Somatostatin Receptor Ligand Therapy—A Potential Therapy for Neurocytoma
Bibliographic record
Abstract
CONTEXT: Neurocytoma (NC) is a rare, low-grade tumor of the central nervous system, with a 10-year survival rate of 90% and local control rate of 74%. However, 25% of NCs will be atypical, with an elevated Ki-67 labeling index >2%, and will exhibit a more aggressive course, with a high propensity for local recurrence and/or craniospinal dissemination. Although no standard treatment regimen exists for these atypical cases, adjuvant stereotactic or conventional radiotherapy and/or chemotherapy have been typically offered but have yielded inconsistent results. CASE DESCRIPTION: We have described the case of a patient with a vasopressin-secreting atypical NC of the sellar and cavernous sinus region. After subtotal resection via endoscopic transsphenoidal surgery, the residual tumor showed increased fluorodeoxyglucose uptake and high somatostatin receptor (SSTR) expression on a 68Ga-DOTA-TATE positron emission tomography/CT scan. Somatostatin receptor ligand (SRL) therapy with lanreotide (120 mg every 28 days) was initiated. Four years later, the residual tumor was stable with decreased fluorodeoxyglucose tumor uptake. Immunocytochemical SSTR2 and SSTR5 expression >80% was further confirmed in a series of NC tissues. CONCLUSIONS: To the best of our knowledge, we have described the first use of SRL therapy for an atypical NC. Our results support consideration of adjuvant SRL therapy for NC refractory to surgical removal. Our findings further raise the possibility of SSTR-directed peptide receptor radionuclide therapy as NC therapy.
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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 | 0.000 |
| 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 | 0.001 | 0.001 |
| 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".