Proteomics is a powerful approach to study the molecular mechanisms of cancer. In this study, we aim to characterize the proteomic profile of gastric cancer (GC) in patients with diabetes mellitus (DM) type 2. Forty GC tissue samples including 19 cases from diabetic patients and 21 cases from individuals without diabetes (control group) were selected for the proteomics analysis. Gastric tissues were processed following the single-pot, solid-phase-enhanced sample preparation approach—SP3 and enzymatic digestion with trypsin. The resulting peptides were analyzed by LC-MS Liquid Chromatography—Mass Spectrometry (LC-MS). The comparison of protein expression levels between GC samples from diabetic and non-diabetic patients was performed by label-free quantification (LFQ). A total of 6599 protein groups were identified in the 40 samples. Thirty-seven proteins were differentially expressed among the two groups, with 16 upregulated and 21 downregulated in the diabetic cohort. Statistical overrepresentation tests were considered for different annotation sets including the Gene Ontology(GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), Reactome, and Disease functional databases. Upregulated proteins in the GC samples from diabetic patients were particularly enriched in respiratory electron transport and alcohol metabolic biological processes, while downregulated proteins were associated with epithelial cancers, intestinal diseases, and cell–cell junction cellular components. Taken together, these results support the data already obtained by previous studies that associate diabetes with metabolic disorders and diabetes-associated diseases, such as Alzheimer’s and Parkinson’s, and also provide valuable insights into seven GC-associated protein targets, claudin-3, polymeric immunoglobulin receptor protein, cadherin-17, villin-1, transglutaminase-2, desmoglein-2, and mucin-13, which warrant further investigation.

Background: Epstein-Barr Virus (EBV) positive and microsatellite unstable (MSI-high) gastric cancer (GC) are molecular subgroups with distinctive molecular profiles. We explored the transcriptomic differences between EBV+ and MSI-high GCs, and the expression of current GC immunotherapy targets such as PD-1, PD-L1, CTLA4 and Dies1/VISTA. Methods: Using Nanostring Technology and comparative bioinformatics, we analyzed the expression of 499 genes in 46 GCs, classified either as EBV positive (EBER in situ hybridization) or MSI-high (PCR/fragment analysis). PD-L1 protein expression was assessed by immunohistochemistry. Results: From the 46 GCs, 27 tested MSI-high/EBV−, 15 tested MSS/EBV+ and four tested MSS/EBV−. The Nanostring CodeSet could segregate GCs according to MSI and, to a lesser extent, EBV status. Functional annotation of differentially expressed genes associated MSI-high/EBV− GCs with mitotic activity and MSS/EBV+ GCs with immune response. PD-L1 protein expression, evaluated in stromal immune cells, was lower in MSI-high/EBV− GCs. High mRNA expression of PD-1, CTLA4 and Dies1/VISTA and distinctive PD-1/PD-L1 co-expression patterns (PD-1^high/PD-L1^low, PD-1^high/PDL1^high) were associated with MSS/EBV+ molecular subtype and gastric cancer with lymphoid stroma (GCLS) morphological features. Conclusions: EBV+ and MSI-high GCs present distinct transcriptomic profiles. GCLS/EBV+ cases frequently present co-expression of multiple immunotherapy targets, a finding with putative therapeutic implications.

Gastric Cancer (GC) is one of the most common and deadliest types of cancer in the world. To improve GC prognosis, increasing efforts are being made to develop new targeted therapies. Although FGFR2 genetic amplification and protein overexpression in GC have been targeted in clinical trials, so far no improvement in patient overall survival has been found. To address this issue, we studied genetic and epigenetic events affecting FGFR2 and its splicing regulator ESRP1 in GC that could be used as new therapeutic targets or predictive biomarkers. We performed copy number variation (CNV), DNA methylation, and RNA expression analyses of FGFR2/ESRP1 across several cohorts. We discovered that both genes were frequently amplified and demethylated in GC, resulting in increased ESRP1 expression and of a specific FGFR2 isoform: FGFR2-IIIb. We also showed that ESRP1 amplification in GC correlated with a significant decreased expression of FGFR2-IIIc, an alternative FGFR2 splicing isoform. Furthermore, when we performed a survival analysis, we observed that patients harboring diffuse-type tumors with low FGFR2-IIIc expression revealed a better overall survival than patients with FGFR2-IIIc high-expressing diffuse tumors. Our results encourage further studies on the role of ESRP1 in GC and support FGFR2-IIIc as a relevant biomarker in GC.

