Introduction: Interleukin-like epithelial-to-mesenchymal transition inducer (ILEI) is an essential cytokine in tumor progression that is upregulated in several cancers, and its altered subcellular localization is a predictor of poor survival in human breast cancer. However, the regulation of ILEI activity and the molecular meaning of its altered localization remain elusive. Methods: The influence of serum withdrawal, broad-specificity protease inhibitors, different serine proteases and plasminogen depletion on the size and amount of the secreted ILEI protein was investigated by Western blot analysis of EpRas cells. Proteases with ILEI-processing capacity were identified by carrying out an in vitro cleavage assay. Murine mammary tumor and metastasis models of EpC40 and 4T1 cells overexpressing different mutant forms of ILEI were used—extended with in vivo aprotinin treatment for the inhibition of ILEI-processing proteases—to test the in vivo relevance of proteolytic cleavage. Stable knockdown of urokinase plasminogen activator receptor (uPAR) in EpRas cells was performed to investigate the involvement of uPAR in ILEI secretion. The subcellular localization of the ILEI protein in tumor cell lines was analyzed by immunofluorescence. Immunohistochemistry for ILEI localization and uPAR expression was performed on two human breast cancer arrays, and ILEI and uPAR scores were correlated with the metastasis-free survival of patients. Results: We demonstrate that secreted ILEI requires site-specific proteolytic maturation into its short form for its tumor-promoting function, which is executed by serine proteases, most efficiently by plasmin. Noncleaved ILEI is tethered to fibronectin-containing fibers of the extracellular matrix through a propeptide-dependent interaction. In addition to ILEI processing, plasmin rapidly increases ILEI secretion by mobilizing its intracellular protein pool in a uPAR-dependent manner. Elevated ILEI secretion correlates with an altered subcellular localization of the protein, most likely representing a shift into secretory vesicles. Moreover, altered subcellular ILEI localization strongly correlates with high tumor cell–associated uPAR protein expression, as well as with poor survival, in human breast cancer. Conclusions: Our findings point out extracellular serine proteases, in particular plasmin, and uPAR as valuable therapeutic targets against ILEI-driven tumor progression and emphasize the prognostic relevance of ILEI localization and a combined ILEI-uPAR marker analysis in human breast cancer.

Recent years have ushered in a transformative era in in vitro modeling with the advent of organoids, three-dimensional structures derived from stem cells or patient tumor cells. Still, fully harnessing the potential of organoids requires advanced imaging technologies and analytical tools to quantitatively monitor organoid growth. Optical coherence tomography (OCT) is a promising imaging modality for organoid analysis due to its high-resolution, label-free, non-destructive, and real-time 3D imaging capabilities, but accurately identifying and quantifying organoids in OCT images remain challenging due to various factors. Here, we propose an automatic deep learning-based pipeline with convolutional neural networks that synergistically includes optimized preprocessing steps, the implementation of a state-of-the-art deep learning model, and ad-hoc postprocessing methods, showcasing good generalizability and tracking capabilities over an extended period of 13 days. The proposed tracking algorithm thoroughly documents organoid evolution, utilizing reference volumes, a dual branch analysis, key attribute evaluation, and probability scoring for match identification. The proposed comprehensive approach enables the accurate tracking of organoid growth and morphological changes over time, advancing organoid analysis and serving as a solid foundation for future studies for drug screening and tumor drug sensitivity detection based on organoids.

