Investigate heterogeneous neutrophils in NSCLC

尽管进行了多次尝试，但仅在中性粒细胞中失去SiglecF表达的小鼠模式具有不可预见的缺陷：它不能在任何细胞类型中表达SiglecF，这可能是由于未知的表观遗传效应。因此，我们决定寻找调节肿瘤内中性粒细胞发育的上游调节因子，并基于我们的单细胞RNA测序和单细胞ATAC（转座酶可降解染色质测定）测序数据将RUNX 1鉴定为潜在的转录因子。我们生成了仅在成熟中性粒细胞中缺乏RUNX 1的小鼠模型（Ly 6 G-Cre; RUNX 1-flox），并发现肿瘤浸润性中性粒细胞中SiglecF+中性粒细胞显著增加。这是第一个可以调节肿瘤浸润性中性粒细胞发育的转录因子，为了解异质性肿瘤浸润性中性粒细胞奠定了基础。为了进一步研究其在GEM模型中对肿瘤进展的影响，我们建立了骨髓嵌合体GEM模型，其免疫系统在成熟的中性粒细胞中缺乏RUNX 1。为了在NSCLC的GEM模型中更精确和无偏地测量肿瘤负荷，我们与CCR人工智能资源合作。我们开发了一种用于自动肿瘤定量的人工智能算法。我们的手稿，“人工智能为基础的肿瘤分割在小鼠模型肺腺癌，”发表在病理学信息学杂志。

Despite multiple attempts, the mouse mode supposed only to lose SiglecF expression in neutrophils has an unforeseen defect: it can't express SiglecF in any cell type, likely due to unknown epigenetic effects. Therefore, we decided to find upstream regulators modulating intratumor neutrophil development and identified RUNX1 as a potential transcription factor based on our single-cell RNA sequencing with single-cell ATAC (Assay for Transposase-Accessible Chromatin) sequencing data. We generated a mouse model lacking RUNX1 only in matured neutrophils (Ly6G-Cre; RUNX1-flox) and discovered a significant increase of SiglecF+ neutrophils in tumor-infiltrating neutrophils. This is the first transcription factor that can regulate tumor-infiltrating neutrophil development, laying the groundwork for understanding the heterogeneous tumor-infiltrating neutrophils. To further study its impact on tumor progression in a GEM model, we have created a bone marrow chimera GEM model with an immune system lacking RUNX1 in matured neutrophils. To have a more precise and unbiased measurement of tumor burden in the GEM model of NSCLC, we collaborated with CCR Artificial Intelligence Resource. We developed an artificial intelligence algorithm for automatic tumor quantification. Our manuscript, "Artificial Intelligence-based Tumor Segmentation in Mouse Models of Lung Adenocarcinoma," was published in the Journal of Pathology Informatics.