Potential Applications for Circulating Tumor Cells Expressing the Insulin-Like Growth Factor-I Receptor
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Bibliographic record
Abstract
PURPOSE: To detect insulin-like growth factor-IR (IGF-IR) on circulating tumor cells (CTC) as a biomarker in the clinical development of a monoclonal human antibody, CP-751,871, targeting IGF-IR. EXPERIMENTAL DESIGN: An automated sample preparation and analysis system for enumerating CTCs (CellTracks) was adapted for detecting IGF-IR-positive CTCs with a diagnostic antibody targeting a different IGF-IR epitope to CP-751,871. This assay was used in three phase I trials of CP-751,871 as a single agent or with chemotherapy and was validated using cell lines and blood samples from healthy volunteers and patients with metastatic carcinoma. RESULTS: There was no interference between the analytic and therapeutic antibodies. Eighty patients were enrolled on phase I studies of CP-751,871, with 47 (59%) patients having CTCs detected during the study. Before treatment, 26 patients (33%) had CTCs, with 23 having detectable IGF-IR-positive CTCs. CP-751,871 alone, and CP-751,871 with cytotoxic chemotherapy, decreased CTCs and IGF-IR-positive CTCs; these increased toward the end of the 21-day cycle in some patients, falling again with retreatment. CTCs were commonest in advanced hormone refractory prostate cancer (11 of 20). Detectable IGF-IR expression on CTCs before treatment with CP-751,871 and docetaxel was associated with a higher frequency of prostate-specific antigen decline by >50% (6 of 10 versus 2 of 8 patients). A relationship was observed between sustained decreases in CTC counts and prostate-specific antigen declines by >50%. CONCLUSIONS: IGF-IR expression is detectable by immunofluorescence on CTCs. These data support the further evaluation of CTCs in pharmacodynamic studies and patient selection, particularly in advanced prostate cancer.
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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 | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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 it