Single cell view of tumor microenvironment gradients in pleural mesothelioma.

Immunotherapies have shown great promise in pleural mesothelioma (PM), yet most patients still do not achieve significant clinical response, highlighting the importance of improving understanding of the tumor microenvironment (TME). Here, we utilized high-throughput, single-cell RNA-sequencing to de novo identify 54 expression programs and construct a comprehensive cellular catalogue of the PM TME. We found four cancer-intrinsic programs associated with poor disease outcome and a novel fetal-like, endothelial cell population that likely responds to VEGF signaling and promotes angiogenesis. Throughout cellular compartments, we observe substantial difference in the TME associated with a cancer-intrinsic sarcomatoid signature, including enrichment in fetal-like endothelial cells, CXCL9+ macrophages, cytotoxic, exhausted, and regulatory T cells, which we validated using imaging and bulk deconvolution analyses on independent cohorts. Finally, we show, both computationally and experimentally, that NKG2A-HLA-E interaction between NK and tumor cells represents an important new therapeutic axis in PM, especially for epithelioid cases.

Deep learning for colorectal cancer detection in contrast-enhanced CT without bowel preparation: a retrospective, multicentre study.

BACKGROUND: Contrast-enhanced CT scans provide a means to detect unsuspected colorectal cancer. However, colorectal cancers in contrast-enhanced CT without bowel preparation may elude detection by radiologists. We aimed to develop a deep learning (DL) model for accurate detection of colorectal cancer, and evaluate whether it could improve the detection performance of radiologists. METHODS: We developed a DL model using a manually annotated dataset (1196 cancer vs 1034 normal). The DL model was tested using an internal test set (98 vs 115), two external test sets (202 vs 265 in 1, and 252 vs 481 in 2), and a real-world test set (53 vs 1524). We compared the detection performance of the DL model with radiologists, and evaluated its capacity to enhance radiologists' detection performance. FINDINGS: In the four test sets, the DL model had the area under the receiver operating characteristic curves (AUCs) ranging between 0.957 and 0.994. In both the internal test set and external test set 1, the DL model yielded higher accuracy than that of radiologists (97.2% vs 86.0%, p < 0.0001; 94.9% vs 85.3%, p < 0.0001), and significantly improved the accuracy of radiologists (93.4% vs 86.0%, p < 0.0001; 93.6% vs 85.3%, p < 0.0001). In the real-world test set, the DL model delivered sensitivity comparable to that of radiologists who had been informed about clinical indications for most cancer cases (94.3% vs 96.2%, p > 0.99), and it detected 2 cases that had been missed by radiologists. INTERPRETATION: The developed DL model can accurately detect colorectal cancer and improve radiologists' detection performance, showing its potential as an effective computer-aided detection tool. FUNDING: This study was supported by National Science Fund for Distinguished Young Scholars of China (No. 81925023); Regional Innovation and Development Joint Fund of National Natural Science Foundation of China (No. U22A20345); National Natural Science Foundation of China (No. 82072090 and No. 82371954); Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application (No. 2022B1212010011); High-level Hospital Construction Project (No. DFJHBF202105).

A single-cell atlas characterizes dysregulation of the bone marrow immune microenvironment associated with outcomes in multiple myeloma.

Multiple Myeloma (MM) remains incurable despite advances in treatment options. Although tumor subtypes and specific DNA abnormalities are linked to worse prognosis, the impact of immune dysfunction on disease emergence and/or treatment sensitivity remains unclear. We established a harmonized consortium to generate an Immune Atlas of MM aimed at informing disease etiology, risk stratification, and potential therapeutic strategies. We generated a transcriptome profile of 1,149,344 single cells from the bone marrow of 263 newly diagnosed patients enrolled in the CoMMpass study and characterized immune and hematopoietic cell populations. Associating cell abundances and gene expression with disease progression revealed the presence of a proinflammatory immune senescence-associated secretory phenotype in rapidly progressing patients. Furthermore, signaling analyses suggested active intercellular communication involving APRIL-BCMA, potentially promoting tumor growth and survival. Finally, we demonstrate that integrating immune cell levels with genetic information can significantly improve patient stratification.

