Breast cancer Cell Models for Research

Breast cancer is the most commonly diagnosed cancer worldwide, with an estimated 2.3 million new cases and 685,000 deaths in 2020 (WHO). It is the leading cause of cancer death in women. In the United States, the 5-year relative survival rate is 90% for localized disease, but drops to 28% for distant metastases (NCI SEER). Risk factors include age, genetic mutations (BRCA1/2), reproductive history, and lifestyle factors.

Breast cancer is a heterogeneous disease with distinct molecular subtypes (luminal A, luminal B, HER2-enriched, basal-like/triple-negative). This diversity makes it an ideal model for studying oncogenic pathways, drug resistance, and precision medicine. Public datasets such as TCGA and DepMap provide extensive genomic and functional data, enabling mechanistic studies and target discovery.

Key pathways in breast cancer pathogenesis include:

1. Estrogen receptor (ER) signaling: ER activation drives proliferation in luminal subtypes.

2. HER2/neu signaling: Amplification/overexpression activates PI3K/AKT and MAPK pathways.

3. PI3K/AKT/mTOR pathway: Frequently mutated (PIK3CA) leading to cell survival and growth.

4. DNA repair pathways: BRCA1/2 mutations impair homologous recombination, leading to genomic instability.

Data from TCGA and COSMIC.

Deregulated signaling networks in breast cancer include:

• • PI3K/AKT/mTOR: Key nodes: PIK3CA, PTEN, AKT1, MTOR. Activation promotes cell growth and survival.
• • MAPK/ERK: Key nodes: KRAS, BRAF, EGFR, HER2. Drives proliferation and differentiation.
• • Wnt/β-catenin: Key nodes: CTNNB1, APC, LRP5/6. Involved in stem cell maintenance and invasion.
• • JAK/STAT: Key nodes: JAK2, STAT3. Mediates inflammation and immune evasion.

Organoids derived from patient tumors preserve 3D architecture and heterogeneity, offering more physiologically relevant models for drug testing.

Animal models include:

• • Patient-derived xenografts (PDX): Engraftment of patient tumors in immunodeficient mice, preserving tumor heterogeneity.
• • Genetically engineered mouse models (GEMM): Conditional knock-in of oncogenes (e.g., MMTV-PyMT) or knockout of tumor suppressors (e.g., BRCA1).
• • Induced models: Use of carcinogens or hormonal stimulation to induce tumors.

CRISPR-based gene editing enables the creation of isogenic cell lines with precise genetic modifications. For example:

• • BRCA1 knockout in MCF10A cells to study DNA repair deficiency.
• • PIK3CA H1047R knock-in in MCF7 cells to model oncogenic activation.
• • TP53 R175H knock-in in MDA-MB-231 to study mutant p53 gain-of-function.

These models are commercially available and sequence-verified, providing reproducible tools for drug discovery and functional genomics.

Knockout and knock-in lines are used to validate gene function. For example, CRISPR-mediated knockout of ESR1 in MCF7 cells confirms its role in estrogen-dependent growth. Knock-in of activating mutations (e.g., PIK3CA) allows study of oncogenic signaling.

Isogenic pairs (wild-type vs. mutant) are used in high-throughput screens to identify selective inhibitors. Resistance models can be generated by chronic exposure to drugs, and CRISPR editing can introduce known resistance mutations (e.g., ESR1 Y537S) to study mechanisms.

CRISPR screens (e.g., synthetic lethality) identify genes whose knockout is lethal in specific genetic backgrounds. For example, PARP inhibitors are effective in BRCA1-deficient cells due to synthetic lethality. Gene-edited models enable discovery of novel biomarkers for patient stratification.