PO.TB10.07 · 肿瘤生物学
空间揭示PanIN来源和IPMN来源PDAC中的恶性细胞和微环境生态系统
Spatially revealed malignant and microenvironment ecosystems in PanIN- and IPMN-derived PDAC
作者与单位 Authors & Affiliations
摘要 Abstract
中文摘要
引言:胰腺导管腺癌(PDAC)起源于不同的前驱病变,主要为胰腺上皮内瘤变(PanINs)和导管内乳头状黏液性肿瘤(IPMNs),二者在遗传学、分化生态系统和临床行为方面存在差异。PanIN来源的PDAC通常表现出更多的分子和空间异质性,伴有显著的经典型-基底型分化。IPMN来源的腺癌表现出不同的组织学类型:肠型病变常发展为胶样癌,而起源于胰胆管(PB)型IPMN的腺癌类似于传统的PanIN来源PDAC。明确前驱病变来源如何塑造恶性状态和空间微环境生态系统对于PDAC分类至关重要。
方法:采用CosMx SMI(Bruker)全转录组和6K-panel进行单细胞空间转录组学分析。使用了两个不同的组织微阵列(TMAs)队列(1.5-mm核心),包括PanIN来源PDAC(15例患者)和IPMN来源PDAC(10例患者)。通过CellPose进行细胞分割,并采用严格的质量控制(QC)阈值,最终获得459,195个高质量细胞。数据经log标准化,并使用scVI进行患者水平校正的整合。通过结合专家组织病理学比对和基于Leiden的细化进行分层注释。下游空间分析使用基于Python的方法,包括Squidpy。
结果:跨队列整合揭示了恶性空间图谱中显著的来源依赖性分化。PanIN-PDAC中的恶性上皮表现出更高的异质性,具有更多样化和分散的细胞状态。相比之下,IPMN来源PDAC中的肿瘤细胞对每种癌症类型呈现出明显的分化特征。肠型IPMN PDAC发展出独特的恶性program,表现出典型的杯状细胞样亚型,这在其他IPMN型PDAC或PanIN来源PDAC中均未观察到。然而,PB型IPMN-PDAC与PanIN-PDAC显示出显著相似性,共享多个恶性program,主要包括pEMT、祖细胞样和ADM样亚型。此外,PanIN-PDAC保留了特定的肿瘤program,如外分泌样、鳞状和炎症相关基底样。值得注意的是,尽管IPMN PDAC中的PB型与PanIN-PDAC在某些肿瘤状态上具有相似性,但进一步分析揭示了肿瘤与微环境(TME)之间在空间模式和细胞通讯方面的显著差异。这提示微环境可能存在不同的演化。
结论:前驱病变来源从根本上塑造了PDAC的恶性状态和基质-免疫生态系统。总之,本研究建立了理解PDAC异质性的空间框架,并强调了在临床和生物学中进行来源感知分层的重要性。
查看英文原文 English abstract
Introduction: Pancreatic ductal adenocarcinoma (PDAC) arises from distinct precursor lesions, mainly pancreatic intraepithelial neoplasias (PanINs) and intraductal papillary mucinous neoplasms (IPMNs), which differ in genetics, differentiation ecosystem, and clinical behavior. PanIN-derived PDAC typically demonstrate more molecular and spatial heterogeneity, with pronounced classical-basal divergence. IPMN-derived adenocarcinomas display different histologic types: intestinal-type lesions often develop colloid carcinoma, where adenocarcinomas arising from pancreatobiliary(PB)-type IPMN resemble conventional PanIN-derived PDAC. Defining how precursor origin shapes malignant states, spatial microenvironment ecosystems are essential for PDAC classification.
Method: Single-cell spatial transcriptomics was performed by CosMx SMI (Bruker) in whole transcriptome and 6K-panel. Two different Tissue Microarrays (TMAs) cohorts were used (1.5-mm cores) include PanIN-origin PDAC (15 patients) and IPMN-origin PDAC (10 patients). Cell Segmentation performed by CellPose and strict quality control (QC) thresholding yielded 459,195 high-quality cells. Data was log-normalized and integrated with scVI using patient-level correction. Hierarchical annotation was performed by combining expert histopathological alignments with Leiden-based refinements. Downstream spatial analysis used Python based methods including Squidpy.
Results: Cross-cohort integration revealed marked origin-dependent divergence in the malignant spatial atlas. Malignant epithelium in PanIN-PDAC exhibited higher heterogeneity with more diverse and dispersed cell states. In contrast, the tumor cells in IPMN-derived PDAC presented obvious differentiation features for each carcinoma type. Intestinal-type IPMN PDAC developed unique malignant program that exhibiting typical goblet-like subtype, which was not observed in either other IPMN-type PDAC or PanIN-derived PDAC. However, the PB-type IPMN-PDAC showed substantial similarity with PanIN-PDAC, sharing multiple malignant programs, primarily including pEMT, progenitor cell-like and ADM-like subtypes. Furthermore, PanIN-PDAC retained specific tumor programs as exocrine-like, squamous, and inflammatory-association basal-like. Notably, although PB-type in IPMN PDAC and PanIN-PDAC share similarities in some tumor states, further analysis revealed significant differences in the spatial patterns and cell communication between tumor and microenvironments (TME). This suggests potentially different evolution of microenvironments.
Conclusion: Precursor origin fundamentally shapes PDAC malignant states and stromal-immune ecosystems. Together, this work establishes a spatial framework for understanding PDAC heterogeneity and highlights the importance of origin-aware stratification in clinic and biology.
利益披露 Disclosure
T. Zhang, None..
A. Legrini, None..
M. McGuigan, None..
S. B. Dreyer, None..
G. Latifi, None..
C. Kennedy Dietrich, None..
H. Morgan, None..
E. Verkolf, None..
V. Padoan, None..
Y. Doncheva, None..
J. Da Silva Filho, None..
M. Doukas, None..
B. G. Koerkamp, None..
J. Edwards, None..
N. Jamieson, None.