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Journal of Visualized Experiments : JoVE Aug 2020Immunohistochemistry is a widely used technique to visualize specific tissue structures as well as protein expression and localization. Two alternative approaches are...
Immunohistochemistry is a widely used technique to visualize specific tissue structures as well as protein expression and localization. Two alternative approaches are widely used to handle the tissue sections during the staining procedure, one approach consists of mounting the sections directly on glass slides, while a second approach, the free-floating, allows for fixed sections to be maintained and stained while suspended in solution. Although slide-mounted and free-floating approaches may yield similar results, the free-floating technique allows for better antibody penetration and thus should be the method of choice when thicker sections are to be used for 3D reconstruction of the tissues, for example when the focus of the experiment is to gain information on dendritic and axonal projections in brain regions. In addition, since the sections are kept in solution, a single aliquot can easily accommodate 30 to 40 sections, handling of which is less laborious, particularly in large-scale biomedical studies. Here, we illustrate how to apply the free-floating method to fluorescent immunohistochemistry staining, with a major focus on brain sections. We will also discuss how the free-floating technique can easily be modified to fit the individual needs of researchers and adapted to other tissues as well as other histochemical-based stainings, such as hematoxylin and eosin and cresyl violet, as long as tissue samples are properly fixed, typically with paraformaldehyde or formalin.
Topics: Animals; Brain; Cryoultramicrotomy; Eosine Yellowish-(YS); Female; Fluorescence; Formaldehyde; Hematoxylin; Immunohistochemistry; Liver; Male; Mice; Polymers; Staining and Labeling
PubMed: 32925894
DOI: 10.3791/61622 -
Nature Cancer Aug 2020Molecular alterations in cancer can cause phenotypic changes in tumor cells and their micro-environment. Routine histopathology tissue slides - which are ubiquitously...
Molecular alterations in cancer can cause phenotypic changes in tumor cells and their micro-environment. Routine histopathology tissue slides - which are ubiquitously available - can reflect such morphological changes. Here, we show that deep learning can consistently infer a wide range of genetic mutations, molecular tumor subtypes, gene expression signatures and standard pathology biomarkers directly from routine histology. We developed, optimized, validated and publicly released a one-stop-shop workflow and applied it to tissue slides of more than 5000 patients across multiple solid tumors. Our findings show that a single deep learning algorithm can be trained to predict a wide range of molecular alterations from routine, paraffin-embedded histology slides stained with hematoxylin and eosin. These predictions generalize to other populations and are spatially resolved. Our method can be implemented on mobile hardware, potentially enabling point-of-care diagnostics for personalized cancer treatment. More generally, this approach could elucidate and quantify genotype-phenotype links in cancer.
Topics: Deep Learning; Eosine Yellowish-(YS); Hematoxylin; Humans; Mutation; Neoplasms
PubMed: 33763651
DOI: 10.1038/s43018-020-0087-6 -
Reconstruction of the tumor spatial microenvironment along the malignant-boundary-nonmalignant axis.Nature Communications Feb 2023Although advances in spatial transcriptomics (ST) enlarge to unveil spatial landscape of tissues, it remains challenging to delineate pathology-relevant and cellular...
Although advances in spatial transcriptomics (ST) enlarge to unveil spatial landscape of tissues, it remains challenging to delineate pathology-relevant and cellular localizations, and interactions exclusive to a spatial niche (e.g., tumor boundary). Here, we develop Cottrazm, integrating ST with hematoxylin and eosin histological image, and single-cell transcriptomics to delineate the tumor boundary connecting malignant and non-malignant cell spots in tumor tissues, deconvolute cell-type composition at spatial location, and reconstruct cell type-specific gene expression profiles at sub-spot level. We validate the performance of Cottrazm along the malignant-boundary-nonmalignant spatial axis. We identify specific macrophage and fibroblast subtypes localized around tumor boundary that interacted with tumor cells to generate a structural boundary, which limits T cell infiltration and promotes immune exclusion in tumor microenvironment. In this work, Cottrazm provides an integrated tool framework to dissect the tumor spatial microenvironment and facilitates the discovery of functional biological insights, thereby identifying therapeutic targets in oncologic ST datasets.
