Relationship between epidermal growth factor receptor overexpression and response to radiation regimens in patients with newly diagnosed glioblastoma multiforme
Bibliographic record
Abstract
Glioblastoma multiforme (GBM), the most common infiltrative astrocytic primary brain malignancy remains an incurable disease, despite a multimodal therapy that consists of surgery followed by radiotherapy (RT) with concurrent and adjuvant chemotherapy (TMZ).GBM is a devastating disease with a highly heterogeneous survival between patients.A number of recent large-scale genomic and proteomic studies have shed new light on GBM pathogenesis and molecular diversity.Nonetheless, all patients receive the same treatment of surgery, RT and TMZ.A multitude of targeted therapies have so far failed to demonstrate any survival differences in GBM patients.While certain markers, such as MGMT methylation with respect to TMZ treatment, have been found to confer different survival outcomes between patients, there is a need to further stratify patients to investigate optimal treatment regimes.To this end, we constructed a tissue microarray (TMA) for 201 newly diagnosed GBM patients from a single institution, recorded their histopathological and clinical information and assessed expression of major GBM prognostic markers including Ki67, EGFR, p53, PTEN, CD44, and vimentin.MGMT promoter methylation has been prospectively performed for 143 (71.1%) patients.We analyzed survival outcomes between patients with EGFR overexpression and nonoverexpression.EGFR is known to be involved in the radioresistant phenotype of GBM and activated by RT.Since EGFR overexpression has been found to confer different survival and treatment benefits in GBM and other cancer types, we investigated the different survival outcomes between conventional RT and hypofractionated regimens.We also subdivided tumours into profiles reminiscent of three of the identified molecular based subtypes (Classical, Mesenchymal, Proneural) using immunohistochemistry scoring and analyzed the survival outcomes based on molecular profiles.Further investigation is currently underway to assess the prognostic value of EGFR overexpression in radioresistance with respect to other clinical and histopathological variables.Our study established a TMA with a clinically annotated database for 201 newly diagnosed GBM patients.This will be of great value for stratification of GBM patients who may derive benefit from a tailored radiation regimen using cost-effective protocols for the implementation of an immunohistochemical-based molecular signature.
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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 | 0.001 |
| 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 | 0.000 |
| 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".