Low Concordance Between T-Cell Densities in Matched Primary Tumors and Liver Metastases in Microsatellite Stable Colorectal Cancer

ICOSeg: Real-Time ICOS Protein Expression Segmentation from Immunohistochemistry Slides Using a Lightweight Conv-Transformer Network

Simple Summary

Inducible T-cell COStimulator (ICOS) is a biomarker of interest in checkpoint inhibitor therapy, and as a means of assessing T-cell regulation as part of a complex process of adaptive immunity. The aim of our study is to segment the ICOS positive cells using a lightweight deep-learning segmentation network. We aim to assess the potential of a convolutional neural network and transformer together that permits the capture of relevant features from immunohistochemistry images. The proposed study achieved remarkable results compared to the existing biomedical segmentation methods on our in-house dataset and surpassed our previous analysis by only utilizing the Efficient-UNet network.

Abstract

In this article, we propose ICOSeg, a lightweight deep learning model that accurately segments the immune-checkpoint biomarker, Inducible T-cell COStimulator (ICOS) protein in colon cancer from immunohistochemistry (IHC) slide patches. The proposed model relies on the MobileViT network that includes two main components: convolutional neural network (CNN) layers for extracting spatial features; and a transformer block for capturing a global feature representation from IHC patch images. The ICOSeg uses an encoder and decoder sub-network. The encoder extracts the positive cell’s salient features (i.e., shape, texture, intensity, and margin), and the decoder reconstructs important features into segmentation maps. To improve the model generalization capabilities, we adopted a channel attention mechanism that added to the bottleneck of the encoder layer. This approach highlighted the most relevant cell structures by discriminating between the targeted cell and background tissues. We performed extensive experiments on our in-house dataset. The experimental results confirm that the proposed model achieves more significant results against state-of-the-art methods, together with an 8× reduction in parameters.

Electroporation and Immunotherapy-Unleashing the Abscopal Effect

Simple Summary

Electrochemotherapy and irreversible electroporation are primarily used for treating patients with cutaneous and subcutaneous tumors and pancreatic cancer, respectively. Increasing numbers of studies have shown that the treatments may elicit an immune response in addition to eliminating the tumor cells. The purpose of this review is to give an in-depth introduction to the electroporation-induced immune response and the local and peripheral immune systems, and to describe the various studies investigating the combination of electroporation and immunotherapy. The review may help guide and inspire the design of future clinical trials investigating the potential synergy of electroporation and immunotherapy in cancer treatment.

Abstract

The discovery of electroporation in 1968 has led to the development of electrochemotherapy (ECT) and irreversible electroporation (IRE). ECT and IRE have been established as treatments of cutaneous and subcutaneous tumors and locally advanced pancreatic cancer, respectively. Interestingly, the treatment modalities have been shown to elicit immunogenic cell death, which in turn can induce an immune response towards the tumor cells. With the dawn of the immunotherapy era, the potential of combining ECT and IRE with immunotherapy has led to the launch of numerous studies. Data from the first clinical trials are promising, and new combination regimes might change the way we treat tumors characterized by low immunogenicity and high levels of immunosuppression, such as melanoma and pancreatic cancer. In this review we will give an introduction to ECT and IRE and discuss the impact on the immune system. Additionally, we will present the results of clinical and preclinical trials, investigating the combination of electroporation modalities and immunotherapy.