Abstract B12: A novel gene signature associated with response to adoptively transferred T cells in a mouse model of breast cancer
Bibliographic record
Abstract
Abstract Introduction: Adoptive T cell therapy involves the infusion of large numbers of activated, tumor-reactive T cells. In clinical trials, this method often results in mixed responses, wherein some tumor nodules respond while others do not, indicating that the local tumor environment is a critical determinant of response. Aim: We sought to identify a gene expression signature associated with sensitivity of mammary tumors to adoptive T cell therapy in a mouse model of breast cancer. Materials and Methods: A transgenic mouse model was used to derive a panel of mammary tumor lines expressing an ovalbumin-tagged version of the HER-2/neu oncogene. Within the panel were tumor lines that reproducibly underwent complete regression (CR), partial regression (PR), or progressive disease (PD) after adoptive transfer of naive, ovalbumin-specific CD4+ (OT-II) and CD8+ (OT-I) T cells. Six representative tumors representing three outcome groups (CR, PR, and PD) underwent Affymetrix gene expression profiling, and results were validated by quantitative PCR. Results: Gene expression profiling identified four biological pathways associated with outcome following adoptive immunotherapy: leukocyte extravasation, extracellular matrix receptor, GM-CSF receptor, and LXR/RXR receptor pathways. From these pathways, 32 genes that ranked highest for discriminating CR and PD were chosen for further study. The tight junction protein Claudin 4 was expressed at high levels in PD tumors, intermediate levels in PR tumors, and low levels in CR tumors. By contrast, expression levels of the secreted extracellular matrix protein Reelin and the pro-inflammatory cytokine IL-18 were higher in CR tumors compared to PR and PD tumors. Conclusions: Pathways related to cell junctions, extracellular matrix and inflammation influence the response of mammary tumors to adoptively transferred T cells. Currently, we are modulating expression of these and other genes in mammary tumors to identify regulatory nodes that determine outcome and are amenable to therapeutic intervention. Funding: Canadian Institutes for Health Research, Michael Smith Foundation, BC Cancer Foundation Citation Information: Clin Cancer Res 2010;16(7 Suppl):B12
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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".