Mechanistic insights into the C-type lectin receptor CLEC12A-mediated immune recognition of monosodium urate crystal

CLEC12A, a member of the C-type lectin receptor family involved in immune homeostasis, recognizes MSU crystals released from dying cells. However, the molecular mechanism underlying the CLEC12A-mediated recognition of MSU crystals remains unclear. Herein, we reported the crystal structure of the human CLEC12A-C-type lectin-like domain (CTLD) and identified a unique "basic patch" site on CLEC12A-CTLD that is necessary for the binding of MSU crystals. Meanwhile, we determined the interaction strength between CLEC12A-CTLD and MSU crystals using single-molecule force spectroscopy. Furthermore, we found that CLEC12A clusters at the cell membrane and seems to serve as an internalizing receptor of MSU crystals. Altogether, these findings provide mechanistic insights for understanding the molecular mechanisms underlying the interplay between CLEC12A and MSU crystals.

Proteomic Profiling Identifies Specific Leukemic Stem Cell-Associated Protein Expression Patterns in Pediatric AML Patients

Simple Summary

Acute myeloid leukemia is an aggressive cancer in children and novel therapeutic tools are warranted to improve outcomes and reduce late effects in these patients. In this study, we isolate and explore the protein profiles of leukemic stem cells and normal hematopoietic stem cells from hematologically healthy children. Differences in protein profiles between leukemic and normal hematopoietic stem cells were identified. These results provide an insight into the disrupted biological pathways in childhood acute myeloid leukemia. Moreover, differences in protein profiles may serve as potential targets for future therapies specifically aiming at the disease-propagating leukemic stem cells while omitting the normal hematopoietic stem cells.

Abstract

Novel therapeutic tools are warranted to improve outcomes for children with acute myeloid leukemia (AML). Differences in the proteome of leukemic blasts and stem cells (AML-SCs) in AML compared with normal hematopoietic stem cells (HSCs) may facilitate the identification of potential targets for future treatment strategies. In this explorative study, we used mass spectrometry to compare the proteome of AML-SCs and CLEC12A+ blasts from five pediatric AML patients with HSCs and hematopoietic progenitor cells from hematologically healthy, age-matched controls. A total of 456 shared proteins were identified in both leukemic and control samples. Varying protein expression profiles were observed in AML-SCs and leukemic blasts, none having any overall resemblance to healthy counterpart cell populations. Thirty-four proteins were differentially expressed between AML-SCs and HSCs, including the upregulation of HSPE1, SRSF1, and NUP210, and the enrichment of proteins suggestive of protein synthesis perturbations through the downregulation of EIF2 signaling was found. Among others, NUP210 and calreticulin were upregulated in CLEC12A+ blasts compared with HSCs. In conclusion, the observed differences in protein expression between pediatric patients with AML and pediatric controls, in particular when comparing stem cell subsets, encourages the extended exploration of leukemia and AML-SC-specific biomarkers of potential relevance in the development of future therapeutic options in pediatric AML.

Immunophenotypically defined stem cell subsets in paediatric AML are highly heterogeneous and demonstrate differences in BCL-2 expression by cytogenetic subgroups

In adult acute myeloid leukaemia (AML), immunophenotypic differences enable discrimination of leukaemic stem cells (LSCs) from healthy haematopoietic stem cells (HSCs). However, immunophenotypic stem cell characteristics are less explored in paediatric AML. Employing a 15-colour flow cytometry assay, we analysed the expression of eight aberrant surface markers together with BCL-2 on CD34⁺ CD38^- bone marrow stem cells from 38 paediatric AML patients and seven non-leukaemic, age-matched controls. Furthermore, clonality was investigated by genetic analyses of sorted immunophenotypically abnormal stem cells from six patients. A total of 50 aberrant marker positive (non-HSC-like) subsets with 41 different immunophenotypic profiles were detected. CD123, CLEC12A, and IL1RAP were the most frequently expressed markers. IL1RAP, CD93, and CD25 expression were not restricted to stem cells harbouring leukaemia-associated mutations. Differential BCL-2 expression was found among defined cytogenetic subgroups. Interestingly, only immunophenotypically abnormal non-HSC-like subsets demonstrated BCL-2 overexpression. Collectively, we observed pronounced immunophenotypic heterogeneity within the stem cell compartment of paediatric AML patients. Additionally, certain aberrant markers used in adults seemed to be ineligible for detection of leukaemia-representing stem cells in paediatric patients implying that inference from adult studies must be done with caution.

Bimodal expression of potential drug target CLL-1 (CLEC12A) on CD34+ blasts of AML patients

Objectives

This study aims to retrospectively assess C‐lectin‐like molecule 1 (CLL‐1) bimodal expression on CD34+ blasts in acute myeloid leukemia (AML) patients (total N = 306) and explore potential CLL‐1 bimodal associations with leukemia and patient‐specific characteristics.

