33 research outputs found

    Nanoscale Imaging of Kidney Glomeruli Using Expansion Pathology

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    Kidney glomerular diseases, such as the minimal change disease (MCD) and focal segmental glomerulosclerosis (FSGS), and other nephrotic syndromes, are typically diagnosed or confirmed via electron microscopy. Although optical microscopy has been a vital tool to examine clinical specimens for diagnoses in pathology for decades, the optical resolution is constricted by the physical diffraction limit of the optical microscope, which prevents high-resolution investigation of subcellular anatomy, such as of the podocyte tertiary foot processes. Here, we describe a simple, fast, and inexpensive protocol for nanoscale optical imaging of kidney glomeruli. The protocol is based on Expansion Pathology (ExPath), a new principle of microscopy that overcomes optical diffraction limit by chemically embedding specimens into a swellable polymer and physically expanding it homogenously prior to imaging. Our method uses only commercially available reagents, a conventional fluorescence microscope and it can be applied to both fixed-frozen or formalin-fixed paraffin embedded (FFPE) tissue sections. It requires minimal operative experience in a wet lab, optical microscopy and imaging processing. Finally, we also discuss challenges, limitations and prospective applications for ExPath-based imaging of glomeruli

    Meta-analysis of transcriptome data identifies a novel 5-gene pancreatic adenocarcinoma classifier

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    Purpose: Pancreatic ductal adenocarcinoma (PDAC) is largely incurable due to late diagnosis. Superior early detection biomarkers are critical to improving PDAC survival and risk stratification. Experimental Design: Optimized meta-analysis of PDAC transcriptome datasets identified and validated key PDAC biomarkers. PDAC-specific expression of a 5-gene biomarker panel was measured by qRT-PCR in microdissected patient-derived FFPE tissues. Cell-based assays assessed impact of two of these biomarkers, TMPRSS4 and ECT2, on PDAC cells. Results: A 5-gene PDAC classifier (TMPRSS4, AHNAK2, POSTN, ECT2, SERPINB5) achieved on average 95% sensitivity and 89% specificity in discriminating PDAC from non-tumor samples in four training sets and similar performance (sensitivity = 94%, specificity = 89.6%) in five independent validation datasets. This classifier accurately discriminated PDAC from chronic pancreatitis (AUC = 0.83), other cancers (AUC = 0.89), and non-tumor from PDAC precursors (AUC = 0.92) in three independent datasets. Importantly, the classifier distinguished PanIN from healthy pancreas in the PDX1-Cre;LSL-KrasG12D PDAC mouse model. Discriminatory expression of the PDAC classifier genes was confirmed in microdissected FFPE samples of PDAC and matched surrounding non-tumor pancreas or pancreatitis. Notably, knock-down of TMPRSS4 and ECT2 reduced PDAC soft agar growth and cell viability and TMPRSS4 knockdown also blocked PDAC migration and invasion. Conclusions: This study identified and validated a highly accurate 5-gene PDAC classifier for discriminating PDAC and early precursor lesions from non-malignant tissue that may facilitate early diagnosis and risk stratification upon validation in prospective clinical trials. Cell-based experiments of two overexpressed proteins encoded by the panel, TMPRSS4 and ECT2, suggest a causal link to PDAC development and progression, confirming them as potential therapeutic targets

    Nanoscale imaging of clinical specimens using pathology-optimized expansion microscopy

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    Expansion microscopy (ExM), a method for improving the resolution of light microscopy by physically expanding the specimen, has not been applied to clinical tissue samples. Here we report a clinically optimized form of ExM that supports nanoscale imaging of human tissue specimens that have been fixed with formalin, embedded in paraffin, stained with hematoxylin and eosin (H&E), and/or fresh frozen. The method, which we call expansion pathology (ExPath), converts clinical samples into an ExM-compatible state, then applies an ExM protocol with protein anchoring and mechanical homogenization steps optimized for clinical samples. ExPath enables ~70 nm resolution imaging of diverse biomolecules in intact tissues using conventional diffraction-limited microscopes, and standard antibody and fluorescent DNA in situ hybridization reagents. We use ExPath for optical diagnosis of kidney minimal-change disease, which previously required electron microscopy (EM), and demonstrate high-fidelity computational discrimination between early breast neoplastic lesions that to date have challenged human judgment. ExPath may enable the routine use of nanoscale imaging in pathology and clinical research

    Meta-analysis of transcriptome data identifies a novel 5-gene pancreatic adenocarcinoma classifier

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    Purpose Pancreatic ductal adenocarcinoma (PDAC) is largely incurable due to late diagnosis. Superior early detection biomarkers are critical to improving PDAC survival and risk stratification. Experimental Design Optimized meta-analysis of PDAC transcriptome datasets identified and validated key PDAC biomarkers. PDAC-specific expression of a 5-gene biomarker panel was measured by qRT-PCR in microdissected patient-derived FFPE tissues. Cell-based assays assessed impact of two of these biomarkers, TMPRSS4 and ECT2, on PDAC cells. Results: A 5-gene PDAC classifier (TMPRSS4, AHNAK2, POSTN, ECT2, SERPINB5) achieved on average 95% sensitivity and 89% specificity in discriminating PDAC from non-tumor samples in four training sets and similar performance (sensitivity = 94%, specificity = 89.6%) in five independent validation datasets. This classifier accurately discriminated PDAC from chronic pancreatitis (AUC = 0.83), other cancers (AUC = 0.89), and non-tumor from PDAC precursors (AUC = 0.92) in three independent datasets. Importantly, the classifier distinguished PanIN from healthy pancreas in the PDX1-Cre;LSL-KrasG12D PDAC mouse model. Discriminatory expression of the PDAC classifier genes was confirmed in microdissected FFPE samples of PDAC and matched surrounding non-tumor pancreas or pancreatitis. Notably, knock-down of TMPRSS4 and ECT2 reduced PDAC soft agar growth and cell viability and TMPRSS4 knockdown also blocked PDAC migration and invasion. Conclusions: This study identified and validated a highly accurate 5-gene PDAC classifier for discriminating PDAC and early precursor lesions from non-malignant tissue that may facilitate early diagnosis and risk stratification upon validation in prospective clinical trials. Cell-based experiments of two overexpressed proteins encoded by the panel, TMPRSS4 and ECT2, suggest a causal link to PDAC development and progression, confirming them as potential therapeutic targets
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