Conventional histological and cytological staining with simultaneous immunohistochemistry enabled by invisible chromogens

Digital analysis of the prostate tumor microenvironment with high-order chromogenic multiplexing

As our understanding of the tumor microenvironment grows, the pathology field is increasingly utilizing multianalyte diagnostic assays to understand important characteristics of tumor growth. In clinical settings, brightfield chromogenic assays represent the gold-standard and have developed significant trust as the first-line diagnostic method. However, conventional brightfield tests have been limited to low-order assays that are visually interrogated. We have developed a hybrid method of brightfield chromogenic multiplexing that overcomes these limitations and enables high-order multiplex assays. However, how compatible high-order brightfield multiplexed images are with advanced analytical algorithms has not been extensively evaluated. In the present study, we address this gap by developing a novel 6-marker prostate cancer assay that targets diverse aspects of the tumor microenvironment such as prostate-specific biomarkers (PSMA and p504s), immune biomarkers (CD8 and PD-L1), a prognostic biomarker (Ki-67), as well as an adjunctive diagnostic biomarker (basal cell cocktail) and apply the assay to 143 differentially graded adenocarcinoma prostate tissues. The tissues were then imaged on our spectroscopic multiplexing imaging platform and mined for proteomic and spatial features that were correlated with cancer presence and disease grade. Extracted features were used to train a UMAP model that differentiated healthy from cancerous tissue with an accuracy of 89% and identified clusters of cells based on cancer grade. For spatial analysis, cell-to-cell distances were calculated for all biomarkers and differences between healthy and adenocarcinoma tissues were studied. We report that p504s positive cells were at least 2× closer to cells expressing PD-L1, CD8, Ki-67, and basal cell in adenocarcinoma tissues relative to the healthy control tissues. These findings offer a powerful insight to understand the fingerprint of the prostate tumor microenvironment and indicate that high-order chromogenic multiplexing is compatible with digital analysis. Thus, the presented chromogenic multiplexing system combines the clinical applicability of brightfield assays with the emerging diagnostic power of high-order multiplexing in a digital pathology friendly format that is well-suited for translational studies to better understand mechanisms of tumor development and growth.

Genome-wide RNA-Seq identifies TP53-mediated embryonic stem cells inhibiting tumor invasion and metastasis

The discovery of embryonic stem cell (ESC) mediating tumoricidal activity revealed the intimate relationship between ESCs and tumor cells, but the functional role of ESCs in tumor progression is poorly understood. To further investigate tumor cell and ESC interactions, we co-cultured mouse ESCs with mouse pancreatic cancer Pan02 cells or mouse melanoma B16-F10 cells in Transwell, and found that tumor cell invasion was significantly inhibited by ESCs. Application of ESCs to tumor-bearing mice resulted in significant inhibition of tumor metastasis in vivo. RNA-Seq analyses of tumor cell and ESC co-cultures identified TP53 and related signalling as major pathways involved in ESC-mediated inhibition of tumor cell invasion and metastasis, which indicated the potential clinical application of ESCs to treat cancer.

MSGM: An Advanced Deep Multi-Size Guiding Matching Network for Whole Slide Histopathology Images Addressing Staining Variation and Low Visibility Challenges

Matching whole slide histopathology images to provide comprehensive information on homologous tissues is beneficial for cancer diagnosis. However, the challenge arises with the Giga-pixel whole slide images (WSIs) when aiming for high-accuracy matching. Learning-based methods are difficult to generalize well with large-size WSIs, necessitating the integration of traditional matching methods to enhance accuracy as the size increases. In this paper, we propose a multi-size guiding matching method applicable high-accuracy requirements. Specifically, we design learning multiscale texture to train deep descriptors, called TDescNet, that trains 64 × 64 × 256 and 256 × 256 × 128 size convolution layer as C64 and C256 descriptors to overcome staining variation and low visibility challenges. Furthermore, we develop the 3D-ring descriptor using sparse keypoints to support the description of large-size WSIs. Finally, we employ C64, C256, and 3D-ring descriptors to progressively guide refined local matching, utilizing geometric consistency to identify correct matching results. Experiments show that when matching WSIs of size 4096 × 4096 pixels, our average matching error is 123.48 μm and the success rate is 93.02 % in 43 cases. Notably, our method achieves an average improvement of 65.52 μm in matching accuracy compared to recent state-of-the-art methods, with enhancements ranging from 36.27 μm to 131.66 μm. Therefore, we achieve high-fidelity whole-slice image matching, and overcome staining variation and low visibility challenges, enabling assistance in comprehensive cancer diagnosis through matched WSIs.

