Laboratory Investigation最新文献

CD248 (Endosialin/TEM-1) is upregulated in cancer, including colorectal cancer (CRC), but its exact role in tumor progression remains to be elucidated. Previous studies have shown that the extracellular domain of CD248 mediates the interaction between tumor cells and extracellular matrix proteins and that interfering with this interaction may reduce tumor invasion and migration activities. We have examined the expression of CD248 in 117 human CRC samples by immunohistochemistry and investigated the association with various clinicopathological features, including the occurrence of metastasis intra-tumoral immune cell density, and overall survival. Out of the 117 specimens analyzed, 76.1% (89/117) exhibited CD248-high stromal expression, while 23.1% (28/117) demonstrated CD248-low stromal expression. Interestingly, we detected the presence of a cleaved form of CD248, which appears to accumulate in the stromal extracellular matrix. A higher metastasis rate (lymph node and distant) was observed in the CD248-low group (21/28, 75.0% versus 44/89, 49.4%, p=0.02). In addition, CD248-low tumors had fewer CD163-positive macrophages and FoxP3-positive regulatory T cells (p<0.05) with no significant difference in CD8-positive T-cell infiltration and PD-L1 expression between the groups (p>0.05). Finally, overall survival was lower in CD248-low tumors than in CD248-high tumors, with 5-year survival rates of 35.7% and 57.3%, respectively (p=0.01). In a multivariate analysis, the hazard ratio of CD248-low tumors versus CD248-high tumors was 1.93 (95% confidence interval: 1.09 - 3.40; p=0.02). Our findings suggest that CD248 stromal expression may influence the TME, impacting tumor behavior and prognosis, and can serve as a promising prognostic biomarker in CRC.

Malignant peripheral nerve sheath tumors (MPNSTs) are aggressive sarcomas arising from peripheral nerves, accounting for 3-5% of soft tissue sarcomas. MPNSTs often recur locally, leading to poor survival. Achieving tumor-free surgical margins is essential to prevent recurrence, but current methods for determining tumor margins are limited, highlighting the need for improved biomarkers. In this study we investigated the degree to which MPNST extends into nerves adjacent to tumors. Alterations to the lipidome of MPNST and adjacent peripheral nerves were assessed using spatial lipidomics. Tissue samples from 5 MPNST patients were analyzed, revealing alterations of the lipid profile extending into the peripheral nerves beyond what was expected based on macroscopic and histological observations. Integration of spatial lipidomics and high-resolution accurate mass profiling identified distinct lipid profiles associated with healthy nerves, connective tissue, and tumors. Notably, histologically normal nerves exhibited myelin degradation and infiltration of pro-tumoral M2 macrophages, particularly near the tumor. Furthermore, aberrant osmium staining patterns and loss of H3K27me3 staining in absence of atypia were observed in a case with tumor recurrence. This exploratory study thereby highlights the changes occurring in the nerves affected by MPNST beyond what is visible on H&E, and provides leads for further biomarker studies, including aberrant osmium staining, to assess resection margins in MPNST.

About 20% of human cancers harbor mutations of genes encoding SWI/SNF (Switch/Sucrose Non-Fermentable) complex subunits. Deficiency of subunits of the complex is present in 10% non-small cell lung cancers (NSCLC; SMARCA4/SMARCA2 deficient), 100% thoracic SMARCA4/A2 deficient undifferentiated tumors (TSADUDT; SMARCA4/A2 deficient), malignant rhabdoid tumor (MRT) and atypical/teratoid tumor (AT/RT) (SMARCB1 deficient), >90% of small cell carcinoma of the ovary, hypercalcemic type (SCCOHT; SMARCA4/SMARCA2 deficient), frequently in undifferentiated/dedifferentiated endometrial carcinoma (UDEC/DDEC; SMARCA4, SMARCA2, SMARCB1, ARID1A/B deficient), 100% SMARCA4 deficient undifferentiated uterine sarcoma (SDUS; SMARCA4 deficient); and in various other tumors from multifarious anatomic sites. Silencing of SWI/SNF gene expression may be genomically or epigenetically driven, causing loss of tumor suppression function or facilitating other oncogenic events. The SWI/SNF deficient tumors share the phenotype of poor or no differentiation, often with a variable component of rhabdoid tumor cells. They present at advanced stages with poor prognosis. Rhabdoid tumor cell phenotype is a useful feature to prompt investigation for this group of tumors. In the thoracic space, the overlap in morphology, immunophenotype, genetics, and epigenetics of SMARCA4/A2 deficient NSCLC and TSADUDT appears more significant. This raises a possible nosological relationship between TSADUDT and SMARCA4/A2 deficient NSCLC. Increased understanding of the genetics, epigenetics, and mechanisms of oncogenesis in these poor prognostic tumors, which are often resistant to conventional treatment, opens a new horizon of therapy for the tumors.