Enhanced Thermal Stability of Carbonyl Iron Nanocrystalline Microwave Absorbents by Pinning Grain Boundaries with SiBaFe Alloy Nanoparticles.

Nanocrystalline carbonyl iron (CI) particles are promising microwave absorbents at elevated temperature, whereas their excessive grain boundary energy leads to the growth of nanograins and a deterioration in permeability. In this work, we report a strategy to enhance the thermal stability of the grains and microwave absorption of CI particles by doping a SiBaFe alloy. Grain growth was effectively inhibited by the pinning effect of SiBaFe alloy nanoparticles at the grain boundaries. After heat treatment at 600 °C, the grain size of CI particles increased from ~10 nm to 85.1 nm, while that of CI/SiBaFe particles was only 32.0 nm; with the temperature rising to 700 °C, the grain size of CI particles sharply increased to 158.1 nm, while that of CI/SiBaFe particles was only 40.8 nm. Excellent stability in saturation magnetization and microwave absorption was also achieved in CI/SiBaFe particles. After heat treatment at 600 °C, the flaky CI/SiBaFe particles exhibited reflection loss below -10 dB over 7.01~10.11 GHz and a minimum of -14.92 dB when the thickness of their paraffin-based composite was 1.5 mm. We provided a low-cost and efficient kinetic strategy to stabilize the grain size in nanoscale and microwave absorption for nanocrystalline magnetic absorbents working at elevated temperature.

Regioselective and Enantioselective Nickel-Catalyzed Intermolecular Reductive Coupling of Aliphatic Alkenes with Imines.

Unactivated aliphatic alkenes are particularly desirable as starting materials because they are readily accessible in large quantities, but the enantioselective intermolecular reductive coupling of unactivated alkenes with imines is challenging. In this paper, we report a method for nickel-catalyzed intermolecular reductive coupling reactions between aliphatic alkenes and imines to yield chiral amines with excellent enantioselectivities and good linear selectivities. The reaction conditions are compatible with a broad range of aliphatic alkenes, including those derived from bioactive molecules. The success of this method can be attributed to the use of newly developed monodentate chiral spiro phosphine ligands.

Extracellular vesicles as carriers for noncoding RNA-based regulation of macrophage/microglia polarization: an emerging candidate regulator for lung and traumatic brain injuries.

Macrophage/microglia function as immune defense and homeostatic cells that originate from bone marrow progenitor cells. Macrophage/microglia activation is historically divided into proinflammatory M1 or anti-inflammatory M2 states based on intracellular dynamics and protein production. The polarization of macrophages/microglia involves a pivotal impact in modulating the development of inflammatory disorders, namely lung and traumatic brain injuries. Recent evidence indicates shared signaling pathways in lung and traumatic brain injuries, regulated through non-coding RNAs (ncRNAs) loaded into extracellular vesicles (EVs). This packaging protects ncRNAs from degradation. These vesicles are subcellular components released through a paracellular mechanism, constituting a group of nanoparticles that involve exosomes, microvesicles, and apoptotic bodies. EVs are characterized by a double-layered membrane and are abound with proteins, nucleic acids, and other bioactive compounds. ncRNAs are RNA molecules with functional roles, despite their absence of coding capacity. They actively participate in the regulation of mRNA expression and function through various mechanisms. Recent studies pointed out that selective packaging of ncRNAs into EVs plays a role in modulating distinct facets of macrophage/microglia polarization, under conditions of lung and traumatic brain injuries. This study will explore the latest findings regarding the role of EVs in the progression of lung and traumatic brain injuries, with a specific focus on the involvement of ncRNAs within these vesicles. The conclusion of this review will emphasize the clinical opportunities presented by EV-ncRNAs, underscoring their potential functions as both biomarkers and targets for therapeutic interventions.

Redoxhigh phenotype mediated by KEAP1/STK11/SMARCA4/NRF2 mutations diminishes tissue-resident memory CD8+ T cells and attenuates the efficacy of immunotherapy in lung adenocarcinoma.