CytoGAN: Unpaired staining transfer by structure preservation for cytopathology image analysis

With the development of digital pathology, deep learning is increasingly being applied to endometrial cell morphology analysis for cancer screening. And cytology images with different staining may degrade the performance of these analysis algorithms. To address the impact of staining patterns, many strategies have been proposed and hematoxylin and eosin (H&E) images have been transferred to other staining styles. However, none of the existing methods are able to generate realistic cytological images with preserved cellular layout, and many important clinical structural information is lost. To address the above issues, we propose a different staining transformation model, CytoGAN, which can quickly and realistically generate images with different staining styles. It includes a novel structure preservation module that preserves the cell structure well, even if the resolution or cell size between the source and target domains do not match. Meanwhile, a stain adaptive module is designed to help the model generate realistic and high-quality endometrial cytology images. We compared our model with ten state-of-the-art stain transformation models and evaluated by two pathologists. Furthermore, in the downstream endometrial cancer classification task, our algorithm improves the robustness of the classification model on multimodal datasets, with more than 20 % improvement in accuracy. We found that generating specified specific stains from existing H&E images improves the diagnosis of endometrial cancer. Our code will be available on github.

Dexmedetomidine facilitates autophagic flux to promote liver regeneration by suppressing GSK3β activity in mouse partial hepatectomy

INTRODUCTION

Dexmedetomidine (DEX), a highly selective α2-adrenergic receptor agonist, is widely used for sedation and anesthesia in patients undergoing hepatectomy. However, the effect of DEX on autophagic flux and liver regeneration remains unclear.

OBJECTIVES

This study aimed to determine the role of DEX in hepatocyte autophagic flux and liver regeneration after PHx.

METHODS

In mice, DEX was intraperitoneally injected 5 min before and 6 h after PHx. In vitro, DEX was co-incubated with culture medium for 24 h. Autophagic flux was detected by LC3-II and SQSTM1 expression levels in primary mouse hepatocytes and the proportion of red puncta in AML-12 cells transfected with FUGW-PK-hLC3 plasmid. Liver regeneration was assessed by cyclinD1 expression, Edu incorporation, H&E staining, ki67 immunostaining and liver/body ratios. Bafilomycin A1, si-GSK3β and Flag-tagged GSK3β, α2-ADR antagonist, GSK3β inhibitor, AKT inhibitor were used to identify the role of GSK3β in DEX-mediated autophagic flux and hepatocyte proliferation.

RESULTS

Pre- and post-operative DEX treatment promoted liver regeneration after PHx, showing 12 h earlier than in DEX-untreated mice, accompanied by facilitated autophagic flux, which was completely abolished by bafilomycin A1 or α2-ADR antagonist. The suppression of GSK3β activity by SB216763 and si-GSK3β enhanced the effect of DEX on autophagic flux and liver regeneration, which was abolished by AKT inhibitor.

CONCLUSION

Pre- and post-operative administration of DEX facilitates autophagic flux, leading to enhanced liver regeneration after partial hepatectomy through suppression of GSK3β activity in an α2-ADR-dependent manner.

Automated Whole Slide Imaging for Label-Free Histology Using Photon Absorption Remote Sensing Microscopy

OBJECTIVE

Pathologists rely on histochemical stains to impart contrast in thin translucent tissue samples, revealing tissue features necessary for identifying pathological conditions. However, the chemical labeling process is destructive and often irreversible or challenging to undo, imposing practical limits on the number of stains that can be applied to the same tissue section. Here we present an automated label-free whole slide scanner using a PARS microscope designed for imaging thin, transmissible samples.

METHODS

Peak SNR and in-focus acquisitions are achieved across entire tissue sections using the scattering signal from the PARS detection beam to measure the optimal focal plane. Whole slide images (WSI) are seamlessly stitched together using a custom contrast leveling algorithm. Identical tissue sections are subsequently H&E stained and brightfield imaged. The one-to-one WSIs from both modalities are visually and quantitatively compared.

RESULTS

PARS WSIs are presented at standard 40x magnification in malignant human breast and skin samples. We show correspondence of subcellular diagnostic details in both PARS and H&E WSIs and demonstrate virtual H&E staining of an entire PARS WSI. The one-to-one WSI from both modalities show quantitative similarity in nuclear features and structural information.

CONCLUSION

PARS WSIs are compatible with existing digital pathology tools, and samples remain suitable for histochemical, immunohistochemical, and other staining techniques.

SIGNIFICANCE

This work is a critical advance for integrating label-free optical methods into standard histopathology workflows.

