TPD52L2 impacts proliferation, invasiveness and apoptosis of glioblastoma cells via modulation of wnt/β-catenin/snail signaling
Bibliographic record
Abstract
Intratumoral heterogeneity greatly hinders efficiency of target therapy in glioblastoma (GBM). To decipher the underlying mechanisms of heterogeneity, patient-derived adult GBM cells were separately isolated from margins of T1 gadolinium enhancing tumor lesions (PNCs) and T1 gadolinium enhancing core lesions (ECs). Single clone culture was conducted in ECs and U87MG cell line to screen clones with distinct biological phenotypes. Single cell clones with diverse phenotypes were simultaneously separated from ECs and U87 cell line. PNCs, GCs(H) and U87(H) exhibited longer cellular protrusion than ECs, GCs(L) and U87(L), respectively. Cell strains with longer protrusion exhibited higher invasive ability and lower sensitivity to temozolomide (TMZ) and radiation. Subsequently, TPD52L2 was verified as the functional protein to regulate the cellular heterogeneity by the proteomics analysis. Downregulation of TPD52L2 enhanced cell invasion whereas inhibited cell proliferation rate and sensitivity to chemotherapy in vivo and in vitro, this condition was reversed when TPD52L2 was overexpressed. The invasiveness was facilitated by up-regulating CTNNB1/β-catenin and SNAI1/Snail mediated EMT process. In addition, the clinical data of 88 GBM cases in our neurosurgery center was analyzed to reveal the influence of TPD52L2 in the prognosis of GBM. Low expression of TPD52L2 exacerbated prognosis of GBM patients received standard radiotherapy plus concomitant and adjuvant TMZ (Stupp strategy). Taken together, TPD52L2 is an important biomarker influencing GBM prognosis.
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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".