Back

Multi-omics Identification and Route-Specific Characterization of Metastasis-specific EMT Genes and Their Microenvironmental Interactions

Choi, Y. Y.; Kim, K. T.; Lee, J. E.; Cheong, J.-H.; Cho, I.

2023-10-17 genomics
10.1101/2023.10.15.562367 bioRxiv
Show abstract

BackgroundGastric cancer (GC) constitute a significant cause of cancer-related mortality worldwide, with metastatic patterns including hematogenous, peritoneal, and ovarian routes. Although GC gene expression patterns have been extensively researched, the metastasis-specific gene expression landscape remains largely unexplored. MethodsWe undertook a whole transcriptome sequencing analysis of 66 paired primary and metastatic (hematogenous, peritoneal, or ovarian) GC tumors from 14 patients. Public databases including The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) was used for validation. Single-cell RNA sequencing (scRNA-seq) of four ascites from serosa positive GC patients and five primary tumors by layer (superficial and deep) were analyzed. ResultsThrough differential expression analysis between paired primary and metastatic tumors by routes identified 122 unique metastasis-specific epithelial-mesenchymal transition (msEMT) genes. These genes demonstrated varying expression patterns depending on the metastatic route, suggesting route-specific molecular mechanisms in GC metastasis. High expression of msEMT genes in primary tumors was associated with more frequent CDH1 mutations, the genomically stable subtype, and poor prognosis in TCGA GC cohort. This association was further corroborated by poor prognosis and high predictive performance for peritoneal/ovarian recurrence in two independent cohorts (GSE66229; n=300, GSE84437; n=433). scRNA-seq analysis of five primary tumors (GSE167297) and four independent ascites samples from GC patients revealed that msEMT genes were predominantly expressed in diverse fibroblast sub-populations, rather than cancer cells. ConclusionsThis study illuminates the route-specific mechanisms and underlines the significance of msEMT genes and cancer-associated fibroblasts in peritoneal metastasis of GC.

Matching journals

The top 4 journals account for 50% of the predicted probability mass.

1
British Journal of Cancer
42 papers in training set
Top 0.1%
22.9%
2
Annals of Oncology
13 papers in training set
Top 0.1%
14.9%
3
International Journal of Cancer
42 papers in training set
Top 0.1%
10.3%
4
Scientific Reports
3102 papers in training set
Top 23%
4.9%
50% of probability mass above
5
Gastroenterology
40 papers in training set
Top 0.5%
3.6%
6
Cancer Medicine
24 papers in training set
Top 0.5%
2.6%
7
Cancers
200 papers in training set
Top 2%
2.1%
8
JNCI: Journal of the National Cancer Institute
16 papers in training set
Top 0.2%
2.1%
9
BMC Cancer
52 papers in training set
Top 1.0%
2.1%
10
Nature Communications
4913 papers in training set
Top 49%
1.8%
11
eLife
5422 papers in training set
Top 39%
1.8%
12
Journal of Experimental & Clinical Cancer Research
25 papers in training set
Top 0.1%
1.7%
13
Cancer Research
116 papers in training set
Top 2%
1.7%
14
PLOS ONE
4510 papers in training set
Top 53%
1.7%
15
Clinical Cancer Research
58 papers in training set
Top 1%
1.5%
16
Molecular Oncology
50 papers in training set
Top 0.6%
1.2%
17
iScience
1063 papers in training set
Top 24%
1.0%
18
Frontiers in Immunology
586 papers in training set
Top 6%
1.0%
19
Cellular and Molecular Gastroenterology and Hepatology
41 papers in training set
Top 0.5%
0.9%
20
Cell Death Discovery
51 papers in training set
Top 1%
0.9%
21
Cell Reports
1338 papers in training set
Top 31%
0.8%
22
Computational and Structural Biotechnology Journal
216 papers in training set
Top 8%
0.8%
23
Journal of Medical Genetics
28 papers in training set
Top 0.5%
0.8%
24
Genome Medicine
154 papers in training set
Top 8%
0.8%
25
Modern Pathology
21 papers in training set
Top 0.5%
0.7%
26
Genomics
60 papers in training set
Top 3%
0.7%
27
PeerJ
261 papers in training set
Top 17%
0.7%
28
Cell
370 papers in training set
Top 18%
0.7%