Prediction of prognosis and immunotherapy response of amino acid metabolism genes in acute myeloid leukemia

Background

Amino acid (AA) metabolism plays a crucial role in cancer. However, its role in acute myeloid leukemia (AML) is still unavailable. We screened out AA metabolic genes, which related to prognosis, and analyzed their correlation with tumor immune microenvironment in AML.

Methods

We evaluated 472 amino acid metabolism-related genes in 132 AML patients. The predictive risk model was developed according to differentially expressed genes, univariate Cox and LASSO analyses. We validated the risk signature by survival analysis and independence tests. Single-sample gene set enrichment analysis (ssGSEA), tumor immune microenvironment (TME), tumor mutation burden (TMB), functional enrichment, and the IC50 of drugs were assessed to explore the correlations among the risk model, immunity, and drug sensitivity of AML.

Results

Six amino acid metabolism-related genes were confirmed to develop the risk model, including TRH, HNMT, TFEB, SDSL, SLC43A2, and SFXN3. The high-risk subgroup had an immune "hot" phenotype and was related to a poor prognosis. The high-risk group was also associated with more activity of immune cells, such as Tregs, had higher expression of some immune checkpoints, including PD1 and CTLA4, and might be more susceptible to immunotherapy. Xenobiotic metabolism, the reactive oxygen species (ROS) pathway, fatty acid metabolism, JAK/STAT3, and the inflammatory response were active in the high-risk subgroup. Furthermore, the high-risk subgroup was sensitive to sorafenib, selumetinib, and entospletinib. ssGSEA discovered that the processes of glutamine, arginine, tryptophan, cysteine, histidine, L-serine, isoleucine, threonine, tyrosine, and L-phenylalanine metabolism were more active in the high-risk subgroup.

Conclusion

This study revealed that AA metabolism-related genes were correlated with the immune microenvironment of AML patients and could predict the prognosis and immunotherapy response of AML patients.

Immune dysfunction signatures predict outcomes and define checkpoint blockade-unresponsive microenvironments in acute myeloid leukemia

BackgroundImmune exhaustion and senescence are dominant dysfunctional states of effector T cells and major hurdles for the success of cancer immunotherapy. In the current study, we characterized how acute myeloid leukemia (AML) promotes the generation of senescent-like CD8+ T cells and whether they have prognostic relevance.METHODSWe analyzed NanoString, bulk RNA-Seq and single-cell RNA-Seq data from independent clinical cohorts comprising 1,896 patients treated with chemotherapy and/or immune checkpoint blockade (ICB).ResultsWe show that senescent-like bone marrow CD8+ T cells were impaired in killing autologous AML blasts and that their proportion negatively correlated with overall survival (OS). We defined what we believe to be new immune effector dysfunction (IED) signatures using 2 gene expression profiling platforms and reported that IED scores correlated with adverse-risk molecular lesions, stemness, and poor outcomes; these scores were a more powerful predictor of OS than 2017-ELN risk or leukemia stem cell (LSC17) scores. IED expression signatures also identified an ICB-unresponsive tumor microenvironment and predicted significantly shorter OS.ConclusionThe IED scores provided improved AML-risk stratification and could facilitate the delivery of personalized immunotherapies to patients who are most likely to benefit.TRIAL REGISTRATIONClinicalTrials.gov; NCT02845297.FUNDINGJohn and Lucille van Geest Foundation, Nottingham Trent University's Health & Wellbeing Strategic Research Theme, NIH/NCI P01CA225618, Genentech-imCORE ML40354, Qatar National Research Fund (NPRP8-2297-3-494).

Immune landscapes predict chemotherapy resistance and immunotherapy response in acute myeloid leukemia

Acute myeloid leukemia (AML) is a molecularly and clinically heterogeneous hematological malignancy. Although immunotherapy may be an attractive modality to exploit in patients with AML, the ability to predict the groups of patients and the types of cancer that will respond to immune targeting remains limited. This study dissected the complexity of the immune architecture of AML at high resolution and assessed its influence on therapeutic response. Using 442 primary bone marrow samples from three independent cohorts of children and adults with AML, we defined immune-infiltrated and immune-depleted disease classes and revealed critical differences in immune gene expression across age groups and molecular disease subtypes. Interferon (IFN)-γ-related mRNA profiles were predictive for both chemotherapy resistance and response of primary refractory/relapsed AML to flotetuzumab immunotherapy. Our compendium of microenvironmental gene and protein profiles provides insights into the immuno-biology of AML and could inform the delivery of personalized immunotherapies to IFN-γ-dominant AML subtypes.

Flow cytometry and targeted immune transcriptomics identify distinct profiles in patients with chronic myeloid leukemia receiving tyrosine kinase inhibitors with or without interferon-α

Background

Tumor cells have evolved complex strategies to escape immune surveillance, a process which involves NK cells and T lymphocytes, and various immunological factors. Indeed, tumor cells recruit immunosuppressive cells [including regulatory T-cells (Treg), myeloid-derived suppressor cells (MDSC)] and express factors such as PD-L1. Molecularly targeted therapies, such as imatinib, have off-target effects that may influence immune function. Imatinib has been shown to modulate multiple cell types involved in anti-cancer immune surveillance, with potentially detrimental or favorable outcomes. Imatinib and other tyrosine kinase inhibitors (TKIs) in chronic myeloid leukemia (CML) have dramatically changed disease course. Our study aimed to characterize the different populations of the immune system in patients with CML affected by their treatment.