Topics: Tumor Microenvironment; Eosine Yellowish-(YS); Fibroblasts; Gene Expression Profiling; Hematoxylin
PubMed: 36806082
DOI: 10.1038/s41467-023-36560-7 -
Nature Communications Nov 2022Programmed death ligand-1 (PD-L1) has been recently adopted for breast cancer as a predictive biomarker for immunotherapies. The cost, time, and variability of PD-L1...
Programmed death ligand-1 (PD-L1) has been recently adopted for breast cancer as a predictive biomarker for immunotherapies. The cost, time, and variability of PD-L1 quantification by immunohistochemistry (IHC) are a challenge. In contrast, hematoxylin and eosin (H&E) is a robust staining used routinely for cancer diagnosis. Here, we show that PD-L1 expression can be predicted from H&E-stained images by employing state-of-the-art deep learning techniques. With the help of two expert pathologists and a designed annotation software, we construct a dataset to assess the feasibility of PD-L1 prediction from H&E in breast cancer. In a cohort of 3,376 patients, our system predicts the PD-L1 status in a high area under the curve (AUC) of 0.91 - 0.93. Our system is validated on two external datasets, including an independent clinical trial cohort, showing consistent prediction performance. Furthermore, the proposed system predicts which cases are prone to pathologists miss-interpretation, showing it can serve as a decision support and quality assurance system in clinical practice.
Topics: Humans; Female; B7-H1 Antigen; Breast Neoplasms; Deep Learning; Biomarkers, Tumor; Staining and Labeling; Hematoxylin; Lung Neoplasms
PubMed: 36347854
DOI: 10.1038/s41467-022-34275-9 -
CNS Neuroscience & Therapeutics Nov 2022To investigate the effect of apigenin on fibrous scar formation after mouse spinal cord injury (SCI).
AIM
To investigate the effect of apigenin on fibrous scar formation after mouse spinal cord injury (SCI).
METHODS
The pneumatic impactor strike method was used to establish an SCI model. Mice were intraperitoneally injected with 5 mg/kg or 20 mg/kg apigenin daily for 28 days after SCI. The Basso Mouse Scale (BMS) score, hematoxylin-eosin staining, and immunohistochemical staining were used to assess the effect of apigenin on scar formation and motor function recovery. Western blotting and qRT-PCR were used to detect the expression of fibrosis-related parameters in spinal cord tissue homogenates. NIH-3 T3 cells and mouse primary spinal cord fibroblasts, α-Smooth muscle actin (α-SMA), collagen 1, and fibronectin were used to evaluate apigenin's effect in vitro. Western blotting and immunofluorescence techniques were used to study the effect of apigenin on TGFβ/SMADs signaling.
RESULTS
Apigenin inhibited fibrous scar formation in the mouse spinal cord and promoted the recovery of motor function. It reduced the expression of fibroblast-related parameters and increased the content of nerve growth factor in vivo, decreasing myofibroblast activation and collagen fiber formation by inhibiting TGFβ-induced SMAD2/3 phosphorylation and nuclear translocation in vitro.
CONCLUSION
Apigenin inhibits fibrous scar formation after SCI by decreasing fibrosis-related factor expression through TGFβ/SMADs signaling.
Topics: Actins; Animals; Apigenin; Cicatrix; Collagen; Eosine Yellowish-(YS); Fibronectins; Hematoxylin; Mice; Nerve Growth Factors; Recovery of Function; Signal Transduction; Spinal Cord; Spinal Cord Injuries; Transforming Growth Factor beta
PubMed: 35906830
DOI: 10.1111/cns.13929 -
Cell Cycle (Georgetown, Tex.) Nov 2022Astragalus membranaceus is a traditional Chinese medicine and has been widely used in treating cardiovascular diseases (CVDs), such as asthma, edema, and chest...