Novel Chromogens for Immunohistochemistry in Spatial Biology

Spatial relations between tumor cells and host-infiltrating cells are increasingly important in both basic science and clinical research. In this study, we have tested the feasibility of using standard methods of immunohistochemistry (IHC) in a multiplex staining system using a newly developed set of chromogenic substrates for the peroxidase and alkaline phosphatase enzymes. Using this approach, we have developed a set of chromogens characterized by (1) providing fine cellular detail, (2) non-overlapping spectral profiles, (3) an absence of interactions between chromogens, (4) stability when stored, and (5) compatibility with current standard immunohistochemistry practices. When viewed microscopically under brightfield illumination, the chromogens yielded the following colors: red, black, blue, yellow, brown, and green. By selecting compatible color combinations, we have shown feasibility for four-color multiplex staining. Depending on the particular type of analysis being performed, visual analysis, without the aid of computer-assisted image analysis, was sufficient to differentiate up to four different markers.

RNA sequencing of formalin fixed paraffin-embedded heart tissue provides transcriptomic information about chemotherapy-induced cardiotoxicity

Gene expression of formalin-fixed paraffin-embedded (FFPE) tissue may serve for molecular studies on cardiovascular diseases. Chemotherapeutics, such as doxorubicin (DOX) may cause heart injury, but the mechanisms of these side effects of DOX are not well understood. This study aimed to investigate whether DOX-induced gene expression in archival FFPE heart tissue in experimental rats would correlate with the gene expression in fresh-frozen heart tissue by applying RNA sequencing technology. The results showed RNA from FFPE samples was degraded, resulting in a lower number of uniquely mapped reads. However, DOX-induced differentially expressed genes in FFPE were related to molecular mechanisms of DOX-induced cardiotoxicity, such as inflammation, calcium binding, endothelial dysfunction, senescence, and cardiac hypertrophy signaling. Our data suggest that, despite the limitations, RNA sequencing of archival FFPE heart tissue supports utilizing FFPE tissues from retrospective studies on cardiovascular disorders, including DOX-induced cardiotoxicity.

A Novel Validated Real-World Dataset for the Diagnosis of Multiclass Serous Effusion Cytology according to the International System and Ground-Truth Validation Data

INTRODUCTION

The application of artificial intelligence (AI) algorithms in serous fluid cytology is lacking due to the deficiency in standardized publicly available datasets. Here, we develop a novel public serous effusion cytology dataset. Furthermore, we apply AI algorithms on it to test its diagnostic utility and safety in clinical practice.

METHODS

The work is divided into three phases. Phase 1 entails building the dataset based on the multitiered evidence-based classification system proposed by the International System (TIS) of serous fluid cytology along with ground-truth tissue diagnosis for malignancy. To ensure reliable results of future AI research on this dataset, we carefully consider all the steps of the preparation and staining from a real-world cytopathology perspective. In phase 2, we pay special consideration to the image acquisition pipeline to ensure image integrity. Then we utilize the power of transfer learning using the convolutional layers of the VGG16 deep learning model for feature extraction. Finally, in phase 3, we apply the random forest classifier on the constructed dataset.

RESULTS

The dataset comprises 3,731 images distributed among the four TIS diagnostic categories. The model achieves 74% accuracy in this multiclass classification problem. Using a one-versus-all classifier, the fallout rate for images that are misclassified as negative for malignancy despite being a higher risk diagnosis is 0.13. Most of these misclassified images (77%) belong to the atypia of undetermined significance category in concordance with real-life statistics.

CONCLUSION

This is the first and largest publicly available serous fluid cytology dataset based on a standardized diagnostic system. It is also the first dataset to include various types of effusions and pericardial fluid specimens. In addition, it is the first dataset to include the diagnostically challenging atypical categories. AI algorithms applied on this novel dataset show reliable results that can be incorporated into actual clinical practice with minimal risk of missing a diagnosis of malignancy. This work provides a foundation for researchers to develop and test further AI algorithms for the diagnosis of serous effusions.

Arresting the G2/M phase empowers synergy in magnetic nanomanipulator-based cancer mechanotherapy and chemotherapy

Using mechanical cues for cancer cells can realize precise control and efficient therapeutic effects. However, the cell cycle-specific response for dynamic mechanical manipulation is barely investigated. Here, RGD-modified iron oxide nanomanipulators were utilized as the intracellular magneto-mechanical transducers to investigate the mechanical impacts on the cell cycle under a dynamic magnetic field for cancer treatment. The G2/M phase was identified to be sensitive to the intracellular magneto-mechanical modulation with a synergistic treatment effect between the pretreatment of cell cycle-specific drugs and the magneto-mechanical destruction, and thus could be an important mechanical-targeted phase for regulation of cancer cell death. Finally, combining the cell cycle-specific drugs with magneto-mechanical manipulation could significantly inhibit glioma and breast cancer growth in vivo. This intracellular mechanical stimulus showed cell cycle-dependent cytotoxicity and could be developed as a spatiotemporal therapeutic modality in combination with chemotherapy drugs for treating deep-seated tumors.

