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Cell reports. Medicine. 2025 Jun 3:102188. doi: 10.1016/j.xcrm.2025.102188 Q111.72024

Cell states and neighborhoods in distinct clinical stages of primary and metastatic esophageal adenocarcinoma

原发性和转移性食管腺癌不同临床阶段的细胞状态及相邻细胞簇 翻译改进

Josephine Yates  1, Camille Mathey-Andrews  2, Jihye Park  3, Amanda Garza  3, Andréanne Gagné  3, Samantha Hoffman  4, Kevin Bi  3, Breanna Titchen  4, Connor Hennessey  5, Joshua Remland  6, Matthew Carnes  6, Erin Shannon  3, Sabrina Camp  3, Siddhi Balamurali  3, Shweta Kiran Cavale  3, Zhixin Li  3, Akhouri Kishore Raghawan  3, Agnieszka Kraft  7, Genevieve Boland  8, Andrew J Aguirre  9, Nilay S Sethi  10, Valentina Boeva  11, Eliezer M Van Allen  12

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作者单位

  • 1 Institute for Machine Learning, Department of Computer Science, ETH Zürich, Zurich, Switzerland; ETH AI Center, ETH Zurich, Zurich, Switzerland; Swiss Institute for Bioinformatics (SIB), Lausanne, Switzerland; Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA.
  • 2 Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA; Department of Surgery, Massachusetts General Hospital, Boston, MA, USA.
  • 3 Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA; Cancer Program, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
  • 4 Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA; Cancer Program, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Division of Medical Sciences, Harvard University, Boston, MA, USA.
  • 5 Penn Medicine, University of Pennsylvania, Philadelphia, PA, USA.
  • 6 Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA.
  • 7 Institute for Machine Learning, Department of Computer Science, ETH Zürich, Zurich, Switzerland; Swiss Institute for Bioinformatics (SIB), Lausanne, Switzerland.
  • 8 Department of Surgery, Division of Gastrointestinal and Surgical Oncology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
  • 9 Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA; Cancer Program, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Division of Medical Sciences, Harvard University, Boston, MA, USA; Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
  • 10 Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA; Cancer Program, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
  • 11 Institute for Machine Learning, Department of Computer Science, ETH Zürich, Zurich, Switzerland; ETH AI Center, ETH Zurich, Zurich, Switzerland; Swiss Institute for Bioinformatics (SIB), Lausanne, Switzerland; Cochin Institute, Inserm U1016, CNRS UMR 8104 Paris Descartes University UMR-S1016, Paris 75014, France. Electronic address: valentina.boeva@inf.ethz.ch.
  • 12 Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA; Cancer Program, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Division of Medical Sciences, Harvard University, Boston, MA, USA; Parker Institute for Cancer Immunotherapy, Dana-Farber Cancer Institute, Boston, MA, USA. Electronic address: eliezerm_vanallen@dfci.harvard.edu.

    • DOI: 10.1016/j.xcrm.2025.102188 PMID: 40499545

    摘要 中英对照阅读

    Esophageal adenocarcinoma (EAC) is a highly lethal cancer of the upper gastrointestinal tract with rising incidence in western populations. To decipher EAC disease progression and therapeutic response, we perform multiomic analyses of a cohort of primary and metastatic EAC tumors, incorporating single-nuclei transcriptomic and chromatin accessibility sequencing along with spatial profiling. We recover tumor microenvironmental features previously described to associate with therapy response. We subsequently identify five malignant cell programs, including undifferentiated, intermediate, differentiated, epithelial-to-mesenchymal transition, and cycling programs, which are associated with differential epigenetic plasticity and clinical outcomes, and for which we infer candidate transcription factor regulons. Furthermore, we reveal diverse spatial localizations of malignant cells expressing their associated transcriptional programs and predict their significant interactions with microenvironmental cell types. We validate our findings in three external single-cell RNA sequencing (RNA-seq) and three bulk RNA-seq studies. Altogether, our findings advance the understanding of EAC heterogeneity, disease progression, and therapeutic response.

    Keywords: bioinformatics; computational biology; epigenetics; esophageal adenocarcinoma; gastrointestinal cancer; oncology; single cell; spatial transcriptomics; transcriptomics.

    Keywords：cell states; clinical stages; esophageal adenocarcinoma

    食管腺癌（EAC）是上消化道的一种高度致命的癌症，在西方人群中发病率正在上升。为了揭示EAC疾病进展和治疗反应，我们对一组原发性和转移性EAC肿瘤进行了多组学分析，包括单细胞转录组测序、染色质可及性测序以及空间定位分析。我们恢复了先前描述与治疗反应相关的肿瘤微环境特征。随后，我们识别出五个恶性细胞程序，包括未分化、中间型、分化型、上皮-间充质转化和周期型程序，这些程序与不同的表观遗传学塑性和临床结局相关，并且我们推断出了候选转录因子调控网络。此外，我们揭示了表达其相应转录程序的恶性细胞在空间上的多样分布，并预测了它们与微环境细胞类型之间的重要相互作用。我们在三个外部单细胞RNA测序（RNA-seq）和三个批量RNA-seq研究中验证了我们的发现。总的来说，我们的发现推进了对EAC异质性、疾病进展和治疗反应的理解。

    关键词：生物信息学；计算生物学；表观遗传学；食管腺癌；胃肠道癌症；肿瘤学；单细胞；空间转录组学；转录组学。

    关键词：细胞状态; 临床分期; 食管腺癌

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    期刊名：Cell reports medicine

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    ISSN：2666-3791

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    IF/分区：11.7/Q1

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    Cell states and neighborhoods in distinct clinical stages of primary and metastatic esophageal adenocarcinoma