Metastasis occurs frequently after resection of pancreatic cancer (PaC). In this study, we hypothesized that multi-parametric analysis of pre-metastatic liver biopsies would classify patients according to their metastatic risk, timing and organ site. Liver biopsies obtained during pancreatectomy from 49 patients with localized PaC and 19 control patients with non-cancerous pancreatic lesions were analyzed, combining metabolomic, tissue and single-cell transcriptomics and multiplex imaging approaches. Patients were followed prospectively (median 3 years) and classified into four recurrence groups; early (<6 months after resection) or late (>6 months after resection) liver metastasis (LiM); extrahepatic metastasis (EHM); and disease-free survivors (no evidence of disease (NED)). Overall, PaC livers exhibited signs of augmented inflammation compared to controls. Enrichment of neutrophil extracellular traps (NETs), Ki-67 upregulation and decreased liver creatine significantly distinguished those with future metastasis from NED. Patients with future LiM were characterized by scant T cell lobular infiltration, less steatosis and higher levels of citrullinated H3 compared to patients who developed EHM, who had overexpression of interferon target genes (MX1 and NR1D1) and an increase of CD11B⁺ natural killer (NK) cells. Upregulation of sortilin-1 and prominent NETs, together with the lack of T cells and a reduction in CD11B⁺ NK cells, differentiated patients with early-onset LiM from those with late-onset LiM. Liver profiles of NED closely resembled those of controls. Using the above parameters, a machine-learning-based model was developed that successfully predicted the metastatic outcome at the time of surgery with 78% accuracy. Therefore, multi-parametric profiling of liver biopsies at the time of PaC diagnosis may determine metastatic risk and organotropism and guide clinical stratification for optimal treatment selection.

胰腺癌（PaC）切除后经常发生转移。在这项研究中，我们假设转移前肝活检的多参数分析将根据患者的转移风险、时间和器官部位对患者进行分类。结合代谢组学、组织和单细胞转录组学以及多重成像方法，对 49 名局部 PaC 患者和 19 名非癌性胰腺病变对照患者在胰腺切除术中获得的肝活检进行了分析。对患者进行前瞻性随访（中位 3 年）并分为四个复发组；早期（切除后<6个月）或晚期（切除后>6个月）肝转移（LiM）；肝外转移（EHM）；无病幸存者（无疾病证据 (NED)）。总体而言，与对照组相比，PaC 肝脏表现出炎症加剧的迹象。中性粒细胞胞外陷阱 (NET) 的富集、Ki-67 上调和肝肌酸下降显着区分了未来发生 NED 转移的患者。与发生 EHM 的患者相比，未来发生 LiM 的患者的特点是 T 细胞小叶浸润较少、脂肪变性较少、瓜氨酸 H3 水平较高，而 EHM 患者的干扰素靶基因（MX1 和 NR1D1）过度表达且 CD11B 增加 ⁺ NK 细胞的减少，将早发 LiM 患者与晚发 LiM 患者区分开来。 NED 的肝脏特征与对照组非常相似。使用上述参数，开发了一个基于机器学习的模型，成功预测手术时的转移结果，准确率达 78%。 因此，在 PaC 诊断时对肝活检进行多参数分析可以确定转移风险和器官趋向性，并指导临床分层以实现最佳治疗选择。