Metabolism reprogramming within the tumor microenvironment (TME) can have a profound impact on immune cells. Identifying the association between metabolic phenotypes and immune cells in lung adenocarcinoma (LUAD) may reveal mechanisms of resistance to immune checkpoint inhibitors (ICIs). Metabolic phenotypes were classified by expression of metabolic genes. Somatic mutations and transcriptomic features were compared across the different metabolic phenotypes. The metabolic phenotype of LUAD is predominantly determined by reductase-oxidative activity and is divided into two categories: redoxhigh LUAD and redoxlow LUAD. Genetically, redoxhigh LUAD is mainly driven by mutations in KEAP1, STK11, NRF2, or SMARCA4. These mutations are more prevalent in redoxhigh LUAD (72.5%) compared to redoxlow LUAD (17.4%), whereas EGFR mutations are more common in redoxlow LUAD (19.0% vs. 0.7%). Single-cell RNA profiling of pre-treatment and post-treatment samples from patients receiving neoadjuvant chemoimmunotherapy revealed that tissue-resident memory CD8+ T cells are responders to ICIs. However, these cells are significantly reduced in redoxhigh LUAD. The redoxhigh phenotype is primarily attributed to tumor cells and is positively associated with mTORC1 signaling. LUAD with the redoxhigh phenotype demonstrates a lower response rate (39.1% vs. 70.8%, p = 0.001), shorter progression-free survival (3.3 vs. 14.6 months, p = 0.004), and overall survival (12.1 vs. 31.2 months, p = 0.022) when treated with ICIs. The redoxhigh phenotype in LUAD is predominantly driven by mutations in KEAP1, STK11, NRF2, and SMARCA4. This phenotype diminishes the number of tissue-resident memory CD8+ T cells and attenuates the efficacy of ICIs.

MSC-derived exosomes mitigate cadmium-induced male reproductive injury by ameliorating DNA damage and autophagic flux.

Cadmium, an environmental toxicant, severely impairs male reproductive functions and currently lacks effective clinical treatments. Mesenchymal stem cell-derived exosomes (MSC-Exos) are increasingly recognized as a potential alternative to whole-cell therapy for tissue injury and regeneration. This study aims to investigate the protective effects of MSC-Exos against cadmium toxicity on male reproduction. Our findings reveal that MSC-Exos treatment significantly promotes spermatogenesis, improves sperm quality, and reduces germ cell apoptosis in cadmium-exposed mice. Mechanistically, MSC-Exos dramatically mitigate cadmium-induced cell apoptosis in a spermatogonia cell line (GC-1 spg) in vitro by reducing DNA damage and promoting autophagic flux. These results suggest that MSC-Exos have a protective effect on cadmium-induced germ cell apoptosis by ameliorating DNA damage and autophagy flux, demonstrating the therapeutic potential of MSC-Exos for cadmium toxicity on male reproduction.

Correlation of distribution characteristics and dynamic changes of gut microbiota with the efficacy of immunotherapy in EGFR-mutated non-small cell lung cancer.

BACKGROUND: The effects of gut microbiota and metabolites on the responses to immune checkpoint inhibitors (ICIs) in advanced epidermal growth factor receptor (EGFR) wild-type non-small cell lung cancer (NSCLC) have been studied. However, their effects on EGFR-mutated (EGFR +) NSCLC remain unknown. METHODS: We prospectively recorded the clinicopathological characteristics of patients with advanced EGFR + NSCLC and assessed potential associations between the use of antibiotics or probiotics and immunotherapy efficacy. Fecal samples were collected at baseline, early on-treatment, response and progression status and were subjected to metagenomic next-generation sequencing and ultra-high-performance liquid chromatography-mass spectrometry analyses to assess the effects of gut microbiota and metabolites on immunotherapy efficacy. RESULTS: The clinical data of 74 advanced EGFR + NSCLC patients were complete and 18 patients' fecal samples were dynamically collected. Patients that used antibiotics had shorter progression-free survival (PFS) (mPFS, 4.8 vs. 6.7 months; P = 0.037); probiotics had no impact on PFS. Two dynamic types of gut microbiota during immunotherapy were identified: one type showed the lowest relative abundance at the response time point, whereas the other type showed the highest abundance at the response time point. Metabolomics revealed significant differences in metabolites distribution between responders and non-responders. Deoxycholic acid, glycerol, and quinolinic acid were enriched in responders, whereas L-citrulline was enriched in non-responders. There was a significant correlation between gut microbiota and metabolites. CONCLUSIONS: The use of antibiotics weakens immunotherapy efficacy in patients with advanced EGFR + NSCLC. The distribution characteristics and dynamic changes of gut microbiota and metabolites may indicate the efficacy of immunotherapy in advanced EGFR + NSCLC.

