Antitumor Effect of Large Doses IL-2-Activated HLA Haploidentical Peripheral Blood Stem Cells on Refractory Metastatic Solid Tumor Treatment
Bibliographic record
Abstract
OBJECTIVE: The traditional immunotherapy for patients with refractory metastatic solid tumors is limited because tumors induce immunosuppression. New treatment is, therefore, needed. The aim of this study was to evaluate the clinical efficacy of infusion of high-dose interleukin (IL)-2-activated allogeneic haploidentical peripheral blood stem cells (haplo-PBSCTs) on patients with an advanced stage of refractory solid tumors. METHODS: This study involved 11 patients with refractory metastatic tumors and haploidentical relatives as donors for haplo-PBSCs. The therapeutic outcome of the IL-2-activated haplo-PBSC infusion and patients' cytokine levels were evaluated. The cytotoxicity of IL-2-activated haplo-PBSCs for tumor cells was determined using in vitro cytotoxicity assays. RESULTS: A range from 2.5 to 5.6 x 10(10) of activated haplo-PBSCs were harvested after exposure to rhIL-2, along with a significant increase in the proportion of natural killer (NK) cells and activated lymphocytes (CD69+ and CD25+), and enhanced cytotoxicity of haplo-PBSCs for several tumor cell lines. Following treatment, 1 (1/11) patient achieved a partial response (PR), 1 (1/11) achieved a mild response (MR), 6 (6/11) achieved stable disease (SD), and 3 (3/11) achieved progressive disease (PD). For all of the 11 patients, the median progression-free survival (PFS) was 5 months (3-14 months). We also observed the phenomenon of Th2 shifted to Th1, which played a crucial role in cancer immunotherapy. CONCLUSIONS: The adoptive transfusion of IL-2-activated haplo-PBSCs has potent antitumor effects both in vitro and in vivo. This finding suggests that IL-2-activated haplo-PBSCs may serve as an alternative therapy for advanced-stage solid tumors, especially for those patients who are refractory or ineligible for chemo- or radiotherapy.
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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".