Esophageal cancer (EC) is a worldwide healthcare concern and represents an aggressive malignancy. Squamous cell carcinoma (ESCC) and adenocarcinoma (EAC) are the two primary histological subtypes b...

We discuss the importance of the in vivo models in elucidating cancer biology, focusing on the patient-derived xenograft (PDX) models, which are classic and standard functional in vivo platforms for preclinical evaluation. We provide an overview of the most representative models, including cell-derived xenografts (CDX), tumor and metastatic cell-derived xenografts, and PDX models utilizing humanized mice (HM). The orthotopic models, which could reproduce the cancer environment and its progression, similar to human tumors, are particularly common. The standard procedures and rationales of gastric adenocarcinoma (GAC) orthotopic models are addressed. Despite the significant advantages of the PDX models, such as recapitulating key features of human tumors and enabling drug testing in the in vivo context, some challenges must be acknowledged, including loss of heterogeneity, selection bias, clonal evolution, stroma replacement, tumor micro-environment (TME) changes, host cell carryover and contaminations, human-to-host cell oncogenic transformation, human and host viral infections, as well as limitations for immunologic research. To compensate for these limitations, other mouse models, such as syngeneic and humanized mouse models, are currently utilized. Overall, the PDX models represent a powerful tool in cancer research, providing critical insights into tumor biology and potential therapeutic targets, but their limitations and challenges must be carefully considered for their effective use. Lastly, we present an intronic quantitative PCR (qPCR) method to authenticate, detect, and quantify human/murine cells in cell lines and PDX samples.

Objective: Many cancers engage embryonic genes for rapid growth and evading the immune system. SOX9 has been upregulated in many tumours, yet the role of SOX9 in mediating immunosuppressive tumour microenvironment is unclear. Here, we aim to dissect the role of SOX9-mediated cancer stemness attributes and immunosuppressive microenvironment in advanced gastric adenocarcinoma (GAC) for novel therapeutic discoveries. Methods: Bulk RNAseq/scRNA-seq, patient-derived cells/models and extensive functional studies were used to identify the expression and functions of SOX9 and its target genes in vitro and in vivo. Immune responses were studied in PBMCs or CD45⁺ immune cells cocultured with tumour cells with SOX9^high or knockout and the KP-Luc2 syngeneic models were used for efficacy of combinations. Results: SOX9 is one of the most upregulated SOX genes in GAC and highly expressed in primary and metastatic tissues and associated with poor prognosis. Depletion of SOX9 in patient-derived GAC cells significantly decreased cancer stemness attributes, tumour formation and metastases and consistently increased CD8⁺ T cell responses when cocultured with PBMCs/CD45⁺ cells from GAC patients. RNA sequencing identified the leukaemia inhibitory factor (LIF) as the top secreted molecule regulated by SOX9 in tumour cells and was enriched in malignant ascites and mediated SOX9-induced M2 macrophage repolarisation and inhibited T cell function. Conclusion: Epithelial SOX9 is critical in suppressing CD8⁺ T cell responses and modified macrophage function in GAC through the paracrine LIF factor. Cotargeting LIF/LIFR and CSF1R has great potential in targeting SOX9-mediated cancer stemness, T cell immunosuppression and metastases suggesting the novel combination therapy against advanced GAC.

PURPOSE: Claudin 18 isoform 2 (CLDN18.2) is an emerging biomarker and therapeutic target in gastric and gastroesophageal junction (G/GEJ) adenocarcinoma. This study aimed to obtain deeper understanding of CLDN18.2 positivity patterns, prognostic implications, and associations with various demographic, clinical, and molecular characteristics in G/GEJ adenocarcinoma. METHODS: Archived tumor tissue samples from 304 patients with G/GEJ adenocarcinoma in the United States were assessed for CLDN18.2 positivity by immunohistochemistry. CLDN18.2 positivity was defined as ≥50% or ≥75% of tumor cells with CLDN18 staining intensity ≥2+. CLDN18.2 positivity patterns were analyzed for association with prognosis and clinicopathologic/demographic characteristics. Where possible, CLDN18.2 positivity was analyzed for matched tissue samples to assess concordance between primary and metastatic tumors and concordance before and after chemotherapy. RESULTS: The overall prevalence of CLDN18.2-positive tumors (with ≥75% cutoff) was 44.4% (n = 135 of 304). CLDN18.2-positive tumors had a prevalence of 51.4% (n = 91 of 177) in gastric and 34.6% (n = 44 of 127) in GEJ adenocarcinoma. With a ≥50% cutoff, the prevalence of CLDN18.2-positive tumors was 64.4% (n = 114 of 177) in gastric adenocarcinoma and 44.9% (n = 57 of 127) in GEJ adenocarcinoma. There was no association between overall survival and CLDN18.2 positivity using either threshold. Statistically significant associations were noted between CLDN18.2 positivity and sex, histologic type of G/GEJ adenocarcinoma, and adenocarcinoma subtype (≥75% cutoff), and metastasis site and tumor grade (≥50% cutoff). The overall concordance of CLDN18.2 positivity (≥75% cutoff) was 73% (27 of 37) for matched primary versus metastatic tumor samples and 74% (29 of 39) for matched samples before and after chemotherapy. CONCLUSION: This study demonstrated that CLDN18.2 positivity did not correlate with survival in G/GEJ adenocarcinoma, consistent with published data. On the basis of matched sample analysis, CLDN18.2 appears to demonstrate >70% concordance as a biomarker. Observed correlations with certain patient/tumor characteristics warrant further study.

Objective: Prognosis of patients with advanced oesophagogastric adenocarcinoma (mEGAC) is poor and molecular determinants of shorter or longer overall survivors are lacking. Our objective was to identify molecular features and develop a prognostic model by profiling the genomic features of patients with mEGAC with widely varying outcomes. Design: We profiled 40 untreated mEGACs (20 shorter survivors 36 months) with whole-exome sequencing (WES) and RNA sequencing and performed an integrated analysis of exome, transcriptome, immune profile and pathological phenotypes to identify the molecular determinants, developing an integrated model for prognosis and comparison with The Cancer Genome Atlas (TCGA) cohorts. Results: KMT2C alterations were exclusively observed in shorter survivors together with high level of intratumour heterogeneity and complex clonal architectures, whereas the APOBEC mutational signatures were significantly enriched in longer survivors. Notably, the loss of heterozygosity in chromosome 4 (Chr4) was associated with shorter survival and ‘cold’ immune phenotype characterised by decreased B, CD8, natural killer cells and interferon-gamma responses. Unsupervised transcriptomic clustering revealed a shorter survivor subtype with distinct expression features (eg, upregulated druggable targets JAK2, MAP3K13 and MECOM ). An integrated model was then built based on clinical variables and the identified molecular determinants, which significantly segregated shorter and longer survivors. All the above features and the integrated model have been validated independently in multiple TCGA cohorts. Conclusion: This study discovered novel molecular features prognosticating overall survival in patients with mEGAC and identified potential novel targets in shorter survivors.