Gastric cancer Cell Models for Research

Gastric cancer (GC) is the fifth most common cancer and the fourth leading cause of cancer-related death worldwide, with an estimated 1.1 million new cases and 770,000 deaths in 2020 (WHO GLOBOCAN). The highest incidence rates are in Eastern Asia, Eastern Europe, and South America. Major risk factors include Helicobacter pylori infection, smoking, high salt intake, and genetic predisposition. The 5-year survival rate for localized gastric cancer is about 70%, but for metastatic disease it drops to less than 5% (NCI SEER). This stark contrast underscores the urgent need for early detection and effective therapies.

Gastric cancer is a heterogeneous disease with distinct molecular subtypes (e.g., EBV-positive, microsatellite instability, genomically stable, chromosomal instability) as defined by TCGA. This heterogeneity makes it an ideal model for studying tumor evolution, drug resistance, and personalized medicine. Public datasets such as TCGA, COSMIC, and DepMap provide extensive genomic and functional data, enabling researchers to identify novel therapeutic targets. Gene-edited cell models are essential for functional validation of these targets, allowing precise manipulation of genes in relevant cellular contexts.

Gastric cancer arises from the accumulation of genetic and epigenetic alterations that activate oncogenes and inactivate tumor suppressors. Key pathways include:

• • Wnt/β-catenin pathway: Mutations in CTNNB1 or APC lead to β-catenin stabilization and transcriptional activation of MYC and CCND1.
• • p53 pathway: TP53 mutations are common, impairing cell cycle arrest and apoptosis.
• • RTK/RAS/MAPK pathway: Amplifications or mutations in ERBB2, EGFR, KRAS, and BRAF drive proliferation.
• • PI3K/AKT/mTOR pathway: Mutations in PIK3CA and PTEN loss activate survival signaling.
• • TGF-β pathway: Mutations in TGFBR2 or SMAD4 disrupt growth inhibition.

These pathways are frequently deregulated in gastric cancer and provide targets for therapeutic intervention.

Data from TCGA and COSMIC.

Gastric cancer exhibits extensive crosstalk between signaling networks. Key nodes include:

• • Wnt/β-catenin: β-catenin translocates to nucleus, activates TCF/LEF transcription factors.
• • MAPK cascade: RAS activates RAF, MEK, and ERK, promoting proliferation.
• • PI3K/AKT: PIP3 recruits AKT, which phosphorylates downstream targets like mTOR.
• • JAK/STAT: Cytokine receptors activate STAT3, driving inflammation and survival.

These networks are interconnected, and their dysregulation contributes to tumor aggressiveness and drug resistance.

Organoids derived from patient tumors recapitulate the 3D architecture and genetic heterogeneity, making them valuable for drug testing and personalized medicine.

• • Patient-derived xenografts (PDX): Tumor fragments implanted into immunodeficient mice, preserving the original tumor's genetic and histological features.
• • Genetically engineered mouse models (GEMM): Mice with conditional knockouts or knock-ins of genes like CDH1, TP53, or KRAS develop gastric tumors.
• • Induced models: Chemical carcinogens (e.g., N-methyl-N-nitrosourea) or H. pylori infection can induce gastric cancer in mice.

These models are essential for studying tumor biology and testing therapies in vivo.

CRISPR-Cas9 technology enables the creation of isogenic cell lines with precise genetic modifications, such as knockout of tumor suppressors or knock-in of oncogenic mutations. For example, a TP53 knockout in AGS cells can be used to study the effects of p53 loss on drug sensitivity. Similarly, an ERBB2 knock-in in MKN45 cells can model HER2 amplification for targeted therapy research. These gene-edited models are commercially available and sequence-verified, accelerating research by providing consistent and reproducible systems. They are essential for functional genomics, drug screening, and target validation.

Gene-edited cell lines allow researchers to determine the functional consequences of specific genetic alterations. For instance, knocking out CDH1 in gastric epithelial cells can increase cell migration and invasion, confirming its role as a metastasis suppressor. Similarly, introducing a KRAS G12D mutation into a wild-type cell line can drive proliferation and transformation, validating its oncogenic potential.

Isogenic pairs (wild-type vs. knockout) are powerful tools for drug screening. By comparing the response of these cells to a panel of compounds, researchers can identify drugs that specifically target the mutated pathway. For example, a PIK3CA-mutant cell line may be more sensitive to PI3K inhibitors than its wild-type counterpart. Additionally, gene-edited cells can be used to study resistance mechanisms by exposing them to increasing drug concentrations and identifying secondary mutations.

CRISPR-based synthetic lethality screens can identify genes that are essential only in the context of a specific mutation. For example, in a TP53-null gastric cancer cell line, knocking out other genes can reveal vulnerabilities that can be targeted therapeutically. This approach has led to the discovery of novel biomarkers and drug targets.