Cancer Cell | 单细胞 TCR 联合免疫肽组解析骨髓肿瘤 T 细胞特征精准预测血液肿瘤免疫治疗疗效
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TL;DR - A Cancer Cell study combines single-cell RNA/TCR sequencing, functional screening, and HLA immunopeptidomics to characterize tumor-reactive T cells in multiple myeloma and acute myeloid leukemia. Its 15-gene TFiT classifier identifies these cells and predicts immunotherapy response, potentially enabling better patient stratification.
- Tumor-reactive bone-marrow T cells showed strong cytotoxic effector programs without the deep exhaustion commonly observed in solid tumors.
- Immunopeptidomics identified 17,161 HLA-bound peptides, largely from noncanonical rather than mutation-derived antigens.
- TFiT achieved an AUC of 0.895 in an independent cohort and outperformed published solid-tumor T-cell classifiers.
- TFiT predicted responses to BCMA×CD3 therapy in myeloma and nivolumab-based treatment in AML, but not standard AML chemotherapy.
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Cancer Cell | 单细胞 TCR 联合免疫肽组解析骨髓肿瘤 T 细胞特征精准预测血液肿瘤免疫治疗疗效
TL;DR - A Cancer Cell study combines single-cell RNA/TCR sequencing, functional screening, and HLA immunopeptidomics to characterize tumor-reactive T cells in multiple myeloma and acute myeloid leukemia. Its 15-gene TFiT classifier identifies these cells and predicts immunotherapy response, potentially enabling better patient stratification.
- Tumor-reactive bone-marrow T cells showed strong cytotoxic effector programs without the deep exhaustion commonly observed in solid tumors.
- Immunopeptidomics identified 17,161 HLA-bound peptides, largely from noncanonical rather than mutation-derived antigens.
- TFiT achieved an AUC of 0.895 in an independent cohort and outperformed published solid-tumor T-cell classifiers.
- TFiT predicted responses to BCMA×CD3 therapy in myeloma and nivolumab-based treatment in AML, but not standard AML chemotherapy.