clinical relevance of mutations.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".