Introduction: CT10 regulator of kinase (Crk) adaptor proteins (CrkI, CrkII and CrkL) play a role in integrating signals for migration and invasion of highly malignant breast cancer cell lines. This has important implications, as elevated CrkI/II protein levels were observed in a small cohort of breast cancer patients, which identified a potential role for Crk proteins in breast cancer progression. Numerous in vitro studies identified a role for Crk proteins in cell motility, but little is known about how Crk proteins contribute to breast cancer progression in vivo. Methods: The clinical significance of Crk proteins in human breast cancer was assessed by analyzing published breast cancer datasets using a gene expression signature that was generated following CrkII over-expression and by examining Crk protein expression in tissue microarrays of breast tumors (n = 254). Stable knockdown of Crk (CrkI/CrkII/CrkL) proteins was accomplished using a short hairpin RNA (shRNA)-mediated approach in two basal breast cancer cell lines, MDA-231 1833TR and SUM1315, where the former have a high affinity to form bone metastases. Both in vitro assays (cell migration, invasion, soft agar growth) and in vivo experiments (intra-cardiac, tibial and mammary fat pad injections) were performed to assess the functional significance of Crk proteins in breast cancer. Results: A gene signature derived following CrkII over-expression correlated significantly with basal breast cancers and with high grade and poor outcome in general. Moreover, elevated Crk immunostaining on tissue microarrays revealed a significant association with highly proliferative tumors within the basal subtype. RNAi-mediated knockdown of all three Crk proteins in metastatic basal breast cancer cells established a continued requirement for Crk in cell migration and invasion in vitro and metastatic growth in vivo. Furthermore, Crk ablation suppressed anchorage independent growth and in vivo orthotopic tumor growth. This was associated with diminished cell proliferation and was rescued by expression of non-shRNA targeted CrkI/II. Perturbations in tumor progression correlated with altered integrin signaling, including decreased cell spreading, diminished p130Cas phosphorylation, and Cdc42 activation. Conclusions: These data highlight the physiological importance of Crk proteins in regulating growth of aggressive basal breast cancer cells and identify Crk-dependent signaling networks as promising therapeutic targets.

Invasive lobular carcinoma (ILC) is the second most common histological subtype of breast cancer, and it exhibits a number of clinico-pathological characteristics distinct from the more common invasive ductal carcinoma (IDC). We set out to identify alterations in the tumor microenvironment (TME) of ILC. We used laser-capture microdissection to separate tumor epithelium from stroma in 23 ER+ ILC primary tumors. Gene expression analysis identified 45 genes involved in regulation of the extracellular matrix (ECM) that were enriched in the non-immune stroma of ILC, but not in non-immune stroma from ER+ IDC or normal breast. Of these, 10 were expressed in cancer-associated fibroblasts (CAFs) and were increased in ILC compared to IDC in bulk gene expression datasets, with PAPPA and TIMP2 being associated with better survival in ILC but not IDC. PAPPA, a gene involved in IGF-1 signaling, was the most enriched in the stroma compared to the tumor epithelial compartment in ILC. Analysis of PAPPA- and IGF1-associated genes identified a paracrine signaling pathway, and active PAPP-A was shown to be secreted from primary CAFs. This is the first study to demonstrate molecular differences in the TME between ILC and IDC identifying differences in matrix organization and growth factor signaling pathways.

Background: Invasive lobular carcinoma (ILC) is the second most common histological subtype of breast cancer and exhibits a number of clinico-pathological characteristics that are distinct from the more common invasive ductal carcinoma (IDC). Despite these differences, ILC is treated in the same way as IDC. We set out to identify alterations in the tumor microenvironment (TME) of ILC with potential clinical significance. Methods: We used laser-capture microdissection (LCM) to separate tumor epithelium from stroma in 23 ER+ ILC samples. Gene expression analysis was used to identify genes that are enriched in the stroma of ILC, but not IDC or normal breast. Results: 45 genes involved in regulation of the extracellular matrix (ECM) were enriched in the stroma of ILC, but not stroma from ER+ IDC or normal breast. Of these, 10 were expressed in cancer-associated fibroblasts (CAFs) and were increased in ILC compared to IDC in bulk gene expression datasets. PAPPA was the most enriched in the stroma compared to the tumor epithelial compartment in ILC. PAPPA encodes pregnancy-associated plasma protein-A (PAPP-A), a metalloproteinase that cleaves insulin-like binding protein-4 (IGFBP-4) increasing IGF-1 bioavailability and subsequent downstream signaling. Analysis of PAPPA and IGF1 associated genes identified a paracrine signaling pathway and active PAPP-A was shown to be secreted from primary CAFs. Comprehensive survival analysis across 3000 breast cancers identified PAPPA as a potential ILC-specific prognostic marker. Conclusions: This is the first study to demonstrate molecular differences in the TME between ILC and IDC and identifies PAPP-A, a CAF-derived proteinase, as a potential prognostic marker.

A major limitation in studying gastroesophageal adenocarcinoma (GEA) has been the lack of reliable models that represent the disease’s complexity. We present lessons learned from a comprehensive large-scale biobanking effort combining traditional sample collection with several in vitro models, including 3-dimensional patient-derived organoids (PDOs), 2-dimensional cancer-associated fibroblasts (CAFs), tumor-infiltrating lymphocytes (TILs), and/or in vivo xenografts. This initiative started in 2018, integrating multiple advanced ex vivo models such as PDOs, patient-derived xenografts (PDXs), and organoids (PDXOs). This unique resource now includes tumor avatars from over 380 consented patients, making it the world’s largest living GEA biobank. We achieved a >90% success rate in creating per-patient models, including 227 tumor-derived and 203 neighboring normal PDOs. These organoids accurately mirror key features of the original tumors, such as their histology (e.g., microsatellite instability), mutations, and drug response across treatment points. Notably, PDOs can predict individual patient responses to chemotherapy within five weeks, underscoring their clinical relevance. Furthermore, high-throughput drug screening on PDO subsets with known genetic landscapes generates personalized chemosensitivity profiles for 22 drugs. Through a process of continued refinement of culture techniques and tumor sampling approach, our large-scale comprehensive collection of GEA avatars represents a unique and valuable preclinical experimental resource for precision oncology.