Abstract
Objective
Tumour heterogeneity represents a major obstacle to accurate diagnosis and
treatment in gastric adenocarcinoma (GA). Here, we report a systematic transcriptional
atlas to delineate molecular and cellular heterogeneity in GA using single-cell RNA
sequencing (scRNA-seq).
Design
We performed unbiased transcriptome-wide scRNA-seq analysis on 27 677 cells from
9 tumour and 3 non-tumour samples. Analysis results were validated using large-scale
histological assays and bulk transcriptomic datasets.
Results
Our integrative analysis of tumour cells identified five cell subgroups with
distinct expression profiles. A panel of differentiation-related genes reveals a high
diversity of differentiation degrees within and between tumours. Low differentiation
degrees can predict poor prognosis in GA. Among them, three subgroups exhibited
different differentiation grade which corresponded well to histopathological features
of Lauren’s subtypes. Interestingly, the other two subgroups displayed unique
transcriptome features. One subgroup expressing chief-cell markers (eg,
LIPF and PGC) and
RNF43 with Wnt/β-catenin signalling pathway activated is
consistent with the previously described entity fundic gland-type GA (chief
cell-predominant, GA-FG-CCP). We further confirmed the presence of GA-FG-CCP in two
public bulk datasets using transcriptomic profiles and histological images. The other
subgroup specifically expressed immune-related signature genes (eg,
LY6K and major histocompatibility complex class II) with
the infection of Epstein-Barr virus. In addition, we also analysed non-malignant
epithelium and provided molecular evidences for potential transition from gastric
chief cells into
MUC6+TFF2+
spasmolytic polypeptide expressing metaplasia.
Conclusion
Altogether, our study offers valuable resource for deciphering gastric tumour
heterogeneity, which will provide assistance for precision diagnosis and
prognosis.
Funder
Outstanding Youth
Training Fund of the Chinese PLA General Hospital
National Key R&D
Program of China
Natural Science Foundation
of Beijing Municipality
Cited by
186 articles.
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