肿瘤细胞治疗研究
英文原题：A computational pipeline for identifying gene targets and signalling pathways in cancer cells to improve lymphocyte infiltration and immune checkpoint therapy efficacy.
本研究不仅建立了一个用于发现癌细胞中阻断T细胞浸润的新基因靶点和信号通路的计算流程，还为在实体瘤中改善淋巴细胞浸润和ICB疗效的进一步探索提供了基因靶点库。
TIL（肿瘤浸润淋巴细胞）（TILs）对于实体瘤中有效的免疫检查点阻断（ICB）治疗至关重要。然而，约70%的这类肿瘤表现出淋巴细胞浸润不良，导致ICB疗法效果较差。
我们开发了一个生物信息学流程，整合了多个先前未考虑的因素或数据集，包括肿瘤细胞免疫相关通路、拷贝数变异（CNV）、单肿瘤细胞测序数据，以及肿瘤mRNA-seq数据和患者生存数据，以识别可能改善T细胞浸润和增强ICB疗效的靶点。此外，我们进行了湿实验，并成功验证了排名靠前的一个基因。
我们将这一流程应用于癌症基因组图谱（TCGA）的实体瘤中，并在18种癌症类型中鉴定出一组可能改善淋巴细胞浸润和ICB疗效的基因，为进一步探索提供了有价值的药物靶点资源。重要的是，我们在小鼠结肠癌同源模型中实验验证了SUN1，此前SUN1并未与T细胞浸润和ICB治疗相关联，但基于该流程，它是3种癌症类型中排名最靠前的基因靶点之一。我们发现Sun1 KO可显著增强抗原呈递、增加T细胞浸润并改善抗PD1治疗疗效。此外，通过单细胞多组学分析，我们鉴定出亚基因调控网络（sub-GRNs），显示Stat蛋白在增强Sun1-KO癌细胞中免疫相关通路方面发挥重要作用。
BACKGROUND: Tumour-infiltrating lymphocytes (TILs) are crucial for effective immune checkpoint blockade (ICB) therapy in solid tumours. However, ∼70% of these tumours exhibit poor lymphocyte infiltration, rendering ICB therapies less effective. METHODS: We developed a bioinformatics pipeline integrating multiple previously unconsidered factors or datasets, including tumour cell immune-related pathways, copy number variation (CNV), and single tumour cell sequencing data, as well as tumour mRNA-seq data and patient survival data, to identify targets that can potentially improve T cell infiltration and enhance ICB efficacy. Furthermore, we conducted wet-lab experiments and successfully validated one of the top-identified genes. FINDINGS: We applied this pipeline in solid tumours of the Cancer Genome Atlas (TCGA) and identified a set of genes in 18 cancer types that might potentially improve lymphocyte infiltration and ICB efficacy, providing a valuable drug target resource to be further explored. Importantly, we experimentally validated SUN1, which had not been linked to T cell infiltration and ICB therapy previously, but was one of the top-identified gene targets among 3 cancer types based on the pipeline, in a mouse colon cancer syngeneic model. We showed that Sun1 KO could significantly enhance antigen presentation, increase T-cell infiltration, and improve anti-PD1 treatment efficacy. Moreover, with a single-cell multiome analysis, we identified subgene regulatory networks (sub-GRNs) showing Stat proteins play important roles in enhancing the immune-related pathways in Sun1-KO cancer cells. INTERPRETATION: This study not only established a computational pipeline for discovering new gene targets and signalling pathways in cancer cells that block T-cell infiltration, but also provided a gene target pool for further exploration in improving lymphocyte infiltration and ICB efficacy in solid tumours. FUNDING: A full list of funding bodies that contributed to this study can be found in the Acknowledgements section.
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