Tumor platinum concentrations and pathological responses following preoperative cisplatin-containing chemotherapy in gastric or gastroesophageal junction cancer patients.
Bibliographic record
Abstract
76 Background: Perioperative chemotherapy plus surgical resection is a standard of care for locally advanced gastric or gastroesophageal junction (GEJ) cancers. There is a wide range in tumor response following cisplatin-containing preoperative chemotherapy. We investigated the relationship between tumor platinum levels and pathological tumor responses in gastric or GEJ cancer patients following preoperative chemotherapy. Methods: Tumor and adjacent normal tissues were retrieved. Pathological responses were assessed per standard criteria. Tissue platinum concentrations were determined with high-performance liquid chromatography mass spectrometry. Platinum distribution in tissue components was evaluated with imaging mass cytometry. Tissue collagen content was evaluated using trichrome staining. Results: Ten patients were enrolled in this study. Nine patients received 3 cycles of preoperative chemotherapy and 1 received 2 cycles. The median cumulative cisplatin dose was 166.8 mg/m2 (range: 95.9–181.1 mg/m2). Surgery was performed at a median time of 49 days (range: 28–72 days) after the last cycle of chemotherapy. The mean platinum level in tumor tissue in patients with any response was 893 ± 460 pg, significantly higher than in those with no response [38.8 ± 8.8 pg (p = 0.007)]. The collagen content was significantly higher in patients with any response than in those with no response (37.4 ± 6.8% vs. 11.5 ± 8.6%, p < 0.05). Platinum preferentially bound to collagen. Conclusions: Platinum was detectable in surgical specimens up to 72 days after preoperative chemotherapy. Higher tumor platinum concentration correlated with improved pathological response. Collagen binding potentially explained the high interpatient variability in tumor platinum concentrations.
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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 | 0.000 | 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) | 0.001 | 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".