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Abstract：
BACKGROUND: An understanding of mechanisms underlying colorectal cancer (CRC) development and progression is yet to be fully elucidated. This study aims to employ network theoretic approaches to analyse single cell transcriptomic data from CRC to better characterize its progression and sided-ness.
METHODS: We utilized a recently published single-cell RNA sequencing data (GEO-GSE178341) and parsed the cell X gene data by stage and side (right and left colon). Using Weighted Gene Co-expression Network Analysis (WGCNA), we identified gene modules with varying preservation levels (weak or strong) of network topology between early (pT1) and late stages (pT234), and between right and left colons. Spearman\'s rank correlation (ρ) was used to assess the similarity or dissimilarity in gene connectivity.
RESULTS: Equalizing cell counts across different stages, we detected 13 modules for the early stage, two of which were non-preserved in late stages. Both non-preserved modules displayed distinct gene connectivity patterns between the early and late stages, characterized by low ρ values. One module predominately dealt with myeloid cells, with genes mostly enriched for cytokine-cytokine receptor interaction potentiallystimulating myeloid cells to participate in angiogenesis. The second module, representing a subset of epithelial cells, was mainly enriched for carbohydrate digestion and absorption, influencing the gut microenvironment through the breakdown of carbohydrates. In the comparison of left vs. right colons, two of 12 modules identified in the right colon were non-preserved in the left colon. One captured a small fraction of epithelial cells and was enriched for transcriptional misregulation in cancer, potentially impacting communication between epithelial cells and the tumor microenvironment. The other predominantly contained B cells with a crucial role in maintaining human gastrointestinal health and was enriched for B-cell receptor signalling pathway.
CONCLUSIONS: We identified modules with topological and functional differences specific to cell types between the early and late stages, and between the right and left colons. This study enhances the understanding of roles played by different cell types at different stages and sides, providing valuable insights for future studies focused on the diagnosis and treatment of CRC.
METHODS: We utilized a recently published single-cell RNA sequencing data (GEO-GSE178341) and parsed the cell X gene data by stage and side (right and left colon). Using Weighted Gene Co-expression Network Analysis (WGCNA), we identified gene modules with varying preservation levels (weak or strong) of network topology between early (pT1) and late stages (pT234), and between right and left colons. Spearman\'s rank correlation (ρ) was used to assess the similarity or dissimilarity in gene connectivity.
RESULTS: Equalizing cell counts across different stages, we detected 13 modules for the early stage, two of which were non-preserved in late stages. Both non-preserved modules displayed distinct gene connectivity patterns between the early and late stages, characterized by low ρ values. One module predominately dealt with myeloid cells, with genes mostly enriched for cytokine-cytokine receptor interaction potentiallystimulating myeloid cells to participate in angiogenesis. The second module, representing a subset of epithelial cells, was mainly enriched for carbohydrate digestion and absorption, influencing the gut microenvironment through the breakdown of carbohydrates. In the comparison of left vs. right colons, two of 12 modules identified in the right colon were non-preserved in the left colon. One captured a small fraction of epithelial cells and was enriched for transcriptional misregulation in cancer, potentially impacting communication between epithelial cells and the tumor microenvironment. The other predominantly contained B cells with a crucial role in maintaining human gastrointestinal health and was enriched for B-cell receptor signalling pathway.
CONCLUSIONS: We identified modules with topological and functional differences specific to cell types between the early and late stages, and between the right and left colons. This study enhances the understanding of roles played by different cell types at different stages and sides, providing valuable insights for future studies focused on the diagnosis and treatment of CRC.
摘要：
背景：对结直肠癌（CRC）发展和进展的潜在机制的理解尚未完全阐明。本研究旨在采用网络理论方法分析来自CRC的单细胞转录组数据，以更好地表征其进展和边远性。
方法：我们利用了最近发表的单细胞RNA测序数据（GEO-GSE178341），并通过分期和侧面（右侧和左侧结肠）分析了细胞X基因数据。使用加权基因共表达网络分析(WGCNA)，我们确定了早期（pT1）和晚期（pT234）之间网络拓扑的不同保存水平（弱或强）的基因模块，在左右冒号之间。使用Spearman等级相关(ρ)来评估基因连通性的相似性或差异性。
结果：均衡不同阶段的细胞计数，我们在早期阶段检测到13个模块，其中两个在后期未保存。两个未保留的模块在早期和晚期之间显示出不同的基因连接模式，以ρ值低为特征。一个模块主要处理骨髓细胞，主要富含细胞因子-细胞因子受体相互作用的基因可能刺激骨髓细胞参与血管生成。第二个模块，代表上皮细胞的一个子集，主要富含碳水化合物的消化吸收，通过碳水化合物的分解影响肠道微环境。在左与左的比较右冒号,在右结肠中确定的12个模块中有两个在左结肠中未保留。一个人捕获了一小部分上皮细胞，并富集了癌症中的转录失调，可能影响上皮细胞和肿瘤微环境之间的通讯。另一种主要包含B细胞，在维持人类胃肠道健康中起关键作用，并富集了B细胞受体信号通路。
结论：我们确定了在早期和晚期之间具有特定于细胞类型的拓扑和功能差异的模块，在左右冒号之间。这项研究增强了对不同细胞类型在不同阶段和侧面所起作用的理解，为未来关注CRC诊断和治疗的研究提供有价值的见解。
方法：我们利用了最近发表的单细胞RNA测序数据（GEO-GSE178341），并通过分期和侧面（右侧和左侧结肠）分析了细胞X基因数据。使用加权基因共表达网络分析(WGCNA)，我们确定了早期（pT1）和晚期（pT234）之间网络拓扑的不同保存水平（弱或强）的基因模块，在左右冒号之间。使用Spearman等级相关(ρ)来评估基因连通性的相似性或差异性。
结果：均衡不同阶段的细胞计数，我们在早期阶段检测到13个模块，其中两个在后期未保存。两个未保留的模块在早期和晚期之间显示出不同的基因连接模式，以ρ值低为特征。一个模块主要处理骨髓细胞，主要富含细胞因子-细胞因子受体相互作用的基因可能刺激骨髓细胞参与血管生成。第二个模块，代表上皮细胞的一个子集，主要富含碳水化合物的消化吸收，通过碳水化合物的分解影响肠道微环境。在左与左的比较右冒号,在右结肠中确定的12个模块中有两个在左结肠中未保留。一个人捕获了一小部分上皮细胞，并富集了癌症中的转录失调，可能影响上皮细胞和肿瘤微环境之间的通讯。另一种主要包含B细胞，在维持人类胃肠道健康中起关键作用，并富集了B细胞受体信号通路。
结论：我们确定了在早期和晚期之间具有特定于细胞类型的拓扑和功能差异的模块，在左右冒号之间。这项研究增强了对不同细胞类型在不同阶段和侧面所起作用的理解，为未来关注CRC诊断和治疗的研究提供有价值的见解。