Background: Gene amplification of MET, which encodes for the receptor tyrosine kinase c-MET, occurs in a variety of human cancers. High c-MET levels often correlate with poor cancer prognosis. Interleukin-like EMT inducer (ILEI) is also overexpressed in many cancers and is associated with metastasis and poor survival. The gene for ILEI, FAM3C, is located close to MET on chromosome 7q31 in an amplification “hotspot”, but it is unclear whether FAMC3 amplification contributes to elevated ILEI expression in cancer. In this study we have investigated FAMC3 copy number gain in different cancers and its potential connection to MET amplifications. Methods: FAMC3 and MET copy numbers were investigated in various cancer samples and 200 cancer cell lines. Copy numbers of the two genes were correlated with mRNA levels, with relapse-free survival in lung cancer patient samples as well as with clinicopathological parameters in primary samples from 49 advanced stage colorectal cancer patients. ILEI knock-down and c-MET inhibition effects on proliferation and invasiveness of five cancer cell lines and growth of xenograft tumors in mice were then investigated. Results: FAMC3 was amplified in strict association with MET amplification in several human cancers and cancer cell lines. Increased FAM3C and MET copy numbers were tightly linked and correlated with increased gene expression and poor survival in human lung cancer and with extramural invasion in colorectal carcinoma. Stable ILEI shRNA knock-down did not influence proliferation or sensitivity towards c-MET-inhibitor induced proliferation arrest in cancer cells, but impaired both c-MET-independent and -dependent cancer cell invasion. c-MET inhibition reduced ILEI secretion, and shRNA mediated ILEI knock-down prevented c-MET-signaling induced elevated expression and secretion of matrix metalloproteinase (MMP)-2 and MMP-9. Combination of ILEI knock-down and c-MET-inhibition significantly reduced the invasive outgrowth of NCI-H441 and NCI-H1993 lung tumor xenografts by inhibiting proliferation, MMP expression and E-cadherin membrane localization. Conclusions: These novel findings suggest MET amplifications are often in reality MET-FAM3C co-amplifications with tight functional cooperation. Therefore, the clinical relevance of this frequent cancer amplification hotspot, so far dedicated purely to c-MET function, should be re-evaluated to include ILEI as a target in the therapy of c-MET-amplified human carcinomas.

FAM3C/ILEI is an important cytokine for tumor progression and metastasis. However, its involvement in inflammation remains elusive. Here, we show that ILEI protein is highly expressed in psoriatic lesions. Inducible keratinocyte‐specific ILEI overexpression in mice ( K5‐ILEI ^ind ) recapitulates many aspects of psoriasis following TPA challenge, primarily manifested by impaired epidermal differentiation and increased neutrophil recruitment. Mechanistically, ILEI triggers Erk and Akt signaling, which then activates STAT3 via Ser727 phosphorylation. Keratinocyte‐specific ILEI deletion ameliorates TPA‐induced skin inflammation. A transcriptomic ILEI signature obtained from the K5 ‐ ILEI ^ind model shows enrichment in several signaling pathways also found in psoriasis and identifies urokinase as a targetable enzyme to counteract ILEI activity. Pharmacological inhibition of urokinase in TPA‐induced K5‐ILEI ^ind mice results in significant improvement of psoriasiform symptoms by reducing ILEI secretion. The ILEI signature distinguishes psoriasis from healthy skin with uPA ranking among the top “separator” genes. Our study identifies ILEI as a key driver in psoriasis, indicates the relevance of ILEI‐regulated genes for disease manifestation, and shows the clinical impact of ILEI and urokinase as novel potential therapeutic targets in psoriasis.

Cancer organoids and cancer spheroids are 3D cell culture models with distinct yet overlapping purposes in cancer research. Various commercially available optical imaging techniques have been employed to study these cell cultures, but these methods suffer from various limitations such as the requirement of fluorescence labeling, complicated sample handling, and limited image volume size. In this work, we demonstrate a multimodal optical coherence photoacoustic microscopy (OC-PAM) system for the study of these models, overcoming these limitations. We first performed a longitudinal study using optical coherence microscopy (OCM) for breast cancer organoids. Using the OCM imaging results, artificial intelligence (AI)-based algorithms were developed to automatically segment individual organoids and classify their viability over time using a radiomics texture feature approach, enabling robust, quantitative tracking and classification at the single-organoid level. To supplement OCM’s contrast, we then performed OC-PAM imaging of spheroid models with both melanin positive and melanin negative cells. In the second study, the OC-PAM images clearly mapped the distribution of melanin positive cells hidden amongst melanin negative cells. These results suggest that OC-PAM coupled with AI techniques can be a powerful tool to study cancer organoids and cancer spheroids.