Introduction
Gastric cancer (GC) is the third most common cancer globally and the third leading cause of cancer death [
1]. China is a high-incidence area of GC [
2]. GC can be divided into proximal GC, middle GC, and distal GC [
3]. It is generally believed that proximal GC exhibits different clinical and biological behaviors compared with middle and distal GC. A study in Portugal indicated that proximal and distal gastric cancers are significantly different in terms of patient survival, tumor size, venous invasion, nodal status, and overall stage [
4]. Moreover, the prognosis for proximal GC is significantly worse than distal GC [
3].
Previous studies have also investigated the molecular differences between proximal and distal GCs. Whole-genome sequencing analysis of gastroesophageal junction (GEJ) carcinoma and distal GC by previous researchers showed no significant difference between the mutations in the two cancers and that the expression rates of PD-L1 in distal GC and GEJ cancer were 58.3% and 66.7%, respectively [
5]. Moreover, the expression of the adenomatous polyposis coli gene, β-catenin, and E-cadherin was not significantly different between proximal and distal GCs [
6]. An analysis conducted by Zhao et al. based on the SEER and TCGA databases revealed that the prognosis of proximal GC was worse than distal GC. Among the 280 differential genes, 90 were up-regulated in distal GC, while 190 were up-regulated in proximal GC. Pathway analysis showed that the activity of serine protease, ion channel (Na + /Cl-), and cytoskeleton could be related to the poor prognosis of proximal GC [
7]. Furthermore, lower blood glucose levels were significantly associated with an increased risk of distal GC [
8]. The overexpression of HER2 was significantly higher in Chinese patients with proximal GC than those with distal GC [
9].
GC is a multifactorial disease, and alterations in the tumor microenvironment are necessitated for GC initiation, progression, and metastasis [
10,
11]. As part of the tumor microenvironment, gastric microbiota has attracted increasing attention as it can impact cancer growth and spread in several ways. However, gastric microbiota has been relatively understudied compared to gut microbiota. Although the human stomach is thought to be exclusively inhabited by
Helicobacter pylori (Hp) and viewed as an inhospitable environment for microbiota, attributable to its acidic conditions and other antimicrobial factors, more gastric microbiota has been identified with the development of sequencing technology; studies have demonstrated that gastric bacteria mainly include
Proteus, Firmicutes, Bacteroidetes, Actinomycetes, and
Clostridium [
12]. Currently, it is unclear whether there is a correlation between the diversity of the gastric microbiota and the progression from healthy gastric mucosa to gastric cancer. Some studies found GC microbiota exhibit decreased microbial diversity, decreased abundance of Hp, and enrichment with other bacteria [
13,
14]. However, there have also been studies suggesting that gastric cancer is associated with increased diversity and richness of the microbiota [
15]. There were also research results indicated there was no significant difference in microbial abundance between gastric cancer and control samples [
16].
The metabolome of GC has been studied as well; Pan et al. discovered that TG (54:2), G3p, α- aminobutyric acid, α-CEHC, dodecanol, glutamylalanine, 3-methylalanine, sulfite, CL (63:4), PE NME (40:5), TG (53:4), retinol, 3-hydroxysterol, tetradecanoic acid, Mg (21:0 / 0:0 / 0:0), tridecanoic acid, myristic acid glycine, and octacarbonate were potential biomarkers of abdominal metastasis from GC[
17]. In another instance, Lee et al. studied the correlation between bile acid metabolism and GC [
18]. A study comparing urine metabolomics of patients with GC and healthy controls found significant differences in urine alanine, citric acid, creatine, creatinine, glycerol, hippuric acid, phenylalanine, taurine, and 3-hydroxybutyric acid between the two groups [
19]. In general, metabolic changes in blood, urine, gastric juice, and tissue in patients with GC have been evaluated, and changes in the metabolic spectrum have also been validated to be related to the occurrence and development of GC [
20].
The prognostic differences and molecular biological characteristics of proximal and distal GCs have been explored for decades; the microbiome and metabolome of GC have also been studied [
21]. However, the microbial composition and metabolic differences between proximal and distal GCs have not been fully studied and discussed. This study aimed to explore the metabolic differences between microbial-related proximal and distal gastric cancer through 16S rRNA amplicon sequencing and non-targeted metabolome analysis and explore the causes and development of proximal and distal gastric cancer.
Discussion
To the best of our knowledge, this is the first study to explore the differences in microbial diversity between proximal and distal GCs. Herein, the diversity and richness of the gastric microbiota were not significantly different between Proximal T and Distal T. At the phylum level,
Campilobacterota was significantly decreased in Proximal T and Distal T.
