Breast cancer is the second leading cause of cancer deaths among women. Breast tumorigenesis and progression arise through a sequential accumulation of mutations in oncogenes and tumor suppressor genes that serve as tumor driver genes. MET tyrosine kinase is the hepatocyte growth factor/scatter factor (HGF/SF) receptor. MET constitutive activation and mutations have profound effects on promoting tumor growth and metastases. We hypothesize that MET activation, alteration of other driver genes, and Inherited Driver Modifier Gene products (IDMGs) generate Dynamic Driver Modifiers Protein-Protein Carcinogenic Networks (DMCNs) that Induce tumorigenesis and metastasis.
To isolate MET-IDMGs and DMCNs, we created a novel mice model in which 20 CC lines (Collaborative-Cross CC - mice with diverse genetic backgrounds) overexpress the activated MET receptor. We followed tumor development using CT imaging and characterized the pathology H&E staining analysis. Tumor follow-up revealed that the mutated MET CC lines showed wider diversity regarding tumor types (carcinoma, lymphoma, and sarcoma).
QTL and computational bioinformatics analyses (SNP’s, ANAT and Human cBioPortal Database), together with qPCR and immunofluorescence staining, enabled the selection of 9 candidates IDMGs that demonstrate alteration by modulation of MET signaling. Several IDMGs served as very significant prognostic factors in human breast cohorts. Another set of candidate IDMGs code for pathomic and radiomic features. QTL analysis based on the AI of the nuclear structure enable the isolation of MET induced nuclear morphology modifiers.
CRISPR-CAS9 KD and KO of several IDMGs significantly altered MET expression and reduced MET-induced motility. We developed a precision medicine tool using graphic AI and MET and IDMGs expression. Using our morphokinetic analysis infrastructure we demonstrate that KO of NCKAP5L MET candidate modifier showed dramatic decrease in the Morphokinetic parameters, validating its role in MET induced cell motility.
These results demonstrate that modifier genes play a significant role in tumor type development and tumor progression. The multidisciplinary molecular imaging analysis enables elucidating the molecular mechanisms of MET-induced tumorigenicity to generate novel prognostic factors and precision anti-MET therapy.