Identification of a risk score model based on tertiary lymphoid structure-related genes for predicting immunotherapy efficacy in non-small cell lung cancer.

BACKGROUND: Tertiary lymphoid structures (TLSs) affect the prognosis and efficacy of immunotherapy in patients with non-small cell lung cancer (NSCLC), but the underlying mechanisms are not well understood. METHODS: TLSs were identified and categorized online from the Cancer Digital Slide Archive (CDSA). Overall survival (OS) and disease-free survival (DFS) were analyzed. GSE111414 and GSE136961 datasets were downloaded from the GEO database. GSVA, GO and KEGG were used to explore the signaling pathways. Immune cell infiltration was analyzed by xCell, ssGSEA and MCP-counter. The analysis of WGCNA, Lasso and multivariate cox regression were conducted to develop a gene risk score model based on the SU2C-MARK cohort. RESULTS: TLS-positive was a protective factor for OS according to multivariate cox regression analysis (p = 0.029). Both the TLS-positive and TLS-mature groups exhibited genes enrichment in immune activation pathways. The TLS-mature group showed more activated dendritic cell infiltration than the TLS-immature group. We screened TLS-related genes using WGCNA. Lasso and multivariate cox regression analysis were used to construct a five-genes (RGS8, RUF4, HLA-DQB2, THEMIS, and TRBV12-5) risk score model, the progression free survival (PFS) and OS of patients in the low-risk group were markedly superior to those in the high-risk group (p < 0.0001; p = 0.0015, respectively). Calibration and ROC curves indicated that the combined model with gene risk score and clinical features could predict the PFS of patients who have received immunotherapy more accurately than a single clinical factor. CONCLUSIONS: Our data suggested a pivotal role of TLSs formation in survival outcome and immunotherapy response of NSCLC patients. Tumors with mature TLS formation showed more activated immune microenvironment. In addition, the model constructed by TLS-related genes could predict the response to immunotherapy and is meaningful for clinical decision-making.

Deep learning-aided 3D proxy-bridged region-growing framework for multi-organ segmentation.

Accurate multi-organ segmentation in 3D CT images is imperative for enhancing computer-aided diagnosis and radiotherapy planning. However, current deep learning-based methods for 3D multi-organ segmentation face challenges such as the need for labor-intensive manual pixel-level annotations and high hardware resource demands, especially regarding GPU resources. To address these issues, we propose a 3D proxy-bridged region-growing framework specifically designed for the segmentation of the liver and spleen. Specifically, a key slice is selected from each 3D volume according to the corresponding intensity histogram. Subsequently, a deep learning model is employed to pinpoint the semantic central patch on this key slice, to calculate the growing seed. To counteract the impact of noise, segmentation of the liver and spleen is conducted on superpixel images created through proxy-bridging strategy. The segmentation process is then extended to adjacent slices by applying the same methodology iteratively, culminating in the comprehensive segmentation results. Experimental results demonstrate that the proposed framework accomplishes segmentation of the liver and spleen with an average Dice Similarity Coefficient of approximately 0.93 and a Jaccard Similarity Coefficient of around 0.88. These outcomes substantiate the framework's capability to achieve performance on par with that of deep learning methods, albeit requiring less guidance information and lower GPU resources.

A Colorectal Coordinate-Driven Method for Colorectum and Colorectal Cancer Segmentation in Conventional CT Scans.

