Skip to content

Correlation between Gastric Cancer Transcriptome and Histotype Demonstrates Prognostic Potential

The study provides comprehensive insights into this correlation, shedding light on the histopathological effects of the disease.

Gastric cancer is the fifth most common cancer worldwide and remains the third most common in cancer-related deaths, despite a declining incidence rate in recent years. A lack of screening means that gastric cancer patients are diagnosed late and surgery remains the only potential cure.

Histopathology categorises gastric cancer into two distinct types: intestinal, which is well-differentiated, and diffuse, which is undifferentiated. The diffuse tumours are the more aggressive, but the molecular mechanisms that separate the two are poorly understood. There are few biomarkers available to predict therapeutic efficacy, although these include HER2 for trastuzumab and PD‑L1 for pembrolizumab.

In this study, the authors used RNA sequencing (RNA‑Seq) to identify genes differentially expressed in healthy samples compared to the two histotypes of gastric cancer.

  • 24 gastric cancer patients undergoing resection were divided into two groups according to Lauren’s classification: an “intestinal group” and a “diffuse group”. Mean age, gender and cancer stage in the two groups were similar and all patients underwent either a total or subtotal gastrectomy plus D1, D2 or D3 lymphadenectomy.
  • Transcriptomic analysis was conducted using RNA‑Seq. Principal component analysis (PCA) demonstrated clustering of healthy samples, whereas tumour samples clustered separately. The two types of tumour samples had some overlap but did show some separate clustering.
  • Differentially expressed transcripts partially overlapped between the two types of cancers with 885 transcripts differentially expressed in both types compared to healthy mucosa. 407 transcripts were differentially expressed in only diffuse gastric cancer compared to normal and 772 only in intestinal cancer compared to normal.
  • In genes differentially expressed in both histotypes, many were associated with the cell cycle, (mitosis, cell division, DNA replication), extracellular matrix, regulation of inflammation (IL‑18, chemokines, cytokines, IL6 signalling pathways) and cancer development and progression (PI3K‑Akt‑mTOR, VEGFA‑VEGFR2, MAPK, Ras, EGF/EGFR signalling pathways).
  • Amongst the upregulated genes were those involved in the cell cycle, such as CDK1, CDC25A, CDC25B, CCNB1 and CCNB2. Genes involved in Epithelial to Mesenchymal Transition (EMT) regulation were also found including TMPRSS4, NF‑Kβ/MMP9 signalling and Claudins (CLDN1, CLDN3, CLDN4, CLDN7), ITGA2, LAMC2 and WNT5A. Matrix metalloproteases MMP1, MMP3, MMP10, MMP12 were also overexpressed in tumours compared to normal.
  • A cluster of genes was identified that are involved in chemokine and cytokine signalling. Upregulated genes in this cluster include CCL3, CCL15, CCL20 and genes in the CXCLs family CXC1, CXCL2, CXCL5 and CXCL16, as well as several cytokines including IL‑1β, IL‑11 and IL‑8.
  • Transcriptomic analysis of the only diffuse subset of genes highlighted genes involved in lipid metabolism and transport, metabolic pathways and transcription. Upregulated genes include HNF4A, IDH1, APOC1, APOE and FASN, many of which have already been implicated in gastric cancers. Likewise, a number of downregulated genes have been associated with gastric cancer, such as VLDLR, CYP27A1 and CCL2.
  • In the intestinal gastric cancer samples, there was a strong association with an inflammatory response because of its association with H. pylori infection. Pathway analysis demonstrated genes were associated with chemotaxis, inflammation, and innate and adaptive immunity.
  • Differentially expressed genes include CCL4, FN1, PTGS2, CCL19, NR0B2, CXCR2, CCL19, CXCL14, TIMP1, SERPINE1, S100A9, many of which are known markers of gastric cancers. The most differentially expressed genes were associated with the focal adhesion‑PI3 kinase‑AKT‑mTOR signalling pathway.
  • Increasing the stringency of differential significance identified 9 genes; CARD14, FPR2, EFNA2, CXCR2, CXCR1, AQP9 and TRIP13, which were overexpressed in intestinal gastric cancer compared to diffuse. KLK11 and GHRL expression were decreased compared to diffuse.
  • AQP9 expression in the intestinal group correlated with patient survival with high expression associated with significantly worse prognosis compared to low expressers. High expression of CARD14 and CXCR2 in the diffuse group was associated with worse prognosis.

In this study, the authors addressed the lack of molecular mechanistic data for the two main types of gastric cancer, diffuse and intestinal (classified according to Lauren’s histological scoring). They used RNA sequencing to identify transcriptomic differences between the two types of cancer and healthy controls. Clear differences were observed in the gene set, with enrichment analysis identifying a strong inflammatory component in the intestinal gastric cancer whereas the diffuse cancer was enriched in methylation and cell division and adhesion pathways. Nine genes (FPR2, CARD14, CXCR2, EFNA2, CXCR1, AQP9, TRIP13, GHRL and KLK11) were identified that could be used as biomarkers for each type of cancer. Expression of two of these genes, AQP9 and CXCR2, is significantly associated with patient survival and could be targeted for therapeutic intervention in gastric cancers.



Epistem is a GCLP-accredited laboratory specialising in providing biomarkers, target discovery and personalised medicine information. We offer microarray, qPCR and NGS services for gene expression, whole genome and epigenetic analysis in all species.

Your ideal partner for cancer drug discovery is Epistem, using our range of in vitro and in vivo cancer models. We have orthotopic, in-life imaging oncology models for a number of cancer types, with more in development. We also offer in vitro cytotoxicity testing in cell lines, cancer stem cell assays, and spheroids that can be used for drug development.

Epistem provides a unique plucked hair biomarker platform for targeting intracellular signalling pathways in inflammation, oncology, fibrosis and other therapeutic areas. Plucked hair provides a minimally invasive surrogate tissue to assess epithelial tissue drug-induced changes. Effects on mRNA and protein expression levels can be analysed. Epistem is able to discover and validate ideal biomarkers for use in clinical settings using a range of preclinical models, which include assessing human hairy skin or plucked scalp hair ex vivo in the presence of compounds at different concentrations.