Methods

Forty-one patients with CML [33 treated with TKIs and 8 with TKIs plus interferon (IFN)-α] and 20 controls were enrolled in the present study. Peripheral blood populations of the immune system [referred to as the overview of immune system (OVIS) panel, Treg cells and MDSCs] and PD-1 expression were evaluated by flow cytometry. The immunological profile was assessed using the mRNA Pan-Cancer Immune Profiling Panel and a NanoString nCounter FLEX platform.

Results

Patients receiving combination therapy (TKIs + IFN-α) had lower numbers of lymphocytes, particularly T cells [838/µL (95% CI 594–1182)] compared with healthy controls [1500/µL (95% CI 1207 – 1865), p = 0.017]. These patients also had a higher percentage of Treg (9.1%) and CD4⁺PD-1⁺ cells (1.65%) compared with controls [Treg (6.1%) and CD4⁺/PD-1⁺(0.8%); p ≤ 0.05]. Moreover, patients treated with TKIs had more Mo-MDSCs (12.7%) whereas those treated with TKIs + IFN-α had more Gr-MDSC (21.3%) compared to controls [Mo-MDSC (11.4%) and Gr-MDSC (8.48%); p ≤ 0.05]. CD56^bright NK cells, a cell subset endowed with immune-regulatory properties, were increased in patients receiving TKIs plus IFN-α compared with those treated with TKIs alone. Interestingly, serum IL-21 was significantly lower in the TKIs plus IFN-α cohort. Within the group of patients treated with TKI monotherapy, we observed that individuals receiving 2nd generation TKIs had lower percentages of CD4⁺ Treg (3.63%) and Gr-MDSC (4.2%) compared to patients under imatinib treatment (CD4⁺ Treg 6.18% and Gr-MDSC 8.2%), but higher levels of PD-1-co-expressing CD4⁺ cells (1.92%).

Conclusions

Our results suggest that TKIs in combination with IFN-α may promote an enhanced immune suppressive state.

AML through the prism of molecular genetics

Modern management of acute myeloid leukaemia (AML) relies on the integration of phenotypic and genetic data to assign classification, establish prognosis, enhance monitoring and guide treatment. The prism through which we can now disperse a patient's leukaemia, interpret and apply our understanding has fundamentally changed since the completion of the first whole-genome sequencing (WGS) of an AML patient in 2008 and where possible, many clinicians would now prefer to delay treatment decisions until the karyotype and genetic status of a new patient is known. The success of global sequencing initiatives such as The Cancer Genome Atlas (TCGA) have brought us significantly closer to cataloguing the full spectrum of coding mutations involved in human malignancy. Indeed, genetic capability has raced ahead of our capacity to apply much of this knowledge into clinical practice and we are in the peculiar position of having routine access to genetic information on an individual patient's leukaemia that cannot be reliably interpreted or utilised. This is a measure of how rapid the progress has been, and this rate of change is likely to continue into the foreseeable future as research intensifies on the non-coding genome and the epigenome, as we scrutinise disease at a single cell level, and as initiatives like Beat AML and the Harmony Alliance progress. In this review, we will examine how interrogation of the coding genome is revolutionising our understanding of AML and improving our ability to underscore differences between paediatric and adult onset, sporadic and inherited forms of disease. We will look at how this knowledge is informing improvements in outcome prediction and the development of novel treatments, bringing us a step closer to personalised therapy for myeloid malignancy.

Dissecting the Immune Landscape of Acute Myeloid Leukemia

Acute myeloid leukemia (AML) is a molecularly heterogeneous hematological malignancy with variable response to treatment. Recurring cytogenetic abnormalities and molecular lesions identify AML patient subgroups with different survival probabilities; however, 50⁻70% of AML cases harbor either normal or risk-indeterminate karyotypes. The discovery of better biomarkers of clinical success and failure is therefore necessary to inform tailored therapeutic decisions. Harnessing the immune system against cancer with programmed death-1 (PD-1)-directed immune checkpoint blockade (ICB) and other immunotherapy agents is an effective therapeutic option for several advanced malignancies. However, durable responses have been observed in only a minority of patients, highlighting the need to gain insights into the molecular features that predict response and to also develop more effective and rational combination therapies that address mechanisms of immune evasion and resistance. We will review the state of knowledge of the immune landscape of AML and identify the broad opportunity to further explore this incompletely characterized space. Multiplexed, spatially-resolved immunohistochemistry, flow cytometry/mass cytometry, proteomic and transcriptomic approaches are advancing our understanding of the complexity of AML-immune interactions and are expected to support the design and expedite the delivery of personalized immunotherapy clinical trials.