High-Quality Immunohistochemical Stains Through Computational Assay Parameter Optimization

Inhibition of USP7 enhances CD8+ T cell activity in liver cancer by suppressing PRDM1-mediated FGL1 upregulation

Lymphocyte activation gene 3 (LAG3), an immune checkpoint molecule expressed on activated T cells, functions as a negative regulator of immune responses. Persistent antigen exposure in the tumor microenvironment results in sustained LAG3 expression on T cells, contributing to T cell dysfunction. Fibrinogen-like protein 1 (FGL1) has been identified as a major ligand of LAG3, and FGL1/LAG3 interaction forms a novel immune checkpoint pathway that results in tumor immune evasion. In addition, ubiquitin-specific peptidase 7 (USP7) plays a crucial role in cancer development. In this study we investigated the role of USP7 in modulation of FGL1-mediated liver cancer immune evasion. We showed that knockdown of USP7 or treatment with USP7 inhibitor P5091 suppressed liver cancer growth by promoting CD8+ T cell activity in Hepa1-6 xenograft mice and in HepG2 or Huh7 cells co-cultured with T cells, whereas USP7 overexpression produced the opposite effect. We found that USP7 upregulated FGL1 in HepG2 and Huh7 cells by deubiquitination of transcriptional factor PR domain zinc finger protein 1 (PRDM1), which transcriptionally activated FGL1, and attenuated the CD8+ T cell activity, leading to the liver cancer growth. Interestingly, USP7 could be transcriptionally stimulated by PRDM1 as well in a positive feedback loop. P5091, an inhibitor of USP7, was able to downregulate FGL1 expression, thus enhancing CD8+ T cell activity. In an immunocompetent liver cancer mouse model, the dual blockade of USP7 and LAG3 resulted in a superior antitumor activity compared with anti-LAG3 therapy alone. We conclude that USP7 diminishes CD8+ T cell activity by a USP7/PRDM1 positive feedback loop on FGL1 production in liver cancer; USP7 might be a promising target for liver cancer immunotherapy.

Aspirin triggers ferroptosis in hepatocellular carcinoma cells through restricting NF-κB p65-activated SLC7A11 transcription

A number of studies have shown that aspirin, as commonly prescribed drug, prevents the development of hepatocellular carcinoma (HCC). Ferroptosis as a dynamic tumor suppressor plays a vital role in hepatocarcinogenesis. In this study we investigated whether aspirin affected ferroptosis in liver cancer cells. RNA-seq analysis revealed that aspirin up-regulated 4 ferroptosis-related drivers and down-regulated 5 ferroptosis-related suppressors in aspirin-treated HepG2 cells. Treatment with aspirin (4 mM) induced remarkable ferroptosis in HepG2 and Huh7 cells, which was enhanced by the ferroptosis inducer erastin (10 μM). We demonstrated that NF-κB p65 restricted ferroptosis in HepG2 and Huh7 cells through directly binding to the core region of SLC7A11 promoter and activating the transcription of ferroptosis inhibitor SLC7A11, whereas aspirin induced ferroptosis through inhibiting NF-κB p65-activated SLC7A11 transcription. Overexpression of p65 rescued HepG2 and Huh7 cells from aspirin-induced ferroptosis. HCC patients with high expression levels of SLC7A11 and p65 presented lower survival rate. Functionally, NF-κB p65 blocked the aspirin-induced ferroptosis in vitro and in vivo, which was attenuated by erastin. We conclude that aspirin triggers ferroptosis by restricting NF-κB-activated SLC7A11 transcription to suppress the growth of HCC. These results provide a new insight into the mechanism by which aspirin regulates ferroptosis in hepatocarcinogenesis. A combination of aspirin and ferroptosis inducer may provide a potential strategy for the treatment of HCC in clinic.

Current Developments of Artificial Intelligence in Digital Pathology and Its Future Clinical Applications in Gastrointestinal Cancers

The implementation of DP will revolutionize current practice by providing pathologists with additional tools and algorithms to improve workflow. Furthermore, DP will open up opportunities for development of AI-based tools for more precise and reproducible diagnosis through computational pathology. One of the key features of AI is its capability to generate perceptions and recognize patterns beyond the human senses. Thus, the incorporation of AI into DP can reveal additional morphological features and information. At the current rate of AI development and adoption of DP, the interest in computational pathology is expected to rise in tandem. There have already been promising developments related to AI-based solutions in prostate cancer detection; however, in the GI tract, development of more sophisticated algorithms is required to facilitate histological assessment of GI specimens for early and accurate diagnosis. In this review, we aim to provide an overview of the current histological practices in AP laboratories with respect to challenges faced in image preprocessing, present the existing AI-based algorithms, discuss their limitations and present clinical insight with respect to the application of AI in early detection and diagnosis of GI cancer.

Quantifying Antibody Binding Kinetics on Fixed Cells and Tissues via Fluorescence Lifetime Imaging

We present a method for monitoring spatially localized antigen-antibody binding events on physiologically relevant substrates (cell and tissue sections) using fluorescence lifetime imaging. Specifically, we use the difference between the fluorescence decay times of fluorescently tagged antibodies in free solution and in the bound state to track the bound fraction over time and hence deduce the binding kinetics. We make use of a microfluidic probe format to minimize the mass transport effects and localize the analysis to specific regions of interest on the biological substrates. This enables measurement of binding constants (k_on) on surface-bound antigens and on cell blocks using model biomarkers. Finally, we directly measure p53 kinetics with differential biomarker expression in ovarian cancer tissue sections, observing that the degree of expression corresponds to the changes in k_on, with values of 3.27-3.50 × 10³ M^-1 s^-1 for high biomarker expression and 2.27-2.79 × 10³ M^-1 s^-1 for low biomarker expression.

Rapid micro-immunohistochemistry

We present a new and versatile implementation of rapid and localized immunohistochemical staining of tissue sections. Immunohistochemistry (IHC) comprises a sequence of specific biochemical reactions and allows the detection of specific proteins in tissue sections. For the rapid implementation of IHC, we fabricated horizontally oriented microfluidic probes (MFPs) with functionally designed apertures to enable square and circular footprints, which we employ to locally expose a tissue to time-optimized sequences of different biochemicals. We show that the two main incubation steps of IHC protocols can be performed on MDAMB468-1510A cell block sections in less than 30 min, compared to incubation times of an hour or more in standard protocols. IHC analysis on the timescale of tens of minutes could potentially be applied during surgery, enabling clinicians to react in more dynamically and efficiently. Furthermore, this rapid IHC implementation along with conservative tissue usage has strong potential for the implementation of multiplexed assays, allowing the exploration of optimal assay conditions with a small amount of tissue to ensure high-quality staining results for the remainder of the sample.