Dadlani Ekta, Dash Tirtharaj, Sahoo Debashis
bioRxiv. 2025 Feb 6:2023.08.01.551559. doi: 10.1101/2023.08.01.551559.
Tumor-associated Macrophages (or TAMs) are amongst the most common cells that play a significant role in the initiation and progression of colorectal cancer (CRC). [Ghosh et al., 2023] have built a Boolean-logic dependent model to propose a set of gene signatures capable of identifying macrophage polarization states. The signature, called the Signature of Macrophage Reactivity and Tolerance (SMaRT), comprises of 338 human genes (equivalently, 298 mouse genes). The SMaRT signature was constructed using datasets that were not specialized towards any particular disease. To specifically investigate macrophage polarization in CRC, in this paper, we (a) perform a comprehensive analysis of the SMaRT signature on single-cell human and mouse colorectal cancer RNA-seq datasets and (b) adopt transfer learning to construct a "refined" SMaRT signature that specifically characterizes TAM polarization in the CRC tumor microenvironment. Towards validation of our refined gene signature, we use: (a) 5 RNA-seq datasets derived from single-cell human datasets; and (b) 5 large-cohort microarray datasets from humans. Furthermore, we propose the translational potential of our refined gene signature while investigating microsatellite stability and CpG island methylator phenotype (CIMP) in colorectal cancer. Overall, our refined gene signature and its extensive validation provide a path for its adoption in clinical practice in diagnosing colorectal cancer and associated attributes.
The data, codes, and software packages used in our research are linked and shared publicly at https://github.com/tirtharajdash/TAMs-CRC .
肿瘤相关巨噬细胞（或TAMs）是在结直肠癌（CRC）的发生和发展中起重要作用的最常见细胞之一。[戈什等人，2023年]构建了一个基于布尔逻辑的模型，以提出一组能够识别巨噬细胞极化状态的基因特征。该特征称为巨噬细胞反应性和耐受性特征（SMaRT），由338个人类基因（相当于298个小鼠基因）组成。SMaRT特征是使用并非专门针对任何特定疾病的数据集构建的。为了具体研究CRC中的巨噬细胞极化，在本文中，我们（a）对单细胞人类和小鼠结直肠癌RNA测序数据集上的SMaRT特征进行了全面分析，并且（b）采用迁移学习来构建一个“精炼”的SMaRT特征，该特征专门表征CRC肿瘤微环境中的TAM极化。为了验证我们精炼的基因特征，我们使用：（a）来自单细胞人类数据集的5个RNA测序数据集；以及（b）来自人类的5个大型队列微阵列数据集。此外，我们在研究结直肠癌的微卫星稳定性和CpG岛甲基化表型（CIMP）时提出了我们精炼的基因特征的转化潜力。总体而言，我们精炼的基因特征及其广泛的验证为其在临床实践中用于诊断结直肠癌及相关属性提供了一条途径。
我们研究中使用的数据、代码和软件包在https://github.com/tirtharajdash/TAMs-CRC上公开链接和共享。
