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Spatial transcriptomics reveals distinct and conserved tumor core and edge architectures that predict survival and targeted therapy response

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NIAID Data Ecosystem2026-05-01 收录
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https://www.ncbi.nlm.nih.gov/sra/SRP386486
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We performed the first integrative single-cell and spatial transcriptomic analysis on HPV-negative oral squamous cell carcinoma (OSCC) to comprehensively characterize tumor core (TC) and leading edge (LE) transcriptional architectures. We show that the TC and LE are characterized by unique transcriptional profiles, cellular compositions, and ligand-receptor interactions. We demonstrate that LE regions are conserved across multiple cancers while TC states are more tissue specific, highlighting the existence of common mechanisms underlying tumor progression and invasion. Additionally, we found our LE gene signature is associated with worse clinical outcomes while the TC gene signature is associated with improved prognosis across multiple cancer types. Finally, using an in silico modeling approach, we describe spatially-regulated patterns of cell development in OSCC that are predictably associated with drug response. Our work provides pan-cancer insights into TC and LE biology and a platform for data exploration (http://www.pboselab.ca/spatial_OSCC/) that can be foundational for developing novel targeted therapies. Overall design: Overall Design Fresh-frozen OSCC tissue was obtained from the Alberta Cancer Research Biobank under the approval of the Health Research Ethics Board of Alberta – Cancer Committee (reference number: HREBA.CC-16-0644). The BioBank OSCC tumor samples were collected at the time of the surgery, embedded in optimal cutting temperature (OCT) compound, and stored frozen at -80C until retrieval for the study. The study samples were sectioned in a cryostat at 10 um, stained with hematoxylin and eosin (H&E) and used for ST. Tissue optimization was performed to determine the optimal permeabilization time for OSCC tissue for the downstream gene expression protocol. Spatial transcriptomics was performed on OSCC cryosections using the Visium platform according to the manufacturer's protocol (10x Genomics, Pleasanton, CA, USA). Briefly, OCT-embedded 10 micrometer-thick cryosections of OSCC samples were placed on the Visium spatial slide. Sections were enzymatically permeabilized for 24 min. cDNA was obtained from mRNA bound to capture oligos printed on the slide. cDNA quantification was performed using Agilent Bioanalyzer High Sensitivity Kit on an Agilent Bioanalyzer 2100 (Agilent Technologies, CA, USA). cDNA libraries were sequenced on an Illumina NovaSeq 6000 sequencer using the SP flowcell (200 cycles) at the Centre for Health Genomics and Informatics (CHGI, University of Calgary, Alberta, Canada). Sequencing reads were aligned using the 10s Genomics Space Ranger 1.3.1 pipeline to the standard GRCh38 reference genome. 12 samples passing alignment QC were aggregated together using the 10x Genomics Space Ranger aggr function to normalize for read depth between samples. Aggregated samples (n = 12) recovered a total number of 24,876 spots containing tissue sequenced to 43,648 post-normalization mean reads per spot. Extract protocol Fresh-frozen OSCC tissue was obtained from the Alberta Cancer Research Biobank under the approval of the Health Research Ethics Board of Alberta – Cancer Committee (reference number: HREBA.CC-16-0644). The BioBank OSCC tumor samples were collected at the time of the surgery, embedded in optimal cutting temperature (OCT) compound, and stored frozen at -80C until retrieval for the study. The study samples were sectioned in a cryostat at 10 um, stained with hematoxylin and eosin (H&E) and used for ST.
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2023-09-15
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