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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 IC 50 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.

Angioimmunoblastic T-cell lymphoma (AITL) is a kind of aggressive T-cell lymphoma with significant enrichment of non-malignant tumor microenvironment (TME) cells. However, the complexity of TME in AITL progression is poorly understood. We performed single-cell RNA-Seq (scRNA-seq) and imaging mass cytometry (IMC) analysis to compare the cellular composition and spatial architecture between relapsed/refractory AITL (RR-AITL) and newly diagnosed AITL (ND-AITL). Our results showed that the malignant T follicular helper (Tfh) cells showed significantly increased proliferation driven by transcriptional activation of YY1 in RR-AITL, which is markedly associated with the poor prognosis of AITL patients. The CD8 + T cell proportion and cytotoxicity decreased in RR-AITL TME, resulting from elevated expression of the inhibitory checkpoints such as PD-1, TIGIT, and CTLA4. Notably, the transcriptional pattern of B cells in RR-AITL showed an intermediate state of malignant transformation to B-cell-lymphoma, and contributed to immune evasion by highly expressing CD47 and PD-L1. Besides, compared to ND-AITL samples, myeloid-cells-centered spatial communities were more prevalent but showed reduced phagocytic activity and impaired antigen processing and presentation in RR-AITL TME. Furthermore, specific inhibitory ligand-receptor interactions, such as CLEC2D - KLRB1 , CTLA4 - CD86 , and MIF - CD74 , were exclusively identified in the RR-AITL TME. Our study provides a high-resolution characterization of the immunosuppression ecosystem and reveals the potential therapeutic targets for RR-AITL patients.

Previous studies have indicated that the downstream proteins in a key pathway can be potential drug targets and that the pathway can play an important role in the action of drugs. So pathways could be considered as targets of small molecules. A link map between small molecules and pathways was constructed using gene expression profile, pathways, and gene expression of cancer cell line intervened by small molecules and then we analysed the topological characteristics of the link map. Three link patterns were identified based on different drug discovery implications for breast, liver, and lung cancer. Furthermore, molecules that significantly targeted the same pathways tended to treat the same diseases. These results can provide a valuable reference for identifying drug candidates and targets in molecularly targeted therapy.

MicroRNAs (miRNAs) are a class of evolutionarily conserved small noncoding RNAs, ~22 nt in length, and found in diverse organisms and play important roles in the regulation of mRNA translation and degradation. It was shown that miRNAs were involved in many key biological processes through regulating the expression of targets. Genetic polymorphisms in miRNA target sites may alter miRNA regulation and therefore result in the alterations of the drug targets. Recent studies have demonstrated that SNPs in miRNA target sites can affect drug efficiency. However, there are still a large number of specific genetic variants related to drug efficiency that are yet to be discovered. We integrated large scale of genetic variations, drug targets, gene interaction networks, biological pathways, and seeds region of miRNA to identify miRNA polymorphisms affecting drug response. In addition, harnessing the abundant high quality biological network/pathways, we evaluated the cascade distribution of tarSNP impacts. We showed that the predictions can uncover most of the known experimentally supported cases as well as provide informative candidates complementary to existing methods/tools. Although there are several existing databases predicting the gain or loss of targeting function of miRNA mediated by SNPs, such as PolymiRTS, miRNASNP, MicroSNiPer, and MirSNP, none of them evaluated the influences of tarSNPs on drug response alterations. We developed a user-friendly online database of this approach named Mir2Drug.