Methods

Flow cytometry assays were performed to assess the deeper immunophenotyping of CLL‐1 bimodality. Cytogenetic analysis was performed to characterize the gene mutation on CLL‐1‐negative subpopulation of CLL‐1 bimodal AML samples.

Results

The frequency of a bimodal pattern of CLL‐1 expression of CD34⁺ blasts ranged from 8% to 65% in the different cohorts. Bimodal CLL‐1 expression was most prevalent in patients with MDS‐related AML (P = .011), ELN adverse risk (P = .002), NPM1 wild type (WT, P = .049), FLT3 WT (P = .035), and relatively low percentages of leukemia‐associated immunophenotypes (P = .006). Additional immunophenotyping analysis revealed the CLL‐1⁻ subpopulation may consist of pre‐B cells, immature myeloblasts, and hematopoietic stem cells. Furthermore, (pre)‐leukemic mutations were detected in both CLL‐1⁺ and CLL‐1⁻ subfractions of bimodal samples (N = 3).

Conclusions

C‐lectin‐like molecule 1 bimodality occurs in about 25% of AML patients and the CLL‐1⁻ cell population still contains malignant cells, hence it may potentially limit the effectiveness of CLL‐1‐targeted therapies and warrant further investigation.

Cancer Stem Cells-Origins and Biomarkers: Perspectives for Targeted Personalized Therapies

The use of biomarkers in diagnosis, therapy and prognosis has gained increasing interest over the last decades. In particular, the analysis of biomarkers in cancer patients within the pre- and post-therapeutic period is required to identify several types of cells, which carry a risk for a disease progression and subsequent post-therapeutic relapse. Cancer stem cells (CSCs) are a subpopulation of tumor cells that can drive tumor initiation and can cause relapses. At the time point of tumor initiation, CSCs originate from either differentiated cells or adult tissue resident stem cells. Due to their importance, several biomarkers that characterize CSCs have been identified and correlated to diagnosis, therapy and prognosis. However, CSCs have been shown to display a high plasticity, which changes their phenotypic and functional appearance. Such changes are induced by chemo- and radiotherapeutics as well as senescent tumor cells, which cause alterations in the tumor microenvironment. Induction of senescence causes tumor shrinkage by modulating an anti-tumorigenic environment in which tumor cells undergo growth arrest and immune cells are attracted. Besides these positive effects after therapy, senescence can also have negative effects displayed post-therapeutically. These unfavorable effects can directly promote cancer stemness by increasing CSC plasticity phenotypes, by activating stemness pathways in non-CSCs, as well as by promoting senescence escape and subsequent activation of stemness pathways. At the end, all these effects can lead to tumor relapse and metastasis. This review provides an overview of the most frequently used CSC markers and their implementation as biomarkers by focussing on deadliest solid (lung, stomach, liver, breast and colorectal cancers) and hematological (acute myeloid leukemia, chronic myeloid leukemia) cancers. Furthermore, it gives examples on how the CSC markers might be influenced by therapeutics, such as chemo- and radiotherapy, and the tumor microenvironment. It points out, that it is crucial to identify and monitor residual CSCs, senescent tumor cells, and the pro-tumorigenic senescence-associated secretory phenotype in a therapy follow-up using specific biomarkers. As a future perspective, a targeted immune-mediated strategy using chimeric antigen receptor based approaches for the removal of remaining chemotherapy-resistant cells as well as CSCs in a personalized therapeutic approach are discussed.

High GPR56 surface expression correlates with a leukemic stem cell gene signature in CD34-positive AML

Acute myeloid leukemia (AML) is driven by a minor fraction of leukemic stem cells (LSCs) whose persistence is considered being the primary cause of disease relapse. A detailed characterization of the surface immunophenotype of LSCs to discriminate them from bulk leukemic blasts may enable successful targeting of this population thereby improving patient outcomes in AML. To identify surface markers, which may reflect LSC activity at diagnosis, we performed a detailed analysis of 16 putative LSC markers in CD34/38 leukemic subcompartments of 150 diagnostic AML samples using multicolor flow cytometry. The most promising markers were then selected to determine a possible correlation of their expression with a recently published LSC gene signature. We found GPR56 and CLL-1 to be the most prominently differently expressed surface markers in AML subcompartments. While GPR56 was highest expressed within the LSC-enriched CD34⁺ 38^- subcompartment as compared to CD34⁺ 38⁺ and CD34^- leukemic bulk cells, CLL-1 expression was lowest in CD34⁺ 38^- leukemic cells and increased in CD34⁺ 38⁺ and CD34^- blasts. Furthermore, high GPR56 surface expression in CD34⁺ 38^- leukemic cells correlated with a recently published LSC gene expression signature and was associated with decreased overall survival in patients receiving intensive chemotherapy. In contrast, CLL-1 expression correlated inversely with the LSC gene signature and was not informative on outcome. Our data strongly support GPR56 as a promising clinically relevant marker for identifying leukemic cells with LSC activity at diagnosis in CD34-positive AML.