ABCA7在结直肠癌中的临床价值及转录调控机制

doi:10.3969/j.issn.1674-8115.2025.11.008

摘要/Abstract

摘要：

目的·探讨ATP结合盒转运蛋白A7（ATP-binding cassette subfamily A member 7，ABCA7）基因在结直肠癌（colorectal cancer，CRC）中的预后评估价值，为CRC的精准诊断和个性化治疗提供新型分子标志物。方法·从肿瘤免疫单细胞数据库（Tumor Immune Single-cell Hub，TISCH）获取CRC的单细胞转录组数据，从基因表达综合（Gene Expression Omnibus，GEO）数据库下载GSM8594571样本的空间转录组数据（基于10x Genomics Visium平台），从癌症基因组图谱（The Cancer Genome Atlas，TCGA）数据库提取TCGA-COAD和TCGA-READ项目的转录组数据。通过多组学整合分析策略，利用单细胞转录组数据解析ABCA7在不同细胞亚群的表达模式，结合空间转录组数据探究其在肿瘤及邻近组织中的空间分布特征；采用比例风险回归模型（proportional hazards model，Cox模型）评估ABCA7的预后价值；通过成簇规律间隔短回文重复序列（clustered regularly interspaced short palindromic repeats，CRISPR）敲除技术结合CERES算法验证其对CRC细胞增殖的影响；利用Cistrome数据库的ChIP-seq数据及Pearson相关性分析，构建ABCA7与转录因子锌指BTB结构域蛋白33（zinc finger BTB domain-containing protein 33，ZBTB33）、核因子κB抑制因子（nuclear factor-κB-repressing factor，NKRF）的转录调控网络。结果·分析发现，ABCA7在CRC恶性细胞中显著高表达，尤其在Ki-67高表达的肿瘤组织中表达进一步上调，且肿瘤组织中ABCA7mRNA表达显著高于正常组织（P<0.05），具有一定诊断效能［受试者操作特征（receiver operating characteristic，ROC）曲线下面积（area under curve，AUC）=0.686］。敲除ABCA7可显著抑制 CRC细胞系（如C75、CL11）的增殖能力。ABCA7高表达组患者的总生存期（overall survival，OS）、疾病特异性生存期（disease-specific survival，DSS）和无进展生存期（progression-free interval，PFI）均显著缩短（均P<0.05）。表观遗传分析显示，ZBTB33和NKRF可直接结合ABCA7基因调控区域，形成ZBTB33/NKRF-ABCA7转录调控轴，且三者在CRC中均显著上调表达（P<0.05）。结论·ABCA7在CRC中高表达且与不良预后相关，ZBTB33/NKRF-ABCA7调控轴可能是驱动CRC进展的关键机制。

关键词: ATP结合盒转运蛋白A7, 结直肠癌, 空间转录组, 单细胞测序, CRISPR技术, 表观遗传, 转录调控轴

Abstract:

Objective ·To investigate the prognostic value of the ATP-binding cassette subfamily A member 7 (ABCA7) gene in colorectal cancer (CRC) and provide a novel molecular marker for the precise diagnosis and personalized treatment of CRC. Methods ·Single-cell transcriptome data of CRC were retrieved from the Tumor Immune Single-cell Hub (TISCH). Spatial transcriptome data of sample GSM8594571 (based on the 10x Genomics Visium platform) were downloaded from the Gene Expression Omnibus (GEO) database. Transcriptome data from the TCGA-COAD and TCGA-READ projects were extracted from The Cancer Genome Atlas (TCGA) database. Using a multi-omics integration analysis strategy, single-cell transcriptome data were employed to analyze the expression patterns of ABCA7 in different cell subpopulations and were combined with spatial transcriptome data to explore its spatial distribution characteristics in tumor and adjacent tissues. The Cox Proportional Hazards Model (Cox) was used to evaluate the prognostic value of ABCA7. The effect of ABCA7 on CRC cell proliferation was verified using Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) knockout technology combined with the CERES algorithm. The transcriptional regulatory network between ABCA7 and the transcription factors zinc finger BTB domain-containing protein 33 (ZBTB33) and Nuclear factor-κB-repressing factor (NKRF) was constructed using chromatin immunoprecipitation sequencing (ChIP-seq) data from the Cistrome database and Pearson correlation analysis. Results ·The analysis revealed that ABCA7 was significantly overexpressed in CRC malignant cells, with further upregulation particularly in tumor tissues with high Ki-67 expression. Moreover, the mRNA expression of ABCA7 in tumor tissues was significantly higher than that in normal tissues (P<0.05), showing certain diagnostic efficacy [area under the curve (AUC) of the receiver operating characteristic (ROC) curve=0.686]. Knockout of ABCA7 significantly inhibited the proliferative capacity of CRC cell lines (e.g., C75, CL11). Patients in the ABCA7 high-expression group had significantly shorter overall survival (OS), disease-specific survival (DSS), and progression-free interval (PFI) (all P<0.05). Epigenetic analysis showed that ZBTB33 and NKRF could directly bind to the regulatory region of the ABCA7 gene, forming a ZBTB33/NKRF-ABCA7 transcriptional regulatory axis, and all three were significantly upregulated in CRC (P<0.05). Conclusion ·ABCA7 is highly expressed in CRC and associated with poor prognosis. The ZBTB33/NKRF-ABCA7 regulatory axis may be a key mechanism driving CRC progression.