Astragalus membranaceus is a traditional Chinese medicine and has been widely used in treating cardiovascular diseases (CVDs), such as asthma, edema, and chest tightness. Astragaloside IV (AS-IV), one of the major active components extracted from , has a series of pharmacological effects, including inhibiting inflammation, regulating energy metabolism, reducing oxidative stress and apoptosis. However, the effect of AS-IV on myocardial infarction (MI) and the underlying molecular mechanism remains unclear. The purpose of our study is to investigate the effects of AS-IV on MI-induced myocardial fibrosis and cardiac remodeling and to elucidate its underlying mechanisms. MI was induced by ligation of the left anterior descending (LAD) coronary artery. Echocardiography was used to evaluate cardiac function in mice. Pathological changes in cardiac tissues were analyzed with hematoxylin and eosin (H&E) staining, Masson staining, and wheat germ agglutinin (WGA) staining. Immunohistochemistry was used to detect the expression of fibrosis and inflammation-related proteins. Immunofluorescence and flow cytometry were used to detect ROS level. The expressions of α-SMA, Collagen I, NLRP3, cleaved cas-1, cleaved IL-18, cleaved IL-β, GSDMD-N, and cleaved caspase-1 were examined using western blot. The results of cardiac ultrasound showed that AS-IV could improve poor ventricular remodeling, myocardial pathological staining showed that AS-IV could significantly reduce the myocardial fibrosis and myocardial hypertrophy, ROS levels were also significantly reduced, and the protein expression of NLRP3/Caspase-1/GSDMD signaling pathway was remarkably decreased in the AS-IV group. Furthermore, immunohistochemical staining results showed that the expression of myocardial macrophages and neutrophils in AS-IV group decreased significantly, to further investigate whether the reduction of myocardial pyroptosis by AS-IV is related to the regulation of macrophages, , AS-IV was selected to stimulate bone marrow-derived macrophages (BMDMs). Our findings indicated that AS-IV protective effect of the heart might be related to the reduction of macrophage pyroptosis. These results demonstrate that AS-IV alleviated MI-induced myocardial fibrosis and cardiac remodeling by suppressing ROS/Caspase-1/GSDMD signaling pathway, AS-IV should be further studied in the future.
Topics: Animals; Mice; Caspase 1; Collagen; Eosine Yellowish-(YS); Fibrosis; Hematoxylin; Inflammation; Interleukin-18; Myocardial Infarction; NLR Family, Pyrin Domain-Containing 3 Protein; Reactive Oxygen Species; Saponins; Signal Transduction; Triterpenes; Ventricular Remodeling; Wheat Germ Agglutinins
PubMed: 35770948
DOI: 10.1080/15384101.2022.2093598 -
Frontiers in Immunology 2022Tertiary lymphoid structures (TLSs) are crucial in promoting and maintaining positive anti-tumor immune responses. The tumor stroma has a powerful immunosuppressive...
BACKGROUND
Tertiary lymphoid structures (TLSs) are crucial in promoting and maintaining positive anti-tumor immune responses. The tumor stroma has a powerful immunosuppressive function that could exclude tumor-infiltrating lymphocytes from the tumor beds and lead to a "cold" phenotype. TLSs and tumor stroma percentage (TSP) are significantly associated with the prognosis of patients with certain cancers. However, the exact roles of TLSs and TSP and their intrinsic relationship are still largely unknown in colorectal cancer (CRC).
METHODS
TLSs and TSP were assessed using hematoxylin-eosin (H&E) and/or immunohistochemistry (IHC) staining from 114 CRC patients in the training set and 60 CRC patients in the external validation set. The correlation between TILs, TLS and clinicopathological characteristics and their prognostic values were assessed. Finally, we plotted a Nomogram including the TLS, TSP and tumor-node-metastasis (TNM) stage to predict the probability of recurrence-free survival (RFS) at 2- and 5-years in non-metastatic colorectal cancer (nmCRC) patients.
RESULTS
Peritumoral TLS (P-TLS), intratumoral TLS (In-TLS) and high TSP (H-TSP, >50%) were present in 99.1%, 26.3% and 41.2% patients, respectively. H-TSP tumor tends to be associated with lower P-TLS density ( =0.0205). The low P-TLS density (< 0.098/mm) was significantly associated with reduced RFS (HR=6.597 95% CI: 2.882-15.103, 0.001) and reduced overall survival (OS) (HR=6.628 95% CI: 2.893-15.183, < 0.001) of nmCRC patients. In-TLS was not of significance in evaluating the clinical outcomes of nmCRC patients. H-TSP was significantly associated with reduced RFS (HR=0.126 95% CI: 0.048-0.333, 0.001) and reduced OS (HR=0.125 95% CI: 0.047-0.332, 0.001) of nmCRC patients. The 5-year RFS of the high P-TLS, low-TLS, H-TSP, and L-TSP groups were 89.7%, 47.2%, 53.2%, and 92.5%, respectively. The P-TLS density, TSP and TNM stage were independent prognosis factors of nmCRC patients. The Nomogram, including the P-TLS density, TSP and TNM stage, outperformed the TNM stage.
