Spatial transcriptomics reveals prognosis‐associated cellular heterogeneity in the papillary thyroid carcinoma microenvironment

Пространственная транскриптомика выявляет связанную с прогнозом клеточную гетерогенность микроокружения папиллярной карциномы щитовидной железы
Kai Yan, Qingzhi Liu, Rongrong Huang, Yihua Jiang, Zhen‐Hua Bian, Si‐Jin Li, Liang Li, Fei Shen, Koichi Tsuneyama, Qingling Zhang, Zhe‐Xiong Lian, Haixia Guan, Bo Xu
2024-03-01

cellular heterogeneityligand-receptor interactionspapillary thyroid carcinomarelapse-free survivalspatial transcriptomics
BACKGROUND: Papillary thyroid carcinoma (PTC) is the most common malignant endocrine tumour, and its incidence and prevalence are increasing considerably. Cellular heterogeneity in the tumour microenvironment is important for PTC prognosis. Spatial transcriptomics is a powerful technique for cellular heterogeneity study. METHODS: In conjunction with a clinical pathologist identification method, spatial transcriptomics was employed to characterise the spatial location and RNA profiles of PTC-associated cells within the tissue sections. The spatial RNA-clinical signature genes for each cell type were extracted and applied to outlining the distribution regions of specific cells on the entire section. The cellular heterogeneity of each cell type was further revealed by ContourPlot analysis, monocle analysis, trajectory analysis, ligand-receptor analysis and Gene Ontology enrichment analysis. RESULTS: The spatial distribution region of tumour cells, typical and atypical follicular cells (FCs and AFCs) and immune cells were accurately and comprehensively identified in all five PTC tissue sections. AFCs were identified as a transitional state between FCs and tumour cells, exhibiting a higher resemblance to the latter. Three tumour foci were shared among all patients out of the 13 observed. Notably, tumour foci No. 2 displayed elevated expression levels of genes associated with lower relapse-free survival in PTC patients. We discovered key ligand-receptor interactions, including LAMB3-ITGA2, FN1-ITGA3 and FN1-SDC4, involved in the transition of PTC cells from FCs to AFCs and eventually to tumour cells. High expression of these patterns correlated with reduced relapse-free survival. In the tumour immune microenvironment, reduced interaction between myeloid-derived TGFB1 and TGFBR1 in tumour focus No. 2 contributed to tumourigenesis and increased heterogeneity. The spatial RNA-clinical analysis method developed here revealed prognosis-associated cellular heterogeneity in the PTC microenvironment. CONCLUSIONS: The occurrence of tumour foci No. 2 and three enhanced ligand-receptor interactions in the AFC area/tumour foci reduced the relapse-free survival of PTC patients, potentially leading to improved prognostic strategies and targeted therapies for PTC patients.
1
Atypical follicular cells represented a transitional state between typical follicular cells and tumour cells, with greater molecular similarity to tumour cells.
2
LAMB3-ITGA2, FN1-ITGA3, and FN1-SDC4 ligand-receptor interactions were implicated in follicular-to-atypical-to-tumour cell transition and correlated with reduced relapse-free survival.
3
Reduced myeloid-derived TGFB1-TGFBR1 interaction in tumour focus No. 2 was associated with tumourigenesis and increased cellular heterogeneity.
4
Spatial transcriptomics combined with pathological identification accurately mapped tumour, follicular, atypical follicular, and immune-cell regions across five PTC sections.
5
Three tumour foci were shared across patients; tumour focus No. 2 showed elevated expression of genes associated with shorter relapse-free survival.

Papillary thyroid carcinoma tissue microenvironment, including tumour cells, follicular cells, atypical follicular cells, and immune cells

Prognosis-associated spatial cellular heterogeneity, cell-state transitions, and ligand–receptor interactions within the papillary thyroid carcinoma microenvironment

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2024-03-01
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Kai Yan
Qingzhi Liu
Rongrong Huang
Yihua Jiang
Zhen‐Hua Bian
Si‐Jin Li
Liang Li
Fei Shen
Koichi Tsuneyama
Qingling Zhang
Zhe‐Xiong Lian
Haixia Guan
Bo Xu
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