Automated colorectal cancer (CRC) segmentation in medical imaging is the key to achieving automation of CRC detection, staging, and treatment response monitoring. Compared with magnetic resonance imaging (MRI) and computed tomography colonography (CTC), conventional computed tomography (CT) has enormous potential because of its broad implementation, superiority for the hollow viscera (colon), and convenience without needing bowel preparation. However, the segmentation of CRC in conventional CT is more challenging due to the difficulties presenting with the unprepared bowel, such as distinguishing the colorectum from other structures with similar appearance and distinguishing the CRC from the contents of the colorectum. To tackle these challenges, we introduce DeepCRC-SL, the first automated segmentation algorithm for CRC and colorectum in conventional contrast-enhanced CT scans. We propose a topology-aware deep learning-based approach, which builds a novel 1-D colorectal coordinate system and encodes each voxel of the colorectum with a relative position along the coordinate system. We then induce an auxiliary regression task to predict the colorectal coordinate value of each voxel, aiming to integrate global topology into the segmentation network and thus improve the colorectum's continuity. Self-attention layers are utilized to capture global contexts for the coordinate regression task and enhance the ability to differentiate CRC and colorectum tissues. Moreover, a coordinate-driven self-learning (SL) strategy is introduced to leverage a large amount of unlabeled data to improve segmentation performance. We validate the proposed approach on a dataset including 227 labeled and 585 unlabeled CRC cases by fivefold cross-validation. Experimental results demonstrate that our method outperforms some recent related segmentation methods and achieves the segmentation accuracy in DSC for CRC of 0.669 and colorectum of 0.892, reaching to the performance (at 0.639 and 0.890, respectively) of a medical resident with two years of specialized CRC imaging fellowship.

Stem Leydig cells support macrophage immunological homeostasis through mitochondrial transfer in mice.

As testicular mesenchymal stromal cells, stem Leydig cells (SLCs) show great promise in the treatment of male hypogonadism. The therapeutic functions of mesenchymal stromal cells are largely determined by their reciprocal regulation by immune responses. However, the immunoregulatory properties of SLCs remain unclear. Here, we observe that SLCs transplantation restore male fertility and testosterone production in an ischemia‒reperfusion injury mouse model. SLCs prevent inflammatory cascades through mitochondrial transfer to macrophages. Reactive oxygen species (ROS) released from activated macrophages inducing mitochondrial transfer from SLCs to macrophages in a transient receptor potential cation channel subfamily member 7 (TRPM7)-mediated manner. Notably, knockdown of TRPM7 in transplanted SLCs compromised therapeutic outcomes in both testicular ischemia‒reperfusion and testicular aging mouse models. These findings reveal a new mechanism of SLCs transplantation that may contribute to preserve testis function in male patients with hypogonadism related to immune disorders.

SERPINA3, FGA, AGP1, ITIH3 and SAA1 as novel biomarkers for eosinophilic granulomatosis with polyangiitis diagnosis and activity assessment.

OBJECTIVE: To identify novel biomarkers for diagnosis and prediction of active eosinophilic granulomatosis with polyangiitis (EGPA) through data-independent acquisition (DIA) analysis. METHODS: Plasma from 11 EGPA patients and 10 healthy controls (HCs) were analyzed through DIA to identify potential biomarkers. The results were validated in 32 EGPA patients, 24 disease controls (DCs), and 20 HCs using enzyme-linked immunosorbent assay (ELISA). The receiver operating characteristic (ROC) curve was used to assess the diagnostic value of candidate biomarkers. RESULTS: Thirty-five differentially expressed proteins (DEPs) (24 upregulated and 11 downregulated) were screened between EGPA and HC groups. Five proteins, including serine proteinase inhibitor A3 (SERPINA3), alpha-fibrinogen (FGA), alpha-1 acid glycoprotein 1(AGP1), inter-alpha-trypsin inhibitor heavy chain H3 (ITIH3), and serum amyloid A1 (SAA1), were significantly upregulated in EGPA compared with HCs. Apart from SAA1, all proteins were also higher in EGPA patients compared with DCs. Furthermore, a panel of SERPINA3 and SAA1 exhibited potential diagnostic value for EGPA with an area under the curve (AUC) of 0.953, while a panel of SERPINA3, FGA, AGP1, and ITIH3 showed good discriminative power to differentiate EGPA from DCs with AUC of 0.926. Moreover, SERPINA3, FGA, and AGP levels were significantly higher in active EGPA and correlated well with disease activity. A combination of SERPINA3 and AGP1 exhibited an excellent AUC of 0.918 for disease activity assessment. CONCLUSION: SERPINA3, FGA, AGP1, ITIH3 and SAA1 were identified as potential biomarkers for EGPA diagnosis and disease activity assessment. Among them, as a single biomarker, SERPINA3 has the best diagnostic performance.

