Personalized cancer treatment begins with personalized models. But traditional PDX approaches are often slow, costly, and ethically constrained. That’s why leading oncology innovators are turning to the CAM (Chorioallantoic Membrane) model – a fast, immune-reactive platform capable of hosting patient-derived tumor xenografts and circulating tumor cell (CTC)-based avatars.

INOVOTION NAMs CAM model supports functional drug screening, tumor microenvironment analysis, and mechanistic insights using real patient material.

Here’s how studies in Federation of American Societies for Experimental Biology (FASEB) journal and Cancers validate this powerful use case:

1. Liver Cancer Models for IO Therapy Response
“Liver cancer in ovo models for preclinical testing”
Garcia P et al. (2024). FASEB J

Developed several liver cancer avatars (e.g., PLC/PRF/5, Hep3B) in the CAM model. Treatments with atezolizumab (anti–PD-L1) and bevacizumab (anti–VEGF) revealed distinct responses in “hot” vs. “cold” tumor phenotypes – showing CAM’s capacity to model tumor immune microenvironment heterogeneity.
Pubmed: https://pubmed.ncbi.nlm.nih.gov/39215630/

2. CTC-Derived CAM Avatars to Track Metastatic Potential
“Embryonated Chicken Tumor Xenografts Derived from Circulating Tumor Cells as a Relevant Model to Study Metastatic Dissemination: A Proof of Concept“
Rousset X et al. (2022). Cancers (Basel)

Engrafted CTCs from metastatic cancer patients (breast, lung, prostate) into CAM embryos. Resulting tumors retained key genetic alterations and metastatic behavior, including dissemination to distant organs – proving that even rare, aggressive cell populations can be modeled in ovo.
Pubmed: https://pubmed.ncbi.nlm.nih.gov/36077622/

These studies prove that Inovotion’s NAMs CAM model supports patient-specific tumor behavior, immunotherapy evaluation, and genetic and phenotypic fidelity – making it a compelling platform for functional precision oncology, drug stratification, and biomarker discovery.

With faster engraftment, high success rates, and in vivo complexity, CAM avatars are redefining what’s possible in personalized preclinical cancer models.