Abstract A022: Immunotherapy of IL-6R Prevents Relapse and Metastasis of Triple-Negative Breast Cancer
Bibliographic record
Abstract
Abstract Multiple Copies in T-cell Malignancy-1 (MCT-1 or MCTS1) is a prognostic biomarker for aggressive breast cancers. Overexpressed MCT-1 stimulates the IL-6/IL-6R/gp130/STAT3 axis, promoting epithelial-to-mesenchymal transition, cancer cell stemness and tumor progression. To study the mechanism underlying TNBC immunity and aggressiveness, TNBC cell lines with different MCT-1 expression levels were evaluated. Primary tumor invasion and postsurgical local recurrence and distant metastasis were assessed in orthotopic syngeneic mice given indicated immunotherapy and/or MCT-1 silencing (shMCT-1). We found that shMCT-1 suppresses the transcriptome of inflammatory response and metastatic signaling in TNBC cells and inhibits TNBC progression, metastasis and mortality in xenograft mice. Combined IL-6R immunotherapy and shMCT-1 effect further decreased intratumoral M2 macrophages and T regulatory cells (Tregs) and avoided postsurgical TNBC expansion. Multiple positive feedback loops of the MCT-1/IL-6/IL-6R/CXCL7/PD-L1 axis were identified in TNBC cells, which boost metastatic niches and immunosuppressive microenvironments. MCT-1high/PD-L1high/CXCL7high and CXCL7high/IL-6high/IL-6Rhigh expression patterns predict worse prognosis and poorer survival in breast cancer patients. IL-6R-based immunotherapy more effectively prevented postsurgical TNBC metastasis, recurrence and mortality than anti-PD-L1 immunotherapy. Anti-IL-6R improved helper T, cytotoxic T and natural killer (NK) cells in lymphatic system and decreased Tregs in the recurrent and metastatic tumors, but anti-PD-L1 incapably elevated NK cells. Combined IL-6R and PD-L1 immunotherapies abridged TNBC cell stemness and M2 macrophage activity better than monotherapy. Sequential immunotherapy of PD-L1 and IL-6R demonstrated the best survival outcome, lowest postoperative recurrence and metastasis than synchronized therapy, particularly in shMCT-1 context. Conclusion: Systemic targeting of the MCT-1/IL-6/IL-6R/CXCL7/PD-L1 interconnection enhances the immune surveillance that inhibits aggressiveness of TNBC. Citation Format: Aushia Tanzih Al Haq, Pao-Pao Yang, Christopher Jin, Jou-Ho Shih, Li-Mei Chen, Lu-Hai Wang, Michael P. Snyder, Hsin-Ling Hsu. Immunotherapy of IL-6R Prevents Relapse and Metastasis of Triple-Negative Breast Cancer [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Tumor Immunology and Immunotherapy; 2023 Oct 1-4; Toronto, Ontario, Canada. Philadelphia (PA): AACR; Cancer Immunol Res 2023;11(12 Suppl):Abstract nr A022.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".