Warm Acupuncture Reduces Pain and Inflammation in Rats with Lumbar Disc Herniation Induced by Autologous Nucleus Pulposus Transplantation via Regulating p38MAPK/NF-κB Pathway.

Background: : Warm acupuncture (WA) has analgesic and anti-inflammatory effects. However, the underlying mechanism of these effects remain unclear. Objectives: : To explore the analgesic and anti-inflammatory effects of WA and the potential underlying mechanism in male Sprague-Dawley rats with non-compressive lumbar disk herniation (LDH) caused by autologous nucleus pulposus (NP) transplantation. Methods: : We used low-frequency (2 Hz) electrical stimulation and WA (40℃) to treat GB30 and BL54 acupoints in rats for 30 mins per day. We monitored the paw withdrawal threshold of rats during the experiment and measured serum cytokine levels using commercial kits. Dorsal root ganglion (DRG) tissue pathology was analyzed via H&E staining. We used qRT-PCR to measure the mRNA expression levels of IL-1ß, IL-6, and TNF-α genes in DRG. Western blot was used to analyze the expression levels of IL-1ß, IL-6, TNFα, P-p38MAPK, p38MAPK, P-IκBα, IκB α, and NF-κB p65 proteins. Results: : WA treatment significantly increased the pain threshold of rats, reduced serum IL-6, PEG2, NO, SP, NP-Y, and MMP-3 levels, and effected histopathological improvements in the DRG in rats. Moreover, WA treatment significantly downregulated the expression levels of inflammation-associated genes (Il-1ß, Il-6, and Tnf-α) and proteins (IL-1ß, IL-6, TNF-α, P-p38MAPK, P-IκBα, and NF-κB p65) in the DRG of non-compressive LDH rats. Conclusion: : WA can alleviate pain and inhibit inflammatory response in rats with non-compressive LDH caused by autologous NP transplantation, and these effects are likely associated with the inhibition of the p38MAPK/NF-κB pathway.

The HSP90-MYC-CDK9 network drives therapeutic resistance in mantle cell lymphoma.

Brexucabtagene autoleucel CAR-T therapy is highly efficacious in overcoming resistance to Bruton's tyrosine kinase inhibitors (BTKi) in mantle cell lymphoma. However, many patients relapse post CAR-T therapy with dismal outcomes. To dissect the underlying mechanisms of sequential resistance to BTKi and CAR-T therapy, we performed single-cell RNA sequencing analysis for 66 samples from 25 patients treated with BTKi and/or CAR-T therapy and conducted in-depth bioinformatics™ analysis. Our analysis revealed that MYC activity progressively increased with sequential resistance. HSP90AB1 (Heat shock protein 90 alpha family class B member 1), a MYC target, was identified as early driver of CAR-T resistance. CDK9 (Cyclin-dependent kinase 9), another MYC target, was significantly upregulated in Dual-R samples. Both HSP90AB1 and CDK9 expression were correlated with MYC activity levels. Pharmaceutical co-targeting of HSP90 and CDK9 synergistically diminished MYC activity, leading to potent anti-MCL activity. Collectively, our study revealed that HSP90-MYC-CDK9 network is the primary driving force of therapeutic resistance.

Epstein-Barr virus-positive inflammatory follicular dendritic cell sarcoma with significant granuloma: case report and literature review.