CONCLUSIONS
High P-TLS density and low TSP (L-TSP) were independent and favorable prognostic factors of nmCRC patients, which might provide new directions for targeted therapy in the CRC tumor microenvironment, especially the tumor immune microenvironment.
Topics: Colonic Neoplasms; Colorectal Neoplasms; Eosine Yellowish-(YS); Hematoxylin; Humans; Prognosis; Rectal Neoplasms; Tertiary Lymphoid Structures; Tumor Microenvironment
PubMed: 36189233
DOI: 10.3389/fimmu.2022.962056 -
BioMed Research International 2017. In routine histopathology, decalcification is an essential step for mineralized tissues. The purpose of this study is to evaluate the effects of different...
. In routine histopathology, decalcification is an essential step for mineralized tissues. The purpose of this study is to evaluate the effects of different decalcification solutions on the morphological and antigenicity preservation in Sprague Dawley (SD) rat femurs. . Four different decalcification solutions were employed to remove the mineral substances from rat femurs, including 10% neutral buffered EDTA, 3% nitric acid, 5% nitric acid, and 8% hydrochloric acid/formic acid. Shaking and low temperature were used to process the samples. The stainings of hematoxylin-eosin (HE) and immunohistochemical (IHC) were employed to evaluate the bone morphology and antigenicity. . Different decalcification solutions may affect the quality of morphology and the staining of paraffin-embedded sections in pathological examinations. Among four decalcifying solutions, 3% nitric acid is the best decalcifying agent for HE staining. 10% neutral buffered EDTA and 5% nitric acid are the preferred decalcifying agents for IHC staining. . The current study investigated the effects of different decalcifying agents on the preservation of the bone structure and antigenicity, which will help to develop suitable protocols for the analyses of the bony tissue.
Topics: Animals; Antigens; Decalcification Technique; Eosine Yellowish-(YS); Female; Femur; Hematoxylin; Image Processing, Computer-Assisted; Immunohistochemistry; Rats, Sprague-Dawley; Solutions; Staining and Labeling; Time Factors
PubMed: 28246608
DOI: 10.1155/2017/9050754 -
Frontiers in Immunology 2022Neuroinflammation following spinal cord injury (SCI) results in prolonged neurological damage and locomotor dysfunction. Polarization of microglia is vital to regulation...
BACKGROUND
Neuroinflammation following spinal cord injury (SCI) results in prolonged neurological damage and locomotor dysfunction. Polarization of microglia is vital to regulation of neuroinflammation, although the underlying mechanisms have not yet been elucidated. Endocannabinoid receptor subtype 2 (CB2R) is reported to ameliorate neurodegeneration immunomodulation activities. However, the underlying machinery in the context of SCI remains unclear.
METHODS
A lipopolysaccharide-induced microglia inflammation model and a mouse model of SCI were employed to investigate the regulatory role of CB2R in the polarization of microglia in response to excess neuroinflammation. Markers of inflammation and autophagy were measured by Western blot analysis, immunofluorescence, flow cytometry, and enzyme-linked immunosorbent assays. Histological staining with hematoxylin and eosin, Nissl, and Luxol fast blue was conducted using commercial kits. The locomotor function of the hindlimbs of the experimental mice was evaluated with the Basso Mouse Scale, Louisville Swim Scale, and footprint assay.
RESULTS
The results showed that CB2R promoted M2 differentiation, increased interleukin (IL)-10 expression, and inhibited M1 differentiation with decreased expression of IL-1β and IL-6. CB2R activation also increased ubiquitination of the NLRP3 inflammasome and interacted with the autophagy-related proteins p62 and microtubule-associated proteins 1B light chain 3. Treatment with the CB2R activator JWH-133 reduced loss of myelin, apoptosis of neurons, and glial scarring, leading to improved functional recovery of the hindlimbs, while the CB2R antagonist AM630 produced opposite results.
CONCLUSION
Taken together, these results suggested that CB2R activation attenuated neuroinflammation targeting microglial polarization by promoting NLRP3 clearance, thereby facilitating functional recovery post-SCI.
