Convergent dysbiosis of gastric mucosa and fluid microbiome during stomach carcinogenesisHe, Cong; Peng, Chao; Shu, Xu; Wang, Huan; Zhu, Zhenhua; Ouyang, Yaobin; Yang, Xiaoyu; Xie, Chuan; Hu, Yi; Li, Nianshuang; Ge, Zhongming; Zhu, Yin; Lu, Nonghua
doi: 10.1007/s10120-022-01302-zpmid: 35661945
BackgroundA complex microbiota in the gastric mucosa (GM) has been unveiled recently and its dysbiosis is identified to be associated with gastric cancer (GC). However, the microbial composition in gastric fluid (GF) and its correlation with GM during gastric carcinogenesis are unclear.MethodsWe obtained GM and GF samples from 180 patients, including 61 superficial gastritis (SG), 55 intestinal metaplasia (IM) and 64 GC and performed 16S rRNA gene sequencing analysis. The concentration of gastric acid and metabolite nitrite has been measured.ResultsOverall, the composition of microbiome in GM was distinct from GF with less diversity, and both were influenced by H. pylori infection. The structure of microbiota changed differentially in GM and GF across histological stages of GC, accompanied with decreased gastric acid and increased carcinogenic nitrite. The classifiers of GC based on microbial markers were identified in both GM and GF, including Lactobacillus, Veillonella, Gemella, and were further validated in an independent cohort with good performance. Interestingly, paired comparison between GM and GF showed that their compositional distinction remarkably dwindled from SG to GC, with some GF-enriched bacteria significantly increased in GM. Moreover, stronger interaction network between microbes of GM and GF was observed in GC compared to SG.ConclusionOur results, for the first time, revealed a comprehensive profile of both GM and GF microbiomes during the development of GC. The convergent microbial characteristics between GM and GF in GC suggest that the colonization of carcinogenic microbes in GM might derive from GF.
Lipocalin-2 negatively regulates epithelial–mesenchymal transition through matrix metalloprotease-2 downregulation in gastric cancerNishimura, Sadaaki; Yamamoto, Yurie; Sugimoto, Atsushi; Kushiyama, Shuhei; Togano, Shingo; Kuroda, Kenji; Okuno, Tomohisa; Kasashima, Hiroaki; Ohira, Masaichi; Maeda, Kiyoshi; Yashiro, Masakazu
doi: 10.1007/s10120-022-01305-wpmid: 35705840
BackgroundAlthough the role of Lipocalin-2 (LCN2) in cancer development has been focused on recent studies, the molecular mechanisms and clinical relevance of LCN2 in gastric cancer (GC) still remain unclear.MethodsTranscriptome analysis of GC samples from public human data was performed according to Lauren’s classification and molecular classification. In vitro, Western blotting, RT-PCR, wound healing assay and invasion assay were performed to reveal the function and mechanisms of LCN2 in cell proliferation, migration and invasion using LCN2 knockdown cells. Gene set enrichment analysis (GSEA) of GC samples from public human data was analyzed according to LCN2 expression. The clinical significance of LCN2 expression was investigated in GC patients from public data and our hospital.ResultsLCN2 was downregulated in diffuse-type GC, as well as in Epithelial–Mesenchymal Transition (EMT) type GC. LCN2 downregulation significantly promoted proliferation, invasion and migration of GC cells. The molecular mechanisms of LCN2 downregulation contribute to Matrix Metalloproteinases-2 (MMP2) stimulation which enhances EMT signaling in GC cells. GSEA revealed that LCN2 downregulation in human samples was involved in EMT signaling. Low LCN2 protein and mRNA levels were significantly associated with poor prognosis in patients with GC. LCN2 mRNA level was an independent prognostic factor for overall survival in GC patients.ConclusionsLCN2 has a critical role in EMT signaling via MMP2 activity during GC progression. Thus, LCN2 might be a promising therapeutic target to revert EMT signaling in GC patients with poor outcomes.
The combination of gene hyperamplification and PD-L1 expression as a biomarker for the clinical benefit of tislelizumab in gastric/gastroesophageal junction adenocarcinomaLu, Zhihao; Yang, Silu; Luo, Xuerui; Shi, Yang; Lee, Jong-Seok; Deva, Sanjeev; Liu, Tianshu; Chao, Yee; Zhang, Yun; Huang, Ruiqi; Xu, Yaling; Shen, Zhirong; Shen, Lin
doi: 10.1007/s10120-022-01308-7pmid: 35778636
BackgroundIn solid tumor Phase 1/2 trials (NCT02407990; NCT04068519), tislelizumab demonstrated clinical benefit, including in advanced gastroesophageal adenocarcinoma (GEA). However, the majority of patients with GEA did not respond, highlighting the need to understand mechanisms of resistance and identify predictive biomarkers for response.MethodsAll tislelizumab-treated patients with GEA from the Phase 1/2 trials were included (N = 105). Programmed death-ligand 1 (PD-L1) expression (Tumor Area Positivity [TAP] ≥ 5%), interferon gamma (IFNγ)-related gene signature, gene expression profile, tumor mutational burden (TMB), and gene hyperamplification (HA) were analyzed for correlation with tislelizumab.ResultsA moderate association was observed between PD-L1 TAP ≥ 5%, IFNγ gene signature, TMB-high and efficacy. A potential correlation between hyperamplification (HA +) and worse outcomes with programmed cell death protein 1 (PD-1) inhibition was identified. Hyperamplified genes were mainly enriched in cancer progression pathways, including cell cycle and RTK-RAS-PI3K pathways. Joint PD-L1 TAP ≥ 5% and lack of hyperamplification showed the most favorable benefit with an objective response rate of 29.4%, and median progression-free survival and overall survival of 4.1 and 14.7 months, respectively. Tumors with TAP ≥ 5% and HA − had inflamed immune signatures with increased immune cell infiltration, enhanced anti-tumor cytotoxic activity and antigen presentation signatures. Findings were validated in two independent gastric and gastrointestinal cancer cohorts treated with immune checkpoint inhibitors.ConclusionsIn GEA, PD-L1 positivity, IFNγ-related gene signature and TMB-high status were positively associated with tislelizumab clinical benefit, whereas HA was associated with worse clinical outcomes. Combining PD-L1 positivity and HA − may help identify patients more likely to benefit from PD-1 blockade.