Bacteroidota,
Firmicutes,
Actinobacteriota, and
Desulfobacterota were increased in Distal T and Proximal T.
Acidobacteriota,
Myxococcota and
Cyanobacteria were increased in Proximal T.
Proteobacteria,
Fusobacteriota,
Spirochaetota,
Patescibacteria, and
Bdellovibrionota were significantly increased in Distal T. At the genus level,
Helicobacter was decreased in Proximal T and Distal T. This result is consistent with the previous results of other researchers [
22].
Lactobacillus and
Muribaculaceae were both increased in Distal T and Proximal T. Sonveaux et al. reported that
Lactobacillus might generate metabolites that could be used as an energy source for tumor growth and angiogenesis [
23]. Zhang et al. proposed that since the abundance of
Muribaculaceae was increased in cholangiocarcinoma, it could be a promising biomarker for its diagnosis [
24]. However,
Prevotella,
Streptococcus,
Acinetobacter,
Faecalibacterium,
Enterobacter,
Methylobacterium-Methylorubrum, and
Alloprevotella were increased only in Distal T. In comparison,
Rikenellaceae_RC-_gut_group,
Methylophilus,
Bacteroides,
Morganella,
Romboutsia,
Parabacteroides, and
Desulfovibrio were only increased in Proximal T. When Distal T and Proximal T were compared, the abundance of
Methylobacterium-Methylorubrum was increased in Distal T, whereas that of
Rikenellaceae_RC9_gut_group was significantly increased in Proximal T at the genus level. Limited studies on
Methylobacterium-Methylorubrum suggested that it could survive in extreme environments and was related to drug resistance [
25,
26]. Previous studies have also evinced that
Rikenellaceae_RC9_gut_group is associated with inflammation [
27].
The metabolome analysis of Distal T and Distal N revealed 54 significant differential metabolites. However, the comparison between Proximal T and Proximal N revealed merely 37 metabolites with significant differences. KEGG analysis demonstrated that these different metabolites of distal gastric cancer and proximal gastric cancer were related to aminoacyl-tRNA biosynthesis, central carbon metabolism in cancer, neuroactive ligand-receptor interaction, histidine metabolism, biosynthesis of unsaturated fatty acids, protein digestion and absorption, ABC transporters, glutathione metabolism, apoptosis, FoxO signaling pathway, Huntington disease, long-term potentiation, spinocerebellar ataxia, nicotine addiction, GABAergic synapse, and alcoholism. The results are in line with the findings of previous studies. Gao et al. also determined that the aminoacyl tRNA biosynthesis pathway in GC tissues was significantly up-regulated compared with adjacent non-tumor tissues [
28]. The neuroactive live receptor interaction pathway is involved in the tumor microenvironment and cell-cell communication [
29]. The relative abundance of the differential metabolites of amino acids in tumor tissues was higher than in non-tumor tissues. A study by Tsai et al. unveiled the aberrant metabolism of multiple amino acids in gastric cancer [
30]. The relative abundance of the differential metabolites of amino acids in tumor tissues was higher than in non-tumor tissues. Since tumor cells use amino acids to produce energy and synthesize proteins and nucleosides, increasing the concentration of amino acids is essential for tumor cell proliferation.
Different metabolites in distal GC were also correlated with purine metabolism, D-glutamine and D-glutamate metabolism, sphingolipid signaling pathway, proximal tubule bicarbonate reclamation, Parkinson’s disease, taurine and hypotaurine metabolism, arginine biosynthesis, alanine, aspartate and glutamate metabolism, β-alanine metabolism, butanoate metabolism, ascorbate, and aldarate metabolism, and nicotinate and nicotinamide metabolism. Prior studies have highlighted that the sphingolipid signaling pathway, alcoholism, glutathione metabolism, taurine and hypotaurine metabolism, alanine, aspartate, and glutamate metabolism were all associated with GC [
31‐
34]. Strikingly, PD has been associated with most cancers in Taiwan [
35]. Abnormal arginine metabolism is a potential treatment for GC [
36]. Previous studies have also shown that the GC differential genes are enriched in the butyric acid metabolic pathway [
37]. Taylor et al. concluded that the ascorbic acid pathway was related to melanoma [
38]. Cumulative evidence suggests that nicotinamide plays an instrumental role in cancer prevention and therapy [
39]. Interestingly, the abundance of nicotinamide related metabolites was decreased in distal GC. Moreover, different metabolites identified in proximal GC were also related to insulin resistance, inflammatory mediator regulation of TRP channels, human papillomavirus infection, rheumatoid arthritis, glycine, serine, and threonine metabolism, glutamatergic synapse, cocaine addiction, necroptosis, circadian entrainment, and so on. Kwon et al. hypothesized that insulin resistance could be an independent risk factor for GC [
40]. Studies have corroborated that human cytomegalovirus infection is related to the occurrence and development of GC [
41]. The transient receptor potential (TRP) channel is the key receptor of pain stimulation signal transduction. The substances released by the microenvironment of different types of cancer govern the activity of TRPs by regulating intracellular signaling pathways [
42]. Prolonged immune dysregulation and the resulting inflammatory response associated with the development of rheumatoid arthritis could also lead to increased cancer development risk [
43]. There are overwhelming reports supporting the role of supplementary glycine in the prevention of many diseases and disorders, including cancer [
44]. Circadian timing can modify 2- to tenfold the tolerability of anticancer medications in experimental models and cancer patients [
45]. A study of colorectal cancer exposed the differences in genes between the liver metastases and the primary tumors. KEGG analysis of mutant genes showed that the mutations were mainly distributed in circadian entrainment, insulin secretion, and glutamatergic synapses [
46]. These results indicate that the occurrence of distal GC may be closely related to the disorder of amino acid metabolism, lipid metabolism, and nucleotide metabolism. Additionally, the occurrence and development of proximal GC may be related to hormone dysregulation.
