PO.CL01.13 · 临床研究
Stereo-seq 空间转录组学揭示细胞类型对前列腺癌转移的贡献
Stereoseq spatial transcriptomics reveals cell-type contributions to prostate cancer metastasis
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摘要 Abstract
中文摘要
前列腺癌仍是男性发病和死亡的重要原因,其中非裔美国(AA)男性承受着不成比例的疾病负担。尽管分子分析已推进了我们的认识,但驱动恶性进展和转移潜能的细胞起源及空间微环境转变仍未完全明确。为刻画这些转变,我们使用 STEREO-seq(空间增强分辨率组学测序)对取自三名 AA 男性的良性(n = 1)和恶性(n = 2)前列腺组织进行了高分辨率空间转录组刻画,在所有样本中生成了 83,144 个细胞区块(cell-bin)。数据使用 STEREO-seq 分析工作流程(SAW v6.0)处理,并用 Stereopy 和 Seurat 进行分析。细胞类型注释使用 Azimuth 以前列腺细胞图谱(Prostate Cell Atlas)为参考进行,严格的质量过滤(>20% 线粒体 RNA 或注释置信度 <0.5)后得到 63,861 个高置信度注释。空间生态位刻画使用 QUICHE(定量细胞间生态位富集)进行,以定义微环境结构和细胞间生态系统。组成分析揭示了恶性组织中棒状(club)上皮(CE)细胞的显著扩增,其富集程度与肿瘤分级相关,并伴随成纤维细胞的明显减少。高级别病变中的 CE 细胞显示 LTF 强烈上调(avg_log2FC = 6.92,padj = 7.9 × 10⁻⁶⁷),而成纤维细胞则表现出肌动蛋白相关基因(ACTG2、ACTA2、ACTB)的广泛丧失,提示细胞骨架破坏和微环境重塑。基底上皮细胞显示 KRT15 表达近乎完全丧失(avg_log2FC = -4.92,padj = 6.1 × 10⁻²⁸¹),提示结构性上皮群体的耗竭和腺体失稳。QUICHE 分析揭示了高度富集 CE 细胞的独特肿瘤相关空间生态位,而富含成纤维细胞的生态位则主导良性区域。生态位水平的差异表达重现了全局转录组模式,包括肿瘤抑制基因活性的丧失、腺体结构的结构性崩解,以及与侵袭和转移相关通路的激活。这些发现凸显了前列腺癌恶性转化过程中伴随的细胞组成和空间组织的重大转变。ST 刻画鉴定出 CE 细胞驱动的生态位和与转移潜能强相关的转录组特征,提供了新的生物标志物和空间定义的细胞相互作用,增进了我们对 AA 男性 PCa 进展的理解。这一空间分辨的框架为未来旨在剖析转移的微环境驱动因素和开发细胞类型特异性治疗策略的研究奠定了基础。
查看英文原文 English abstract
Prostate cancer remains a significant cause of morbidity and mortality among men, with African-American (AA) men experiencing a disproportionate disease burden. Although molecular profiling has advanced our understanding, the cellular origins and spatial microenvironmental transitions that drive malignant progression and metastatic potential remain incompletely defined. To characterize these transitions, we performed high-resolution spatial transcriptomic profiling on benign (n = 1) and malignant (n = 2) prostate tissues obtained from three AA men using STEREO-seq (SpaTial Enhanced REsolution Omics-sequencing), generating 83,144 cell-bins across all samples. Data were processed using the STEREO-seq Analysis Workflow (SAW v6.0) and analyzed with Stereopy and Seurat. Cell-type annotation was performed using Azimuth with the Prostate Cell Atlas as a reference, and stringent quality filters (>20% mitochondrial RNA or annotation confidence <0.5) resulted in 63,861 high-confidence annotations. Spatial niche characterization was performed using QUICHE (QUantitative InterCellular nicHe Enrichment) to define microenvironmental structure and cell-cell ecosystems. Compositional analysis revealed a pronounced expansion of club epithelial (CE) cells in malignant tissues, with enrichment correlating with tumor grade, accompanied by a marked reduction in fibroblasts. CE cells in high-grade lesions showed strong upregulation of LTF (avg_log2FC = 6.92, padj = 7.9 × 10⁻⁶⁷), while fibroblasts exhibited widespread loss of actin-associated genes (ACTG2, ACTA2, ACTB), indicating cytoskeletal disruption and microenvironmental remodeling. Basal epithelial cells displayed near-complete loss of KRT15 expression (avg_log2FC = -4.92, padj = 6.1 × 10⁻²⁸¹), suggesting depletion of structural epithelial populations and glandular destabilization. QUICHE analysis revealed distinct tumor-associated spatial niches highly enriched for CE cells, whereas fibroblast-rich niches dominated benign regions. Differential niche-level expression recapitulated global transcriptomic patterns, including loss of tumor suppressor gene activity, architectural breakdown of glandular structures, and activation of pathways implicated in invasion and metastasis. These findings highlight substantial shifts in cellular composition and spatial organization accompanying malignant transformation in prostate cancer. ST profiling identified CE-cell-driven niches and transcriptomic signatures strongly associated with metastatic potential, offering novel biomarkers and spatially defined cellular interactions that improve our understanding of PCa progression in African-American men. This spatially resolved framework provides a foundation for future studies aimed at dissecting microenvironmental drivers of metastasis and developing cell-type-specific therapeutic strategies.
利益披露 Disclosure
J. Panzer, None..
S. Carskadon, None..
A. Levin, None..
S. Huang, None..
V. Kumar, None..
I. Adrianto, None..
N. Palanisamy, None.