Kim Myung-Chul, Borcherding Nicholas, Song Woo-Jin, Kolb Ryan, Zhang Weizhou
Veterinary Laboratory Medicine, Clinical Pathology, College of Veterinary Medicine, Jeju National University, Jeju, Republic of Korea.
Research Institute of Veterinary Medicine, College of Veterinary Medicine, Jeju National University, Jeju, Republic of Korea.
Front Vet Sci. 2024 Sep 23;11:1434617. doi: 10.3389/fvets.2024.1434617. eCollection 2024.
Single-cell RNA sequencing (scRNA-seq) has become an essential tool for uncovering the complexities of various physiological and immunopathological conditions in veterinary medicine. However, there is currently limited information on immune-suppressive cancer subsets in canine breast cancers. In this study, we aimed to identify and characterize immune-suppressive subsets of triple-negative canine breast cancer (TNBC) by utilizing integrated scRNA-seq data from published datasets.
Published scRNA-seq datasets, including data from six groups of 30 dogs, were subjected to integrated bioinformatic analysis.
Immune modulatory TNBC subsets were identified through functional enrichment analysis using immune-suppressive gene sets, including those associated with anti-inflammatory and M2-like macrophages. Key immune-suppressive signaling, such as viral infection, angiogenesis, and leukocyte chemotaxis, was found to play a role in enabling TNBC to evade immune surveillance. In addition, interactome analysis revealed significant interactions between distinct subsets of cancer cells and effector T cells, suggesting potential T-cell suppression.
The present study demonstrates a versatile and scalable approach to integrating and analyzing scRNA-seq data, which successfully identified immune-modulatory subsets of canine TNBC. It also revealed potential mechanisms through which TNBC promotes immune evasion in dogs. These findings are crucial for advancing the understanding of the immune pathogenesis of canine TNBC and may aid in the development of new immune-based therapeutic strategies.
单细胞RNA测序（scRNA-seq）已成为揭示兽医学中各种生理和免疫病理状况复杂性的重要工具。然而，目前关于犬乳腺癌中免疫抑制性癌症亚群的信息有限。在本研究中，我们旨在利用已发表数据集中的整合scRNA-seq数据，识别并表征三阴性犬乳腺癌（TNBC）的免疫抑制性亚群。
对已发表的scRNA-seq数据集，包括来自6组共30只犬的数据，进行整合生物信息学分析。
通过使用免疫抑制基因集进行功能富集分析，确定了免疫调节性TNBC亚群，包括与抗炎和M2样巨噬细胞相关的亚群。发现关键的免疫抑制信号，如病毒感染、血管生成和白细胞趋化作用，在使TNBC逃避免疫监视中发挥作用。此外，相互作用组分析揭示了癌细胞不同亚群与效应T细胞之间的显著相互作用，提示潜在的T细胞抑制。
本研究展示了一种通用且可扩展的整合和分析scRNA-seq数据的方法，成功识别了犬TNBC的免疫调节性亚群。它还揭示了TNBC促进犬免疫逃逸的潜在机制。这些发现对于推进对犬TNBC免疫发病机制的理解至关重要，可能有助于开发新的基于免疫的治疗策略。
