Godfrey Trevor M, Shanneik Yasmin, Zhang Wanqiu, Tran Thao, Verbeeck Nico, Patterson Nathan H, Jackobs Faith E, Nagi Chandandeep, Ramineni Maheshwari, Eberlin Livia S
Department of Surgery, Baylor College of Medicine, Houston, TX, 77030, USA.
Aspect Analytics NV, Genk, Belgium.
Angew Chem Int Ed Engl. 2025 Jun 10;64(24):e202502028. doi: 10.1002/anie.202502028. Epub 2025 Apr 24.
Innovations in spatial omics technologies applied to human tissues have led to breakthrough discoveries in various diseases, including cancer. Two of these approaches-spatial transcriptomics and spatial metabolomics-have blossomed independently, fueled by technologies such as spatial transcriptomics (ST) and mass spectrometry imaging (MSI). Although powerful, these technologies only offer insights into the spatial distributions of restricted classes of molecules and have not yet been integrated to provide more holistic insights into biological questions. These techniques can be performed on adjacent serial sections from the same sample, but section-to-section variability can convolute data integration. We present a novel method combining desorption electrospray ionization mass spectrometry imaging (DESI-MSI) spatial metabolomics and Visium spatial transcriptomics on the same tissue sections. We show that RNA quality is maintained after performing DESI-MSI on a tissue under ambient conditions and that ST data is unperturbed following DESI-MSI. We demonstrate this workflow on human breast and lung cancer tissues and identify novel correlations between metabolites and mRNA transcripts in cancer-specific tissue regions.
应用于人体组织的空间组学技术创新已在包括癌症在内的各种疾病中带来了突破性发现。其中两种方法——空间转录组学和空间代谢组学——在空间转录组学（ST）和质谱成像（MSI）等技术的推动下各自蓬勃发展。尽管这些技术很强大，但它们仅能提供对有限类分子空间分布的见解，尚未整合起来以提供对生物学问题更全面的见解。这些技术可以在来自同一样本的相邻连续切片上进行，但切片间的变异性会使数据整合变得复杂。我们提出了一种在同一组织切片上结合解吸电喷雾电离质谱成像（DESI-MSI）空间代谢组学和Visium空间转录组学的新方法。我们表明，在环境条件下对组织进行DESI-MSI后，RNA质量得以维持，并且DESI-MSI后ST数据不受干扰。我们在人乳腺癌和肺癌组织上展示了这一工作流程，并确定了癌症特异性组织区域中代谢物与mRNA转录本之间的新关联。
