Krotee, L. | Search bioRxiv

bioRxiv2025

Dynamic BH3 profiling predicts clinical outcomes in acute myeloid leukemia

Predictive biomarkers can potentially meet the need for improved drug assignment in acute myeloid leukemia (AML). Fewer than half of AML patients have actionable mutations: consequently, targeted therapy achieves remission in only a fraction of those who have them. Dynamic BH3 Profiling (DBP), a functional assay, can measure changes in ex vivo drug-induced apoptotic priming in multiple cancers. To assess the feasibility and predictive capacity of DBP in AML, we prospectively tested DBP using a fixed-drug panel in myeloblasts from 92 patients. We generated a database combining genetic and functional annotation. Established AML clinical and genetic prognostic characteristics were associated with drug-induced apoptotic priming. We observed distinct interpatient sensitivities to single drugs or combinations with the BCL2-inhibitor venetoclax, and intrapatient apoptotic priming differences based on CD123-expression within distinct cell subpopulations. DBP further predicted the likelihood of remission to chemotherapy and targeted agents, supporting its use to identify optimal personalized therapy. Statement of significanceDynamic BH3 profiling provides patient-specific drug vulnerability data in real-time to inform prognosis and therapy selection. Key takeawaysO_LIDynamic BH3 profiling can be performed on bone marrow and leukemic blood from AML patients in 48 hours. C_LIO_LIKnown clinical prognostic factors associate with drug-induced apoptotic priming in AML. C_LIO_LIDrug-induced apoptotic priming identifies drug vulnerabilities in individual patients and predicts clinical response to chemotherapy and small molecule inhibitors. C_LI

cancer biology↗

bioRxiv2025

Drug tolerant persisters and immunotherapy persister cells exhibit cross-resistance and share common survival mechanisms

Persisters are a rare sub-population of tumor cells that survive anti-cancer therapy and are thought to be a major cause of recurrence. These cells have been identified following both drug- and immune-therapy but are generally considered to be distinct entities. Since both pharmacological agents and immune cells often kill via apoptosis, we tested a hypothesis that both types of cells survive based on reduced mitochondrial apoptotic sensitivity, which in turn would yield a similar and reciprocal multi-agent resistant phenotype. Supporting this hypothesis, we indeed observed that IPCs acquired a reduced sensitivity to multiple drug classes and radiotherapy, suggesting non-immune mechanisms are important in the survival of cancer cells after immunotherapy. Likewise, DTPs developed not only a reduced sensitivity to multiple drug classes and radiotherapy, but also acquired a reduced sensitivity to T cell killing. Both IPCs and DTPs developed a decreased sensitivity to mitochondrial apoptosis. A sub-population of IPCs downregulated antigen and upregulated PD-L1. Intriguingly, in the IPCs that didnt employ these mechanisms of resistance, a greater decrease in sensitivity to mitochondrial apoptosis was observed, suggesting that the presence or absence of a resistance mechanism can exert selective pressures over the emergence of others. Targeting anti-apoptotic dependencies in persisters increased sensitivity to chemotherapy or CAR T therapy. These results suggest that common biological mechanisms underly survival of persisters, whether derived from immune or drug therapy, and offer an explanation for the acquired cross-resistance to these two types of therapies often observed in the clinic. HighlightsO_LIImmunotherapy persister cells (IPCs) are less sensitive to drugs and radiation. C_LIO_LIDrug tolerant persisters (DTPs) are less sensitive to radiation and CAR T cell attack. C_LIO_LIIPCs and DTPs are less sensitive to mitochondrial apoptosis. C_LIO_LITargeting anti-apoptotic dependencies helps eliminate IPCs/DTPs. C_LI Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/641492v2_ufig1.gif" ALT="Figure 1"> View larger version (52K): org.highwire.dtl.DTLVardef@fe98b4org.highwire.dtl.DTLVardef@db7bfdorg.highwire.dtl.DTLVardef@1a94469org.highwire.dtl.DTLVardef@1ca6b2c_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