A Multi-Modal Toolkit for Studying Neutrophils in Cancer and Beyond

Multimodal Approach of Optical Coherence Tomography and Raman Spectroscopy Can Improve Differentiating Benign and Malignant Skin Tumors in Animal Patients

Simple Summary

Skin and subcutaneous tumors are among the most frequent neoplasms in dogs and cats. We studied 51 samples of canine and feline skin, lipomas, soft tissue sarcomas, and mast cell tumors using a multimodal approach based on optical coherence tomography and Raman spectroscopy. A supervised machine learning algorithm detected malignant tumors with the sensitivity and specificity of 94% and 98%, respectively. The proposed multimodal algorithm is a novel approach in veterinary oncology that can outperform the existing clinical methods such as the fine-needle aspiration method.

Abstract

As in humans, cancer is one of the leading causes of companion animal mortality. Up to 30% of all canine and feline neoplasms appear on the skin or directly under it. There are only a few available studies that have investigated pet tumors by biophotonics techniques. In this study, we acquired 1115 optical coherence tomography (OCT) images of canine and feline skin, lipomas, soft tissue sarcomas, and mast cell tumors ex vivo, which were subsequently used for automated machine vision analysis. The OCT images were analyzed using a scanning window with a size of 53 × 53 μm. The distributions of the standard deviation, mean, range, and coefficient of variation values were acquired for each image. These distributions were characterized by their mean, standard deviation, and median values, resulting in 12 parameters in total. Additionally, 1002 Raman spectral measurements were made on the same samples, and features were generated by integrating the intensity of the most prominent peaks. Linear discriminant analysis (LDA) was used for sample classification, and sensitivities/specificities were acquired by leave-one-out cross-validation. Three datasets were analyzed—OCT, Raman, and combined. The combined OCT and Raman data enabled the best sample differentiation with the sensitivities of 0.968, 1, and 0.939 and specificities of 0.956, 1, and 0.977 for skin, lipomas, and malignant tumors, respectively. Based on these results, we concluded that the proposed multimodal approach, combining Raman and OCT data, can accurately distinguish between malignant and benign tissues.

Engineering complexity in human tissue models of cancer

Major progress in the understanding and treatment of cancer have tremendously improved our knowledge of this complex disease and improved the length and quality of patients' lives. Still, major challenges remain, in particular with respect to cancer metastasis which still escapes effective treatment and remains responsible for 90% of cancer related deaths. In recent years, the advances in cancer cell biology, oncology and tissue engineering converged into the engineered human tissue models of cancer that are increasingly recapitulating many aspects of cancer progression and response to drugs, in a patient-specific context. The complexity and biological fidelity of these models, as well as the specific questions they aim to investigate, vary in a very broad range. When selecting and designing these experimental models, the fundamental question is "how simple is complex enough" to accomplish a specific goal of cancer research. Here we review the state of the art in developing and using the human tissue models in cancer research and developmental drug screening. We describe the main classes of models providing different levels of biological fidelity and complexity, discuss their advantages and limitations, and propose a framework for designing an appropriate model for a given study. We close by outlining some of the current needs, opportunities and challenges in this rapidly evolving field.

Combining nanotechnology with the multifunctional roles of neutrophils against cancer and inflammatory disease

Neutrophils, the most abundant leukocytes in humans, play a crucial role in acute inflammation during infection and tumorigenesis. Neutrophils are the major types of cells recruited to the inflammation sites induced by pathogens, exhibiting great homing ability towards inflammatory disorders and tumor sites. Therefore, a neutrophil-based drug delivery system (NDDS) has become a promising platform for anti-cancer and anti-inflammatory treatment. Recent decades have witnessed the huge progress of applying nanomaterials in drug delivery. Nanomaterials are regarded as innovative components to enrich the field of neutrophil-based therapies due to their unique physiochemical characteristics. In this review, the latest advancement of combining diverse nanomaterials with an NDDS for cancer and inflammatory disease treatment will be summarized. It is discussed how nanomaterials empower the therapeutic area of an NDDS and how an NDDS circumvents the limitations of nanomaterials. Moreover, based on the finding that neutrophils are closely involved in the progression of cancer and inflammatory diseases, emerging therapeutic strategies that target neutrophils will be outlined. Finally, as neutrophils were demonstrated to play a central role in the immunopathology of COVID-19, which causes necroinflammation that is responsible for the cytokine storm and sepsis during coronavirus infections, novel therapeutic approaches that anchor neutrophils against the pathological consequences related to COVID-19 will be highlighted as well.

CXCR2 Mediates Distinct Neutrophil Behavior in Brain Metastatic Breast Tumor

Brain metastasis is one of the main causes of mortality among breast cancer patients, but the origins and the mechanisms that drive this process remain poorly understood. Here, we report that the upregulation of certain CXCR2-associated ligands in the brain metastatic variants of the breast cancer cells (BrM) dynamically activate the corresponding CXCR2 receptors on the neutrophils, thereby resulting in the modulation of certain key functional neutrophil responses towards the BrM. Using established neutrophil-tumor biomimetic co-culture models, we show that the upregulation of CXCR2 increases the recruitment of Tumor-Associated Neutrophils (TANs) towards the BrM, to enable location-favored formation of Neutrophil Extracellular Traps (NETs). Inhibition of CXCR2 using small molecule antagonist AZD5069 reversed this behavior, limiting the neutrophil responses to the BrM and retarding the reciprocal tumor development. We further demonstrate that abrogation of NETs formation using Neutrophil Elastase Inhibitor (NEI) significantly decreases the influx of neutrophils towards BrM but not to their parental tumor, suggesting that CXCR2 activation could be used by the brain metastatic tumors as a mechanism to program the tumor-infiltrating TANs into a pro-NETotic state, so as to assume a unique spatial distribution that assists in the subsequent migration and invasion of the metastatic tumor cells. This new perspective indicates that CXCR2 is a critical target for suppressing neutrophilic inflammation in brain metastasis.