Key words: ATP-binding cassette subfamily A member 7 (ABCA7), colorectal cancer, spatial transcriptomics, single-cell sequencing, CRISPR technology, epigenetics, transcriptional regulatory axis

中图分类号:

R735.3

孙瑞状, 乔坤朋, 李璞, 徐小莲, 孟俊. ABCA7在结直肠癌中的临床价值及转录调控机制[J]. 上海交通大学学报（医学版）, 2025, 45(11): 1490-1501.

SUN Ruizhuang, QIAO Kunpeng, LI Pu, XU Xiaolian, MENG Jun. Clinical value and transcriptional regulatory mechanism of ABCA7 in colorectal cancer[J]. Journal of Shanghai Jiao Tong University (Medical Science), 2025, 45(11): 1490-1501.

图/表 7

图1 ABCA7 单细胞测序数据展示CRC恶性细胞中 ABCA7 的表达分布Note： A. Subgroup division of multiple CRC single-cell sequencing datasets, displaying the expression distribution of ABCA7 in different CRC cell subgroups. B. Identification of CRC and microenvironmental cell types (including endothelial cells, intestinal epithelial cells, malignant cells, etc.) using t-SNE dimensionality reduction clustering. C. Pie charts presenting the proportion of different cell types in CRC samples, reflecting the dominance of malignant cells. D. t-SNE visualization of ABCA7 expression distribution in CRC cells, with color gradients indicating differences in expression levels. E. Heatmap analysis of differentially expressed genes in CRC, showing gene expression patterns in subgroups and screening for differential genes. F. t-SNE display of the expression distribution of key CRC genes (CEACAM5, TP53, BRAF, etc.) in cells.

Fig 1 Single-cell sequencing data of ABCA7 showing the expression distribution of ABCA7 in malignant cells of CRC

图2 ABCA7 在CRC活性组织中细胞的空间转录组表达分布Note： A. H-E staining of the first group of CRC tissues. B. Spatial transcriptome showing the expression distribution of MKi-67 in CRC tissues, with a color gradient (0-8) representing expression levels. C. Spatial transcriptome presenting the expression distribution of ABCA7 in CRC tissues, with a color gradient (0-6) reflecting expression levels, suggesting high expression of ABCA7 in active tissue cells of CRC. D. H&E staining image of the second group of CRC tissues. E. Mapping of ABCA7 expression values to tissue space, with scatter points and color shading showing the expression distribution, quantifying and visualizing differences and accurately indicating its high expression in active tissue cells of CRC.

Fig 2 Spatial transcriptome showing the expression distribution of ABCA7 in active tissue cells of CRC

图3 ABCA7 在CRC中mRNA水平的表达及其对CRC细胞生长的影响Note： A. Violin plot comparing tumor and normal tissues, showing high mRNA expression of ABCA7 in CRC. B. ROC curve evaluating the diagnostic efficacy of ABCA7 mRNA for CRC, with an AUC of 0.686 (95% CI 0.626‒0.747). C. CRISPR screening results showing CRISPR scores corresponding to different sgRNAs, with CRISPR score<0 suggesting that ABCA7 promotes CRC cell growth.

Fig 3 mRNA expression level of ABCA7 in CRC and its effect on CRC cell growth

图4 ABCA7在CRC正常组织和肿瘤组织中的免疫组化染色图Note： A. CRC tissue: low magnification (×20) showing tumor gland distribution, and high magnification (×40) showing positive staining of ABCA7 in tumor cells. B. NON-CRC normal tissue: low magnification (×20) presenting normal tissue morphology, and high magnification (×40) showingABCA7 expression in normal cells.

Fig 4 Immunohistochemical staining images of ABCA7 in normal and tumor tissues of CRC

图5 ABCA7 在CRC中mRNA水平的表达与预后相关性Note： A. Overall survival (OS) cohort: low-expression group (n=239, events=39) vs high-expression group (n=238, events=64). B. Disease-specific survival (DSS) cohort: low-expression group (n=234, events=24) vs high-expression group (n=227, events=40). C. Progression-free interval (PFI) cohort: low- expression group (n=239, events=54) vs high-expression group (n=238, events=74).

Fig 5 mRNA expression level of ABCA7 in CRC and its correlation with prognosis

图6 ABCA7 与CRC中高表达的 ZBTB33 和 NKRF 的共表达分析Note： A. Pearson and Spearman analyses screening genes co-expressed with ABCA7 (r>0.7, P<0.05. e.g., ZBTB33, NKRF), with scatter plots showing expression correlation. B. mRNA expression of ZBTB33 and NKRF in CRC tumor tissues (purple) vs normal tissues (blue), showing higher expression in tumor tissues. C. Survival curves indicating a higher overall survival probability in CRC patients with low ZBTB33 and NKRF expression (ZBTB33: HR=0.80, P=0.263; NKRF: HR=1.14, P=0.517), reflecting the association between co-expressed genes and prognosis. D. Knockout experiments showing downregulated ABCA7 expression after NKRF and ZBTB33 knockout, revealing their transcriptional regulatory effect on ABCA7.

Fig 6 Co-expression analysis of ABCA7 with highly expressed ZBTB33 and NKRF in CRC

图7 ABCA7 对 CRC 中高表达 ZBTB33 和 NKRF 的表观遗传调控及基因网络解析Note： Integration of multi-omics data (chromatin accessibility, gene expression, epigenetic regulatory elements, etc.) to present the epigenetic regulatory effect of ABCA7 on highly expressed ZBTB33 and NKRF in CRC, and analysis of CRC gene regulatory network through chromatin status and binding element regulation.

Fig 7 Epigenetic regulation of ABCA7 on highly expressed ZBTB33 and NKRF in CRC and analysis of gene network

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