Cadherins are cell–cell adhesion molecules, fundamental for cell architecture and polarity. E-cadherin to P-cadherin switch can rescue adherens junctions in epithelial tumours. Herein, we disclose a mechanism for E-cadherin to P-cadherin switch in gastric cancers. CDH1 and CDH3 mRNA expression was obtained from 42 gastric tumours’ RNA-seq data. CRISPR-Cas9 was used to knock out CDH1 and a putative regulatory element. CDH1-depleted and parental cells were submitted to proteomics and enrichment GO terms analysis; ATAC-seq/4C-seq with a CDH1 promoter viewpoint to assess chromatin accessibility and conformation; and RT-PCR/flow cytometry to assess CDH1/E-cadherin and CDH3/P-cadherin expression. In 42% of gastric tumours analysed, CDH1 to CDH3 switch was observed. CDH1 knockout triggered CDH1/E-cadherin complete loss and CDH3/P-cadherin expression increase at plasma membrane. This switch, likely rescuing adherens junctions, increased cell migration/proliferation, commonly observed in aggressive tumours. E- to P-cadherin switch accompanied increased CDH1 promoter interactions with CDH3–eQTL, absent in normal stomach and parental cells. CDH3–eQTL deletion promotes CDH3/CDH1 reduced expression. These data provide evidence that loss of CDH1/E-cadherin expression alters the CDH3 locus chromatin conformation, allowing a CDH1 promoter interaction with a CDH3-eQTL, and promoting CDH3/P-cadherin expression. These data highlight a novel mechanism triggering E- to P-cadherin switch in gastric cancer.

Transitions between epithelial and mesenchymal cellular states (EMT/MET) contribute to cancer progression. We hypothesize that EMT followed by MET promotes cell population heterogeneity, favouring tumour growth. We developed an EMT model by on and off exposure of epithelial EpH4 cells (E-cells) to TGFβ1 that mimics phenotypic EMT (M-cells) and MET. We aimed at understanding whether phenotypic MET is accompanied by molecular and functional reversion back to epithelia by using RNA sequencing, immunofluorescence (IF), proliferation, wound healing, focus formation and mamosphere formation assays as well as cell xenografts in nude mice. Phenotypic reverted epithelial cells (RE-cells) obtained after MET induction presented epithelial morphologies and proliferation rates resembling E cells. However, the RE transcriptomic profile and IF staining of epithelial and mesenchymal markers revealed a uniquely heterogeneous mixture of cell subpopulations with a high self-renewal ability. RE cell heterogeneity was stably maintained for long periods after TGFβ1 removal both in vitro and in large tumours derived from the nude mice. Overall, we show that phenotypic reverted epithelial cells (RE cells) do not return to the molecular and functional epithelial state and present mesenchymal features related to aggressiveness and cellular heterogeneity that favour tumour growth in vivo. This work strengthens epithelial cell reprogramming and cellular heterogeneity fostered by inflammatory cues as a tumour growth-promoting factor in vivo.

Transfer RNA fragments (tRFs) have gene silencing effects similarly to miRNAs, can be sorted into extracellular vesicles (EVs) and are emerging as potential circulating biomarkers for cancer diagnoses. We aimed at analyzing the expression of tRFs in gastric cancer (GC) and understanding their potential as biomarkers. We explored miRNA datasets from gastric tumors and normal adjacent tissues (NATs) from TCGA repository, as well as proprietary 3D-cultured GC cell lines and corresponding EVs, in order to identify differentially represented tRFs using MINTmap and R/Bioconductor packages. Selected tRFs were validated in patient-derived EVs. We found 613 Differentially Expressed (DE)-tRFs in the TCGA dataset, of which 19 were concomitantly upregulated in TCGA gastric tumors and present in 3D cells and EVs, but barely expressed in NATs. Moreover, 20 tRFs were expressed in 3D cells and EVs and downregulated in TCGA gastric tumors. Of these 39 DE-tRFs, 9 tRFs were also detected in patient-derived EVs. Interestingly, the targets of these 9 tRFs affect neutrophil activation and degranulation, cadherin binding, focal adhesion and the cell–substrate junction, highlighting these pathways as major targets of EV-mediated crosstalk with the tumor microenvironment. Furthermore, as they are present in four distinct GC datasets and can be detected even in low quality patient-derived EV samples, they hold promise as GC biomarkers. By repurposing already available NGS data, we could identify and cross-validate a set of tRFs holding potential as GC diagnosis biomarkers.