Topics: Animals; Autophagy; Autophagy-Related Proteins; Endocannabinoids; Eosine Yellowish-(YS); Hematoxylin; Inflammasomes; Inflammation; Interleukin-6; Lipopolysaccharides; Mice; Microtubule-Associated Proteins; NLR Family, Pyrin Domain-Containing 3 Protein; Neuroinflammatory Diseases; Receptors, Cannabinoid; Spinal Cord Injuries
PubMed: 36238284
DOI: 10.3389/fimmu.2022.993168 -
The Lancet. Digital Health Feb 2023Endometrial cancer can be molecularly classified into POLE, mismatch repair deficient (MMRd), p53 abnormal (p53abn), and no specific molecular profile (NSMP) subgroups.... (Randomized Controlled Trial)
Randomized Controlled Trial
Interpretable deep learning model to predict the molecular classification of endometrial cancer from haematoxylin and eosin-stained whole-slide images: a combined analysis of the PORTEC randomised trials and clinical cohorts.
BACKGROUND
Endometrial cancer can be molecularly classified into POLE, mismatch repair deficient (MMRd), p53 abnormal (p53abn), and no specific molecular profile (NSMP) subgroups. We aimed to develop an interpretable deep learning pipeline for whole-slide-image-based prediction of the four molecular classes in endometrial cancer (im4MEC), to identify morpho-molecular correlates, and to refine prognostication.
METHODS
This combined analysis included diagnostic haematoxylin and eosin-stained slides and molecular and clinicopathological data from 2028 patients with intermediate-to-high-risk endometrial cancer from the PORTEC-1 (n=466), PORTEC-2 (n=375), and PORTEC-3 (n=393) randomised trials and the TransPORTEC pilot study (n=110), the Medisch Spectrum Twente cohort (n=242), a case series of patients with POLE endometrial cancer in the Leiden Endometrial Cancer Repository (n=47), and The Cancer Genome Atlas-Uterine Corpus Endometrial Carcinoma cohort (n=395). PORTEC-3 was held out as an independent test set and a four-fold cross validation was performed. Performance was measured with the macro and class-wise area under the receiver operating characteristic curve (AUROC). Whole-slide images were segmented into tiles of 360 μm resized to 224 × 224 pixels. im4MEC was trained to learn tile-level morphological features with self-supervised learning and to molecularly classify whole-slide images with an attention mechanism. The top 20 tiles with the highest attention scores were reviewed to identify morpho-molecular correlates. Predictions of a nuclear classification deep learning model serve to derive interpretable morphological features. We analysed 5-year recurrence-free survival and explored prognostic refinement by molecular class using the Kaplan-Meier method.
FINDINGS
im4MEC attained macro-average AUROCs of 0·874 (95% CI 0·856-0·893) on four-fold cross-validation and 0·876 on the independent test set. The class-wise AUROCs were 0·849 for POLE (n=51), 0·844 for MMRd (n=134), 0·883 for NSMP (n=120), and 0·928 for p53abn (n=88). POLE and MMRd tiles had a high density of lymphocytes, p53abn tiles had strong nuclear atypia, and the morphology of POLE and MMRd endometrial cancer overlapped. im4MEC highlighted a low tumour-to-stroma ratio as a potentially novel characteristic feature of the NSMP class. 5-year recurrence-free survival was significantly different between im4MEC predicted molecular classes in PORTEC-3 (log-rank p<0·0001). The ten patients with aggressive p53abn endometrial cancer that was predicted as MMRd showed inflammatory morphology and appeared to have a better prognosis than patients with correctly predicted p53abn endometrial cancer (p=0·30). The four patients with NSMP endometrial cancer that was predicted as p53abn showed higher nuclear atypia and appeared to have a worse prognosis than patients with correctly predicted NSMP (p=0·13). Patients with MMRd endometrial cancer predicted as POLE had an excellent prognosis, as do those with true POLE endometrial cancer.
INTERPRETATION
We present the first interpretable deep learning model, im4MEC, for haematoxylin and eosin-based prediction of molecular endometrial cancer classification. im4MEC robustly identified morpho-molecular correlates and could enable further prognostic refinement of patients with endometrial cancer.
FUNDING
The Hanarth Foundation, the Promedica Foundation, and the Swiss Federal Institutes of Technology.
Topics: Female; Humans; Eosine Yellowish-(YS); Hematoxylin; Deep Learning; Pilot Projects; Endometrial Neoplasms
PubMed: 36496303
DOI: 10.1016/S2589-7500(22)00210-2