According to Spearman’s correlation analysis,
Methylobacterium-Methylorubrum, which was significantly increased in Distal T, was positively correlated with adrenic acid, L-pyroglutamic acid, D-(-)-glutamine, and acetyl phosphate. However,
Methylobacterium-Methylorubrum was negatively correlated with glycerophospho-N-palmitoyl ethanolamine, γ-linolenic acid, α-eleostearic acid, monoolein, and FAHFA. L-pyroglutamic acid and glutamine are metabolites of glutamine metabolism, and they were significantly increased in Distal T[
47]. Studies have found that
Streptococcus can metabolize glutamine into pyroglutamate and ammonia [
48]. Recent research implies that adrenic acid can determine the sensitivity of ferroptosis in gastric cancer [
49]. Duan et al. showed that glycosphospho-N-palmitoyl ethanolamine is a potential biomarker of depression [
50]. Besides, correlation analysis revealed that
Methylobacterium-Methylorubrum was associated with the decrease in glycosphospho-N-palmitoyl ethanolamine in Distal T. γ-linolenic acid can inhibit the growth and epithelial-mesenchymal transformation of gastric cancer cells [
51]. Meanwhile, α-Eleostearic acid inhibits the proliferation of breast cancer cells [
52]. Monoolein and nanocomposites could be utilized for cancer drug delivery [
53]. Some FAHFAs can enhance glucose tolerance and insulin sensitivity, stimulate insulin secretion, and exert anti-inflammatory effects [
54].
Rikenellaceae_RC_gut_group, which was significantly increased in Proximal T, was positively correlated with N-acetylneuraminic acid, also referred to as sialic acid, and negatively correlated with 2,3-dihydroxypropyl 12-methyltridecanoate. Büll et al. observed that sialic acid had a key role in tumor immune escape. They proved that sialic acid block creates an immune permissive tumor microenvironment for CD8 + T cell-mediated tumor immunity [
55]. Earlier studies have reported that
Legionella pneumophila can be metabolized to 2,3-dihydroxypropyl 12-methyltridecanoate [
56]. The aforementioned results showed differences in microbial-related metabolites in proximal and distal GCs, which further suggested that there are distinct mechanisms for the occurrence and development of proximal and distal GCs.
Our study had several limitations that need to be taken into account. First, the sample size of proximal and distal GCs was limited, resulting in no significant difference in the microbial diversity and abundance between proximal and distal GCs. Second, differential microbiota and metabolites were discovered in proximal and distal GCs, and the pathways associated with metabolite enrichment were preliminarily analyzed. Nevertheless, no further experiments have been undertaken to determine the cause of this difference. Lastly, dietary habits and medications impact microbial composition and metabolism, but the patients’ dietary and medication data were not collected.
In conclusion, to the best of our knowledge, the differences in microbial composition and metabolites in proximal and distal GCs were described for the first time, and the correlation between microbiota and metabolites was preliminarily discussed. Methylobacterium-Methylorubrum was significantly increased in Distal T, positively correlated with cancer-promoting metabolites, and negatively correlated with cancer-inhibiting metabolites. Moreover, Rikenellaceae_RC_gut_group was significantly increased in Proximal T and was positively correlated with cancer-promoting metabolites. These metabolites and microbiota could be related to the various mechanisms involved in the occurrence and development of proximal and distal GCs and provide a foundation for future treatments; hence, they deserve further study.
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