Background <p>T/myeloid mixed-phenotype acute leukemia (T/My MPAL) is a malignant disease characterized by co-expression of lymphoid and myeloid features. The lack of molecular classification of T/My MPAL results in highly heterogeneity in treatment responses and clinical outcomes. Identifying molecular subtypes and developing subtype-specific treatment strategies are crucial for improving prognosis and enabling personalized therapies.</p> Methods <p>We constructed a single-cell transcriptomic landscape of T/My MPAL, acute myeloid leukemia (AML), T-cell acute lymphoid leukemia (T-ALL), and normal donors by analyzing nearly 275,000 cells. Malignant cells were identified using lineage-specific markers and healthy reference datasets. By comparing the whole transcriptomic profiles of T/My MPAL malignant cells with those of AML and T-ALL, we defined three distinct subpopulations and uncovered both intra- and inter-tumoral heterogeneity. Subpopulation-specific molecular markers were identified and validated using immunohistochemistry and independent datasets. These markers were further linked to clinical outcomes. Finally, potential subpopulation-specific therapeutic drugs were identified by correlating gene signatures with IC<sub>50</sub> values.</p> Results <p>Malignant cells in T/My MPAL display distinct lineage characteristics and experience differentiation arrest at a more primitive stage compared to other leukemias. Biphenotypic and bilineal MPAL subtypes defined by flow cytometry exhibit similar transcriptomic profiles, indicating the traditional classification based on a limited set of lineage markers is insufficient. Instead, we define three subpopulations of malignant cells in T/My MPAL, including AML-like, T-ALL-like, and a unique subpopulation that shows distinct transcriptional characteristics neither similar to AML nor to ALL. Markers for each subpopulation are identified and further validated by independent datasets and immunohistochemistry. The unique subpopulation exhibits higher stemness and quiescence, with elevated <i>HOPX</i> expression. Notably, patients with higher levels of the unique subpopulation have significantly poorer prognoses. We further computationally screen potential drugs targeting each subpopulation and indicate that Venetoclax could effectively inhibit the unique MPAL subpopulation and help patient achieve complete remission.</p> Conclusions <p>Our study provides new insights into the molecular heterogeneity and offers personalized diagnostic and therapeutic targets for T/My MPAL patients. These findings offer valuable insights for enhancing patient outcomes and developing personalized treatment strategies.</p>

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Single-cell transcriptome analysis defines novel molecular subtypes and reveals therapeutic implications of T/myeloid mixed-phenotype acute leukemia

  • Bin Huang,
  • Wenjie Liu,
  • Yuxin Du,
  • Ping Liu,
  • Zixing Lu,
  • Shiyang Zhong,
  • Xingfei Hu,
  • Wanting Zhou,
  • Yuzhu Shi,
  • Runheng Huang,
  • Xian Zhang,
  • Jinning Shi,
  • Chuanyang Lu,
  • Chunling Wang,
  • Liang Yu,
  • Lingxiang Wu,
  • Wei Wu,
  • Peng Xia,
  • Qian Sun,
  • Liwei Zhu,
  • Zhi Wang,
  • Ruohan Zhang,
  • Xinrui Lin,
  • Sali Lv,
  • Qianghu Wang,
  • Sixuan Qian,
  • Kening Li,
  • Ming Hong

摘要

Background

T/myeloid mixed-phenotype acute leukemia (T/My MPAL) is a malignant disease characterized by co-expression of lymphoid and myeloid features. The lack of molecular classification of T/My MPAL results in highly heterogeneity in treatment responses and clinical outcomes. Identifying molecular subtypes and developing subtype-specific treatment strategies are crucial for improving prognosis and enabling personalized therapies.

Methods

We constructed a single-cell transcriptomic landscape of T/My MPAL, acute myeloid leukemia (AML), T-cell acute lymphoid leukemia (T-ALL), and normal donors by analyzing nearly 275,000 cells. Malignant cells were identified using lineage-specific markers and healthy reference datasets. By comparing the whole transcriptomic profiles of T/My MPAL malignant cells with those of AML and T-ALL, we defined three distinct subpopulations and uncovered both intra- and inter-tumoral heterogeneity. Subpopulation-specific molecular markers were identified and validated using immunohistochemistry and independent datasets. These markers were further linked to clinical outcomes. Finally, potential subpopulation-specific therapeutic drugs were identified by correlating gene signatures with IC50 values.

Results

Malignant cells in T/My MPAL display distinct lineage characteristics and experience differentiation arrest at a more primitive stage compared to other leukemias. Biphenotypic and bilineal MPAL subtypes defined by flow cytometry exhibit similar transcriptomic profiles, indicating the traditional classification based on a limited set of lineage markers is insufficient. Instead, we define three subpopulations of malignant cells in T/My MPAL, including AML-like, T-ALL-like, and a unique subpopulation that shows distinct transcriptional characteristics neither similar to AML nor to ALL. Markers for each subpopulation are identified and further validated by independent datasets and immunohistochemistry. The unique subpopulation exhibits higher stemness and quiescence, with elevated HOPX expression. Notably, patients with higher levels of the unique subpopulation have significantly poorer prognoses. We further computationally screen potential drugs targeting each subpopulation and indicate that Venetoclax could effectively inhibit the unique MPAL subpopulation and help patient achieve complete remission.

Conclusions

Our study provides new insights into the molecular heterogeneity and offers personalized diagnostic and therapeutic targets for T/My MPAL patients. These findings offer valuable insights for enhancing patient outcomes and developing personalized treatment strategies.