BACKGROUND: Epstein-Barr virus-positive inflammatory follicular dendritic cell sarcoma (EBV+IFDCS) is a rare disease characterized by mild clinical symptoms and non-specific imaging findings. The diagnosis of the disease depends on pathological diagnosis. However, EBV+IFDCS has a very broad spectrum of histological morphology and immune phenotypes, and its histopathological features have not been fully described by pathologists. CASE PRESENTATION: A 59-year-old female, with no significant discomfort, was found to have a splenic mass during a routine physical examination. Microscopic examination at low magnification revealed numerous epithelioid granulomas, amidst which a substantial inflammatory response was observed. Interspersed among the dense inflammatory cells were spindle or oval-shaped cells, distributed sporadically with indistinct boundaries. Under high magnification, these spindle cells had subtle features: smooth and clear nuclear membranes, inconspicuous small nucleoli, and infrequent mitotic figures. Immunophenotypically, the spindle cells expressed CD21 and CD23, and Epstein-Barr encoding region (EBER) in situ hybridization yielded positive results. The inflammatory milieu predominantly consisted of T cells, with a minority of plasma cells expressing IgG4. The confluence of morphological and immunohistochemical findings led to the final pathological diagnosis of EBV+IFDCS in this case. CONCLUSIONS: The presentation of EBV+IFDCS with pronounced granulomatous changes is rare. This morphological variant poses a high risk of misdiagnosis, frequently leading to confusion with other granulomatous diseases. Accurate diagnosis necessitates a comprehensive analysis, integrating immunohistochemistry and in situ hybridization. The case presented here is instrumental in raising awareness and understanding of EBV+IFDCS, with the goal of reducing misdiagnoses and unrecognized cases.

Transcript Profiles of Microglia/Macrophage Cells at the Borders of Chronic Active and Subpial Gray Matter Lesions in Multiple Sclerosis.

OBJECTIVE: Microglia/macrophages line the border of demyelinated lesions in both cerebral white matter and the cortex in the brains of multiple sclerosis patients. Microglia/macrophages associated with chronic white matter lesions are thought to be responsible for slow lesion expansion and disability progression in progressive multiple sclerosis, whereas those lining gray matter lesions are less studied. Profiling these microglia/macrophages could help to focus therapies on genes or pathways specific to lesion expansion and disease progression. METHODS: We compared the morphology and transcript profiles of microglia/macrophages associated with borders of white matter (WM line) and subpial gray matter lesions (GM line) using laser capture microscopy. We performed RNA sequencing on isolated cells followed by immunocytochemistry to determine the distribution of translational products of transcripts increased in WM line microglia. RESULTS: Cells in the WM line appear activated, with shorter processes and larger cell bodies, whereas those in the GM line appear more homeostatic, with smaller cell bodies and multiple thin processes. Transcript profiling revealed 176 genes in WM lines and 111 genes in GM lines as differentially expressed. Transcripts associated with immune activation and iron homeostasis were increased in WM line microglia, whereas genes belonging to the canonical Wnt signaling pathway were increased in GM line microglia. INTERPRETATION: We propose that the mechanisms of demyelination and dynamics of lesion expansion are responsible for differential transcript expression in WM lines and GM lines, and posit that increased expression of the Fc epsilon receptor, spleen tyrosine kinase, and Bruton's tyrosine kinase, play a key role in regulating microglia/macrophage function at the border of chronic active white matter lesions. ANN NEUROL 2024;95:907-916.

Development of a machine learning-based radiomics signature for estimating breast cancer TME phenotypes and predicting anti-PD-1/PD-L1 immunotherapy response.