Lung squamous cell carcinoma (LUSC), a subtype of non-small cell lung cancer, represents a significant portion of lung cancer cases with distinct histologic patterns impacting prognosis and treatment. The current pathological assessment methods face limitations such as inter-observer variability, necessitating more reliable techniques. This study seeks to predict lymph node metastasis in LUSC using deep learning models applied to histopathology images of primary tumors, offering a more accurate and objective method for diagnosis and prognosis. Whole slide images (WSIs) from the Outdo-LUSC and TCGA-LUSC cohorts were used to train and validate deep-learning models. Multi-instance learning was applied, with patch-level predictions aggregated into WSI-level outcomes. The study employed the ResNet-18 network, transfer learning, and rigorous data preprocessing. To represent WSI features, innovative techniques like patch likelihood histogram (PLH) and bag of words (BoW) were used, followed by training of machine learning classifiers, including the ExtraTrees algorithm. The diagnostic model for lymph node metastasis showed strong performance, particularly using the ExtraTrees algorithm, as demonstrated by receiver operating characteristic (ROC) curves and Grad-CAM visualizations. The signature generated by the ExtraTrees algorithm, named LN_ISLUSCH (lymph node status-related in-situ lung squamous cell carcinoma histopathology), achieved an area under the curve (AUC) of 0.941 (95% CI: 0.926-0.955) in the training set and 0.788 (95% CI: 0.748-0.827) in the test set. Kaplan-Meier analyses confirmed that the LN_ISLUSCH model was a significant prognostic factor (p = 0.02). This study underscores the potential of artificial intelligence in enhancing diagnostic precision in pathology. The LN_ISLUSCH model stands out as a promising tool for predicting lymph node metastasis and prognosis in LUSC. Future studies should focus on larger and more diverse cohorts and explore the integration of additional omics data to further refine predictive accuracy and clinical utility.

Superficial malignant peripheral nerve sheath tumors (SF-MPNSTs) are rare cancers and can be difficult to distinguish from spindle cell (SCM) or desmoplastic (DM) melanomas. Their biology is poorly understood. We performed whole-exome sequencing (WES) and RNA sequencing (RNA-seq) on SF-MPNST (n=8) and compared these to cases of SCM (n=7), DM (n=8), and deep MPNST (D-MPNST, n=8). Immunohistochemical staining for H3K27me3 and PRAME was also performed. SF-MPNST demonstrated intermediate features between D-MPNST and melanoma. Patients were younger than those with melanoma, and older than those with D-MPNST; outcome was worse and better respectively. SF-MPNST tumor mutational burden (TMB) was higher than D-MPNST and lower than melanoma; differences were significant only between SF-MPNST and SCM (p = 0.0454) and between D-MPNST and SCM (p = 0.001, Dunn's Kruskal-Wallis post-hoc test). Despite having an overlapping mutational profile in some common cancer-associated genes, the COSMIC mutational signatures clustered DM and SCM together with ultraviolet light exposure signatures (SBS7a, 7b), and SF- and D-MPNST together with defective DNA base excision repair (SBS30, 36). RNA-seq revealed differentially expressed genes between SF-MPNST and SCM (1670 genes), DM (831 genes), and D-MPNST (614 genes), some of which hold promise for development as immunohistochemical markers (SOX8, PLCH1) or aids (MLPH, CALB2, SOX11, TBX4). H3K27me3 immunoreactivity was diffusely lost in most D-MPNSTs (7/8, 88%), but showed variable and patchy loss in SF-MPNSTs (2/8, 25%). PRAME was entirely negative in the majority (0+ in 20/31, 65%), including 11/15 melanomas, and showed no significant difference between groups (p=0.105, Kruskal-Wallis test). Expression of immune cell transcripts was upregulated in melanomas relative to MPNSTs. Next-generation sequencing revealed multiple differential features between SF- MPNST, D-MPNST, SCM, and DM, including tumor mutation burden, mutational signatures, and differentially expressed genes. These findings help advance our understanding of disease pathogenesis and improve diagnostic modalities.

Accurate whole-cell segmentation is essential in various biomedical applications, particularly in studying the tumor microenvironment (TME). Despite advancements in machine learning for nuclei segmentation in hematoxylin and eosin (H&E) stained images, there remains a need for effective whole-cell segmentation methods. This study aims to develop a deep learning-based pipeline to automatically segment cells in H&E-stained tissues, thereby advancing the capabilities of pathological image analysis. The Cell Segmentation with Globally Optimized boundaries (CSGO) framework integrates nuclei and membrane segmentation algorithms, followed by post-processing using an energy-based watershed method. Specifically, we employed the You Only Look Once (Yolo) object detection algorithm for nuclei segmentation and U-Net for membrane segmentation. The membrane detection model was trained on a dataset of 7 hepatocellular carcinomas and 11 normal liver tissue patches. The cell segmentation performance was extensively evaluated on five external datasets, including liver, lung, and oral disease cases. CSGO demonstrated superior performance over the state-of-the-art method Cellpose, achieving higher F1 scores ranging from 0.37 to 0.53 at an intersection over union (IoU) threshold of 0.5 in four of the five external datasets, compared to that of Cellpose from 0.21 to 0.36. These results underscore the robustness and accuracy of our approach in various tissue types. A web-based application is available at https://ai.swmed.edu/projects/csgo, providing a user-friendly platform for researchers to apply our method to their own datasets. Our method exhibits remarkable versatility in whole-cell segmentation across diverse cancer subtypes, serving as an accurate and reliable tool to facilitate TME studies. The advancements presented in this study have the potential to significantly enhance the precision and efficiency of pathological image analysis, contributing to better understanding and treatment of cancer.

