The diffuse-type gastric cancer (DGC) is a subtype of gastric cancer with the worst prognosis and few treatment options. Here we present a dataset from 84 DGC patients, composed of a proteome of 11,340 gene products and mutation information of 274 cancer driver genes covering paired tumor and nearby tissue. DGC can be classified into three subtypes (PX1–3) based on the altered proteome alone. PX1 and PX2 exhibit dysregulation in the cell cycle and PX2 features an additional EMT process; PX3 is enriched in immune response proteins, has the worst survival, and is insensitive to chemotherapy. Data analysis revealed four major vulnerabilities in DGC that may be targeted for treatment, and allowed the nomination of potential immunotherapy targets for DGC patients, particularly for those in PX3. This dataset provides a rich resource for information and knowledge mining toward altered signaling pathways in DGC and demonstrates the benefit of proteomic analysis in cancer molecular subtyping.

Neoadjuvant chemotherapy is a common treatment for patients with gastric cancer. Although its benefits have been demonstrated, neoadjuvant chemotherapy is underutilized in gastric cancer management, because of the lack of biomarkers for patient selection and a limited understanding of resistance mechanisms. Here, we performed whole-genome, whole-exome, and RNA sequencing on 84 clinical samples (including matched pre- and posttreatment tumors) from 35 patients whose responses to neoadjuvant chemotherapy were rigorously defined. We observed increased microsatellite instability and mutation burden in nonresponse tumors. Through comparisons of response versus nonresponse tumors and pre- versus posttreatment samples, we found that C10orf71 mutations were associated with treatment resistance, which was supported by drug response data and potentially through inhibition of cell cycle, and that MYC amplification correlated with treatment sensitivity, whereas MDM2 amplification showed the opposite pattern. Neoadjuvant chemotherapy also reshapes tumor-immune signaling and microenvironment. Our study provides a critical basis for developing precision neoadjuvant regimens.

A preclinical trial identified 4 of 20 (20%) gastric cancer (GC) patient-derived xenografts responded to cetuximab. Genome-wide profiling and additional investigations revealed that high EGFR mRNA expression and immunohistochemistry score (3+) are associated with tumor growth inhibition. Furthermore, EGFR amplification were observed in 2/4 (50%) responders with average copy number 5.8 and >15 respectively. Our data suggest that a GC subtype with EGFR amplification and overexpression benefit from cetuximab treatment.

Xenotransplantation of human cancers into immunodeficient mice is a very useful approach for studying human tumor biology. However, the occasional occurrence of lymphomagenesis in some mice can spoil the model and must be investigated in detail. We found that a high percentage (32.5%, 26/80) of cancer patient-derived xenografts (PDXs) resembled lymphoma in NOD/SCID mice. Of the 26 xenografts, 23 were human-derived expressing human CD45 (hCD45+) and proved to be of the B-cell subtype (CD3-/CD20+) and they were all positive for Epstein - Barr virus (EBV). The remaining 3 xenografts proved to be mouse-derived for both hCD45- and negative amplification of a human gene. The most interesting finding is that gastric cancer had much higher rates (24/126, 19.0%) of lymphoma formation in the PDX model than did colorectal cancer (1/43, 2.3%). Statistical analysis revealed that cancer type and inflammation in the parent tumor are significantly associated with lymphomagenesis. Further validation discovered lymphomagenesis by inoculating only gastritis mucosa. Therefore, our findings suggest that it is necessary to take precautions when directly xenografting cancer tissues with remarkable baseline inflammation, such as gastric cancer into immunodeficient NOD/SCID strains. Further, the established xenograft models should be validated by both leukocyte markers and human gene signatures.