category
bioRxiv
date
Mar 27, 2026
slug
status
Published
summary
构建了覆盖128例患者的前列腺癌单细胞图谱,发现局部病变中肿瘤细胞存在基底样/俱乐部样状态转换,转移性病变中出现器官特异性基因模块激活(如骨转移的成骨信号、肝转移的红细胞样转化),提出神经内分泌前列腺癌(NEPC)的异质性由HES6等新型基因模块驱动,并开发了基于Transformer架构的PCformer模型实现细胞状态自动分类。
tags
单细胞测序
空间组学
type
Post

📄 原文题目

A single-cell and spatial atlas of prostate cancer reveals the combinatorial nature of gene modules underlying lineage plasticity and metastasis

🔗 原文链接

💡 AI 核心解读

构建了覆盖128例患者的前列腺癌单细胞图谱,发现局部病变中肿瘤细胞存在基底样/俱乐部样状态转换,转移性病变中出现器官特异性基因模块激活(如骨转移的成骨信号、肝转移的红细胞样转化),提出神经内分泌前列腺癌(NEPC)的异质性由HES6等新型基因模块驱动,并开发了基于Transformer架构的PCformer模型实现细胞状态自动分类。

📝 英文原版摘要

Prostate cancer encompasses a spectrum of disease states driven by complex cellular heterogeneity. To delineate the transcriptional programs underlying lineage plasticity and metastasis, we constructed a comprehensive single-cell atlas of 128 patients, spanning localized, castration-resistant, and metastatic disease. Lineage plasticity was prevalent in localized disease, with subsets of tumor cells adopting distinct basal-like and club-like states. Luminal-like cancer cells also displayed extensive lineage infidelity, defined not by a binary loss of identity but by the combinatorial erosion of luminal gene modules associated with higher grade and stage. In the metastatic setting, gene program association analysis (GPAS) identified a broad induction of cell-cycle gene modules across organ sites as well as an induction of organ-specific gene modules, including osteomimetic signaling in bone, neuro-migratory genes in brain, and erythroid-like transitions in liver. Neuroendocrine prostate cancers (NEPCs) were not monolithic but defined by combinations of NE-associated gene modules including a novel HES6 program. Notably, these modules were detected at intermediate levels in localized samples, suggesting molecular plasticity precedes histological transformation. We also developed a refined NE signature that could distinguish NEPC tumors more accurately than previously published signatures. Within the tumor microenvironment (TME), we observed an elevation of pro-inflammatory Th17 T-cells in African American patients and identified a rare Schwann cell population. Finally, we present PCformer, a transformer-based foundation model trained on >500,000 cells to automate cell-state classification. Together, this comprehensive atlas demonstrates the complex nature of gene modules un
derlying lineage infidelity and plasticity in cancer cells and highlights distinct immune and stromal populations within the tumor ecosystem.
m6A修饰位置对mRNA稳定性的影响与涡虫细胞身份相关开源、硬件无关的GPU加速可扩展纳米孔碱基识别:Slorado与Openfish
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