Sudden death can be the first symptom of cardiac disease, and establishing a precise postmortem diagnosis is crucial for genetic testing and follow-up of relatives. Arrhythmogenic cardiomyopathy (ACM) is a structural cardiomyopathy that can be challenging to diagnose postmortem because of differences in structural findings and propagation of the disease at the time of death. Cases can have minimal or no structural findings and later be diagnosed according to genotype, known as concealed cardiomyopathy. Postmortem diagnosis often lacks clinical information, whereas antemortem diagnosis is based on paraclinical investigations that cannot be performed after death. However, the entire substrate is available, which is unique to postmortem diagnosis and research and can provide valuable insights when adding new methods. Reactive changes in the heart such as myocardial fibrosis and fat are significant findings. The patterns of these changes in various diseases are not yet fully understood and may be limited by sampling material and conventional microscopic diagnostics. We demonstrate an automated pipeline in QuPath for quantifying postmortem picrosirius red cardiac tissue for collagen, residual myocardium, and adipocytes, by integrating Cellpose into a versatile pipeline. This method was developed and tested using cardiac tissues from autopsied individuals. Cases diagnosed with ACM and age-matched controls were used for validation and testing. This approach is free and easy to implement by other research groups using this as a template. This can potentially lead to the development of quantitative diagnostic criteria for postmortem cardiac diseases, eliminating the need to rely on diagnostic criteria from endomyocardial biopsies that are not applicable to postmortem specimens. We propose that this approach serves as a template for creating a more efficient process for evaluating postmortem cardiac measurements in an unbiased manner, particularly for rare cardiac diseases.

Although lymph node structures may be compromised in severe SARS-CoV-2 infection, the extent and parameters of recovery in convalescing patients remain unclear. Therefore, this study aimed to elucidate the nuances of lymphoid structural recovery and their implications for immunological memory in non-human primates infected with SARS-CoV-2. To do so, we utilized imaging-based spatial transcriptomics to delineate immune cell composition and tissue architecture formation in the lung draining lymph nodes during primary infection, convalescence, and reinfection from COVID-19. We noted the establishment of a germinal center with memory B cell differentiation within lymphoid follicles during convalescence accompanied by contrasting transcriptome patterns indicative of the acquisition of follicular helper T cells versus the loss of regulatory T cells. Additionally, repopulation of germinal center-like B cells was observed in the medullary niche with accumulating plasma cells along with enhanced transcriptional expression of B cell activating factor receptor over the course of reinfection. The spatial transcriptome atlas produced herein enhances our understanding of germinal center formation with immune cell dynamics during COVID-19 convalescence and lymphoid structural recovery with transcriptome dynamics following reinfection. These findings have the potential to inform the optimization of vaccine strategies and the development of precise therapeutic interventions in the spatial context.

Acute kidney injury (AKI) and chronic kidney disease (CKD) are considered interconnected syndromes, as AKI episodes may accelerate CKD progression and CKD increases the risk of AKI. Genome-wide association studies (GWAS) may identify novel actionable therapeutic targets. Human genome-wide association studies (GWAS) for AKI or CKD were combined with murine AKI transcriptomics datasets to identify 13 (ACACB, ACSM5, CNDP1, DPEP1, GATM, SLC6A12, AGXT2L1, SLC15A2, CTSS, ICAM1, ITGAX, ITGAM, PPM1J) potentially actionable therapeutic targets to modulate kidney disease severity across species and across the AKI-CKD spectrum. Among them, SLC15A2, encoding the cell membrane proton-coupled peptide transporter 2 (PEPT2), was prioritized for data mining and functional intervention studies in vitro and in vivo because of its known function to transport nephrotoxic drugs such as colistin and the possibility for targeting with small molecules already in clinical use, such as cefadroxil. Data mining disclosed that SLC15A2 was upregulated in the tubulointerstitium of human CKD, including diabetic nephropathy, and the upregulation was localized to proximal tubular cells. Colistin elicited cytotoxicity and a proinflammatory response in cultured human and murine proximal tubular cells that was decreased by concomitant exposure to cefadroxil. In proof-of-concept in vivo studies, cefadroxil protected from colistin nephrotoxicity in mice. The GWAS association of SLC15A2 with human kidney disease may be actionable and related to the modifiable transport of nephrotoxins causing repeated subclinical episodes of AKI and/or chronic nephrotoxicity.