前列腺癌
细胞
谱系(遗传)
癌症研究
前列腺
癌症
组织微阵列
生物
基因
遗传学
作者
Samir Zaidi,Jooyoung Park,Joseph M. Chan,Martine P. Roudier,Jimmy L. Zhao,Anuradha Gopalan,Kristine M. Wadosky,Radhika A. Patel,Erolcan Sayar,Wouter R. Karthaus,D. Henry Kates,Ojasvi Chaudhary,Tianhao Xu,Ignas Masilionis,Linas Mažutis,Ronan Chaligné,Aleksandar Z. Obradovic,Irina Linkov,Afşar Barlas,Achim A. Jungbluth
标识
DOI:10.1073/pnas.2322203121
摘要
Targeting cell surface molecules using radioligand and antibody-based therapies has yielded considerable success across cancers. However, it remains unclear how the expression of putative lineage markers, particularly cell surface molecules, varies in the process of lineage plasticity, wherein tumor cells alter their identity and acquire new oncogenic properties. A notable example of lineage plasticity is the transformation of prostate adenocarcinoma (PRAD) to neuroendocrine prostate cancer (NEPC)—a growing resistance mechanism that results in the loss of responsiveness to androgen blockade and portends dismal patient survival. To understand how lineage markers vary across the evolution of lineage plasticity in prostate cancer, we applied single-cell analyses to 21 human prostate tumor biopsies and two genetically engineered mouse models, together with tissue microarray analysis on 131 tumor samples. Not only did we observe a higher degree of phenotypic heterogeneity in castrate-resistant PRAD and NEPC than previously anticipated but also found that the expression of molecules targeted therapeutically, namely PSMA , STEAP1 , STEAP2 , TROP2, CEACAM5 , and DLL3 , varied within a subset of gene-regulatory networks (GRNs). We also noted that NEPC and small cell lung cancer subtypes shared a set of GRNs, indicative of conserved biologic pathways that may be exploited therapeutically across tumor types. While this extreme level of transcriptional heterogeneity, particularly in cell surface marker expression, may mitigate the durability of clinical responses to current and future antigen-directed therapies, its delineation may yield signatures for patient selection in clinical trials, potentially across distinct cancer types.
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