Establishing in vivo and ex vivo chick embryo models to investigate fetal tendon healing

Injured adult tendons heal fibrotically and possess high re-injury rates, whereas fetal tendons appear to heal scarlessly. However, knowledge of fetal tendon wound healing is limited due in part to the need for an accessible animal model. Here, we developed and characterized an in vivo and ex vivo chick embryo tendon model to study fetal tendon healing. In both models, injury sites filled rapidly with cells and extracellular matrix during healing, with wound closure occurring faster in vivo. Tendons injured at an earlier embryonic stage improved mechanical properties to levels similar to non-injured controls, whereas tendons injured at a later embryonic stage did not. Expression levels of tendon phenotype markers, collagens, collagen crosslinking regulators, matrix metalloproteinases, and pro-inflammatory mediators exhibited embryonic stage-dependent trends during healing. Apoptosis occurred during healing, but ex vivo tendons exhibited higher levels of apoptosis than tendons in vivo. Future studies will use these in vivo and ex vivo chick embryo tendon injury models to elucidate mechanisms of stage-specific fetal tendon healing to inform the development of therapeutic approaches to regeneratively heal adult tendons.

Exploring heterogeneity of tumor immune cells and adrenal cells in aldosterone-producing adenomas using single-cell RNA-seq and investigating differences by sex

The mechanism behind the higher incidence of aldosterone-producing adenoma (APA) in women compared to men is not yet understood. In this study, we utilized single-cell RNA sequencing (scRNA-seq) to investigate the immune cell infiltration and adrenal cell characteristics in APA. Our findings revealed a high presence of immune cells in the tumor microenvironment, with macrophages and T lymphocytes being the most prevalent. Comparison of infiltrating cells between males and females showed that female CD8+T cells had stronger cytotoxic and inflammation-related functions, while female myeloid cells had more enrichment in inflammatory pathways. Additionally, we found that female adrenal cells had greater upregulation of immune-related and antigen presentation pathways. Furthermore, our analysis revealed that zona glomerulosa (ZG) cells had a higher capability for aldosterone synthesis. These results provide a deeper understanding of the APA microenvironment in patients of different sexes and offer new insights into the onset of APA.

Mechano-bioconjugation Strategy Empowering Fusion Protein Therapeutics with Aggregation Resistance, Prolonged Circulation, and Enhanced Antitumor Efficacy

Bioconjugation is a powerful protein modification strategy to improve protein properties. Herein, we report mechano-bioconjugation as a novel approach to empower fusion protein therapeutics and demonstrate its utility by a protein heterocatenane (cat-IFN-ABD) containing interferon-α2b (IFN) mechanically interlocked with a consensus albumin-binding domain (ABD). The conjugate was selectively synthesized in cellulo following a cascade of post-translational events using a pair of heterodimerizing p53dim variants and two orthogonal split-intein reactions. The catenane topology was proven by combined techniques of LC-MS, SDS-PAGE, SEC, and controlled proteolytic digestion. Not only did cat-IFN-ABD retain activities comparable to those of the wild-type IFN and ABD, the conjugate also exhibited enhanced aggregation resistance and prolonged circulation time over the simple linear and cyclic fusions. Consequently, cat-IFN-ABD potently inhibited tumor growth in the mouse xenograft model. Therefore, mechano-bioconjugation by catenation accomplishes function integration with additional benefits, providing an alternative pathway for developing advanced protein therapeutics.

Ultrafast 3D histological imaging based on a minutes-time scale tissue clearing and multidirectional selective plane illumination microscopy

Conventional histopathological examinations are time-consuming and labor-intensive, and are insufficient to depict 3D pathological features intuitively. Here we report an ultrafast 3D histological imaging scheme based on optimized selective plane illumination microscopy (mSPIM), a minutes-time scale clearing method (FOCM), and a deep learning-based image enhancement algorithm (SRACNet) to realize histological preparation and imaging of clinical tissues. Our scheme enables 1-minute clearing and fast imaging (up to 900 mm²/min) of 200 µm-thick mouse kidney slices at micron-level resolution. With hematoxylin and eosin analog, we demonstrated the detailed 3D morphological connections between glomeruli and the surrounding tubules, which is difficult to identify in conventional 2D histology. Further, by the preliminary verification on human kidney tissues, this study will provide new, to the best of our knowledge, feasible histological solutions and inspirations in future 3D digital pathology.