Correlation of primary tumor engraftment in immune deficient mice and relapse rate in patients with early-stage non-small cell lung carcinoma (NSCLC)
Bibliographic record
Abstract
11082 Background: Compared to cell lines, primary tumor xenografts potentially are more clinically relevant cancer models as they more closely reflect the phenotype and genotype of the original cancer. However, only a minority of tumors engraft successfully in severe combined immune deficient (scid) mice and can be passaged serially. Although xenograft models are used extensively, few studies have investigated whether tumors that engraft represent a distinct clinical subset. We hypothesized that NSCLC tumors with more aggressive clinical and histological features have greater engraftment capacity than those with a less aggressive phenotype. Methods: Fresh primary tumors were harvested from NSCLC patients who underwent curative resection. Tumor fragments were implanted into the subcutaneous tissue of non-obese diabetic-scid mice within 24 hrs of excision. Patient characteristics for tumors that engrafted (XG) and did not engraft (No-XG) were compared. Only tumors from patients with >1-yr follow-up were evaluated for time to progression (TTP) and to correlate clinicopathological features with engraftment. Results: Between March 2005 and October 2008, 110 tumors were implanted. Of these, 45 (41%) engrafted and were passaged serially in vivo. The histological features of the primary were retained in 93% of XG tumors. Squamous cell carcinomas engrafted significantly more than adenocarcinomas (57% versus 26%, p=0.03). There were no significant differences in differentiation grade or clinical stage between the XG and No-XG groups. XG patients had significantly shorter TTP than the No-XG group (10.19 versus 18.64 months, p=0.003). In multivariate analysis the ability to form a xenograft was an independent predictor of relapse (HR 4.15 95% CI 1.152–14.94, p=0.03). Conclusions: Xenograft models can be established from the histological spectra of NSCLC encountered in the clinical setting and mimic closely the features of their primary tumors. The capacity of these tumors to engraft may be predictive of a more aggressive phenotype and poorer clinical outcome. No significant financial relationships to disclose.
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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 | 0.000 | 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".