MAGIC-DR: An interpretable machine-learning guided approach for acute myeloid leukemia measurable residual disease analysis.

Multiparameter flow cytometry is widely used for acute myeloid leukemia minimal residual disease testing (AML MRD) but is time consuming and demands substantial expertise. Machine learning offers potential advancements in accuracy and efficiency, but has yet to be widely adopted for this application. To explore this, we trained single cell XGBoost classifiers from 98 diagnostic AML cell populations and 30 MRD negative samples. Performance was assessed by cross-validation. Predictions were integrated with UMAP as a heatmap parameter for an augmented/interactive AML MRD analysis framework, which was benchmarked against traditional MRD analysis for 25 test cases. The results showed that XGBoost achieved a median AUC of 0.97, effectively distinguishing diverse AML cell populations from normal cells. When integrated with UMAP, the classifiers highlighted MRD populations against the background of normal events. Our pipeline, MAGIC-DR, incorporated classifier predictions and UMAP into flow cytometry standard (FCS) files. This enabled a human-in-the-loop machine learning guided MRD workflow. Validation against conventional analysis for 25 MRD samples showed 100% concordance in myeloid blast detection, with MAGIC-DR also identifying several immature monocytic populations not readily found by conventional analysis. In conclusion, Integrating a supervised classifier with unsupervised dimension reduction offers a robust method for AML MRD analysis that can be seamlessly integrated into conventional workflows. Our approach can support and augment human analysis by highlighting abnormal populations that can be gated on for quantification and further assessment. This has the potential to speed up MRD analysis, and potentially improve detection sensitivity for certain AML immunophenotypes.

Efficacy and safety of Kumpe access catheter for pre-percutaneous nephrolithotomy renal access in modified supine percutaneous nephrolithotomy.

INTRODUCTION: Traditionally, a pigtail catheter (PCN) is placed for preoperative renal access before performing percutaneous nephrolithotomy (PCNL). However, PCN can hamper the passage of the guidewire to the ureter, due to which, access tract can be lost. Therefore, Kumpe Access Catheter (KMP) has been proposed for preoperative renal access before PCNL. In this study, we analyzed the efficacy and safety of KMP for surgical outcomes in modified supine PCNL compared to those in PCN. MATERIALS AND METHODS: From July 2017 to December 2020, 232 patients underwent modified supine PCNL at a single tertiary center, of which 151 patients were enrolled in this study after excluding patients who underwent bilateral surgery, multiple punctures, or combined operations. Enrolled patients were divided into two groups according to the type of pre-PCNL nephrostomy catheter used: PCN versus KMP. A pre-PCNL nephrostomy catheter was selected based on the radiologist's preference. A single surgeon performed all PCNL procedures. Patient characteristics and surgical outcomes, including stone-free rate, operation time, radiation exposure time (RET), and complications, were compared between the two groups. RESULTS: Of the 151 patients, 53 underwent PCN placement, and 98 underwent KMP placement for pre-PCNL nephrostomy. Patient baseline characteristics were comparable between the two groups, except for the renal stone type and multiplicity. The operation time, stone-free rate, and complication rate were not significantly different between the two groups; however, RET was significantly shorter in the KMP group. CONCLUSION: The surgical outcomes of KMP placement were comparable to those of PCN and showed shorter RET during modified supine PCNL. Based on our results, we recommend KMP placement for pre-PCNL nephrostomy, particularly for reducing RET during supine PCNL.

Single-cell profiling reveals a memory B cell-like subtype of follicular lymphoma with increased transformation risk.

Follicular lymphoma (FL) is an indolent cancer of mature B-cells but with ongoing risk of transformation to more aggressive histology over time. Recurrent mutations associated with transformation have been identified; however, prognostic features that can be discerned at diagnosis could be clinically useful. We present here comprehensive profiling of both tumor and immune compartments in 155 diagnostic FL biopsies at single-cell resolution by mass cytometry. This revealed a diversity of phenotypes but included two recurrent patterns, one which closely resembles germinal center B-cells (GCB) and another which appears more related to memory B-cells (MB). GCB-type tumors are enriched for EZH2, TNFRSF14, and MEF2B mutations, while MB-type tumors contain increased follicular helper T-cells. MB-type and intratumoral phenotypic diversity are independently associated with increased risk of transformation, supporting biological relevance of these features. Notably, a reduced 26-marker panel retains sufficient information to allow phenotypic profiling of future cohorts by conventional flow cytometry.

Inferences in microbial structural signatures of acne microbiome and mycobiome.

Acne vulgaris, commonly known as acne, is the most common skin disorder and a multifactorial disease of the sebaceous gland. Although the pathophysiology of acne is still unclear, bacterial and fungal factors are known to be involved in. This study aimed to investigate whether the microbiomes and mycobiomes of acne patients are distinct from those of healthy subjects and to identify the structural signatures of microbiomes related to acne vulgaris. A total of 33 Korean female subjects were recruited (Acne group, n = 17; Healthy group, n = 16), and microbiome samples were collected swabbing the forehead and right cheek. To characterize the fungal and bacterial communities, 16S rRNA V4-V5 and ITS1 region, respectively, were sequenced and analysed using Qiime2. There were no significant differences in alpha and beta diversities of microbiomes between the Acne and Healthy groups. In comparison with the ratio of Cutibacterium to Staphylococcus, the acne patients had higher abundance of Staphylococcus compared to Cutibacterium than the healthy individuals. In network analysis with the dominant microorganism amplicon sequence variants (ASV) (Cutibacterium, Staphylococcus, Malassezia globosa, and Malassezia restricta) Cutibacterium acnes was identified to have hostile interactions with Staphylococcus and Malassezia globosa. Accordingly, this results suggest an insight into the differences in the skin microbiome and mycobiome between acne patients and healthy controls and provide possible microorganism candidates that modulate the microbiomes associated to acne vulgaris.

Single-Cell Transcriptome Analysis Reveals Disease-Defining T-cell Subsets in the Tumor Microenvironment of Classic Hodgkin Lymphoma.

Hodgkin lymphoma is characterized by an extensively dominant tumor microenvironment (TME) composed of different types of noncancerous immune cells with rare malignant cells. Characterization of the cellular components and their spatial relationship is crucial to understanding cross-talk and therapeutic targeting in the TME. We performed single-cell RNA sequencing of more than 127,000 cells from 22 Hodgkin lymphoma tissue specimens and 5 reactive lymph nodes, profiling for the first time the phenotype of the Hodgkin lymphoma-specific immune microenvironment at single-cell resolution. Single-cell expression profiling identified a novel Hodgkin lymphoma-associated subset of T cells with prominent expression of the inhibitory receptor LAG3, and functional analyses established this LAG3+ T-cell population as a mediator of immunosuppression. Multiplexed spatial assessment of immune cells in the microenvironment also revealed increased LAG3+ T cells in the direct vicinity of MHC class II-deficient tumor cells. Our findings provide novel insights into TME biology and suggest new approaches to immune-checkpoint targeting in Hodgkin lymphoma. SIGNIFICANCE: We provide detailed functional and spatial characteristics of immune cells in classic Hodgkin lymphoma at single-cell resolution. Specifically, we identified a regulatory T-cell-like immunosuppressive subset of LAG3+ T cells contributing to the immune-escape phenotype. Our insights aid in the development of novel biomarkers and combination treatment strategies targeting immune checkpoints.See related commentary by Fisher and Oh, p. 342.This article is highlighted in the In This Issue feature, p. 327.