BACKGROUNDS: Since breast cancer patients respond diversely to immunotherapy, there is an urgent need to explore novel biomarkers to precisely predict clinical responses and enhance therapeutic efficacy. The purpose of our present research was to construct and independently validate a biomarker of tumor microenvironment (TME) phenotypes via a machine learning-based radiomics way. The interrelationship between the biomarker, TME phenotypes and recipients' clinical response was also revealed. METHODS: In this retrospective multi-cohort investigation, five separate cohorts of breast cancer patients were recruited to measure breast cancer TME phenotypes via a radiomics signature, which was constructed and validated by integrating RNA-seq data with DCE-MRI images for predicting immunotherapy response. Initially, we constructed TME phenotypes using RNA-seq of 1089 breast cancer patients in the TCGA database. Then, parallel DCE-MRI images and RNA-seq of 94 breast cancer patients obtained from TCIA were applied to develop a radiomics-based TME phenotypes signature using random forest in machine learning. The repeatability of the radiomics signature was then validated in an internal validation set. Two additional independent external validation sets were analyzed to reassess this signature. The Immune phenotype cohort (n = 158) was divided based on CD8 cell infiltration into immune-inflamed and immune-desert phenotypes; these data were utilized to examine the relationship between the immune phenotypes and this signature. Finally, we utilized an Immunotherapy-treated cohort with 77 cases who received anti-PD-1/PD-L1 treatment to evaluate the predictive efficiency of this signature in terms of clinical outcomes. RESULTS: The TME phenotypes of breast cancer were separated into two heterogeneous clusters: Cluster A, an "immune-inflamed" cluster, containing substantial innate and adaptive immune cell infiltration, and Cluster B, an "immune-desert" cluster, with modest TME cell infiltration. We constructed a radiomics signature for the TME phenotypes ([AUC] = 0.855; 95% CI 0.777-0.932; p < 0.05) and verified it in an internal validation set (0.844; 0.606-1; p < 0.05). In the known immune phenotypes cohort, the signature can identify either immune-inflamed or immune-desert tumor (0.814; 0.717-0.911; p < 0.05). In the Immunotherapy-treated cohort, patients with objective response had higher baseline radiomics scores than those with stable or progressing disease (p < 0.05); moreover, the radiomics signature achieved an AUC of 0.784 (0.643-0.926; p < 0.05) for predicting immunotherapy response. CONCLUSIONS: Our imaging biomarker, a practicable radiomics signature, is beneficial for predicting the TME phenotypes and clinical response in anti-PD-1/PD-L1-treated breast cancer patients. It is particularly effective in identifying the "immune-desert" phenotype and may aid in its transformation into an "immune-inflamed" phenotype.

Gastric cancer mesenchymal stem cells promote tumor glycolysis and chemoresistance by regulating B7H3 in gastric cancer cells.

Despite surgical treatment combined with multidrug therapy having made some progress, chemotherapy resistance is the main cause of recurrence and death of gastric cancer (GC). Gastric cancer mesenchymal stem cells (GCMSCs) have been reported to be correlated with the limited efficacy of chemotherapy in GC, but the mechanism of GCMSCs regulating GC resistance needs to be further studied. The gene set enrichment analysis (GSEA) was performed to explore the glycolysis-related pathways heterogeneity across different cell subpopulations. Glucose uptake and lactate production assays were used to evaluate the importance of B7H3 expression in GCMSCs-treated GC cells. The therapeutic efficacy of oxaliplatin (OXA) and paclitaxel (PTX) was determined using CCK-8 and colony formation assays. Signaling pathways altered by GCMSCs-CM were revealed by immunoblotting. The expression of TNF-α in GCMSCs and bone marrow mesenchymal stem cells (BMMSCs) was detected by western blot analysis and qPCR. Our results showed that the OXA and PTX resistance of GC cells were significantly enhanced in the GCMSCs-CM treated GC cells. Acquired OXA and PTX resistance was characterized by increased cell viability for OXA and PTX, the formation of cell colonies, and decreased levels of cell apoptosis, which were accompanied by reduced levels of cleaved caspase-3 and Bax expression, and increased levels of Bcl-2, HK2, MDR1, and B7H3 expression. Blocking TNF-α in GCMSCs-CM, B7H3 knockdown or the use of 2-DG, a key enzyme inhibitor of glycolysis in GC cells suppressed the OXA and PTX resistance of GC cells that had been treated with GCMSCs-CM. This study shows that GCMSCs-CM derived TNF-α could upregulate the expression of B7H3 of GC cells to promote tumor chemoresistance. Our results provide a new basis for the treatment of GC.