Comparison of EMT-Related and Multi-Drug Resistant Gene Expression, Extracellular Matrix Production, and Drug Sensitivity in NSCLC Spheroids Generated by Scaffold-Free and Scaffold-Based Methods

EMMPRIN promotes spheroid organization and metastatic formation: comparison between monolayers and spheroids of CT26 colon carcinoma cells

Background

In vitro studies often use two-dimensional (2D) monolayers, but 3D cell organization, such as in spheroids, better mimics the complexity of solid tumors. To metastasize, cancer cells undergo the process of epithelial-to-mesenchymal transition (EMT) to become more invasive and pro-angiogenic, with expression of both epithelial and mesenchymal markers.

Aims

We asked whether EMMPRIN/CD147 contributes to the formation of the 3D spheroid structure, and whether spheroids, which are often used to study proliferation and drug resistance, could better model the EMT process and the metastatic properties of cells, and improve our understanding of the role of EMMPRIN in them.

Methods

We used the parental mouse CT26 colon carcinoma (CT26-WT) cells, and infected them with a lentivirus vector to knock down EMMPRIN expression (CT26-KD cells), or with an empty lentivirus vector (CT26-NC) that served as a negative control. In some cases, we repeated the experiments with the 4T1 or LLC cell lines. We compared the magnitude of change between CT26-KD and CT26-WT/NC cells in different metastatic properties in cells seeded as monolayers or as spheroids formed by the scaffold-free liquid overlay method.

Results

We show that reduced EMMPRIN expression changed the morphology of cells and their spatial organization in both 2D and 3D models. The 3D models more clearly demonstrated how reduced EMMPRIN expression inhibited proliferation and the angiogenic potential, while it enhanced drug resistance, invasiveness, and EMT status, and moreover it enhanced cell dormancy and prevented CT26-KD cells from forming metastatic-like lesions when seeded on basement membrane extract (BME). Most interestingly, this approach enabled us to identify that EMMPRIN and miR-146a-5p form a negative feedback loop, thus identifying a key mechanism for EMMPRIN activities. These results underline EMMPRIN role as a gatekeeper that prevents dormancy, and suggest that EMMPRIN links EMT characteristics to the process of spheroid formation.

Conclusions

Thus, 3D models can help identify mechanisms by which EMMPRIN facilitates tumor and metastasis progression, which might render EMMPRIN as a promising target for anti-metastatic tumor therapy.

PPP2R1B abolishes colorectal cancer liver metastasis and sensitizes Oxaliplatin by inhibiting MAPK/ERK signaling pathway

BACKGROUND

Patients with colorectal cancer (CRC) with liver metastasis or drug resistance have a poor prognosis. Previous research has demonstrated that PPP2R1B inactivation results in the development of CRC. However, the role of PPP2R1B in CRC metastasis and drug resistance is unclear.

METHODS

Venny 2.1 was used to determine the intersection between survival-related differentially expressed genes (DEGs) and liver metastasis-related DEGs according to RNA-seq data from The Cancer Genome Atlas (TCGA) and the GEO database (GSE179979). LC‒MS/MS and coimmunoprecipitation were performed to predict and verify the substrate protein of PPP2R1B. Gene Set Variation Analysis (GSVA) was subsequently utilized to assess pathway enrichment levels. The predictive performance of PPP2R1B was assessed by regression analysis, Kaplan-Meier (KM) survival analysis and drug sensitivity analysis. Immunohistochemistry (IHC), qRT-PCR and western blotting were performed to measure the expression levels of related mRNAs or proteins. Biological features were evaluated by wound healing, cell migration and invasion assays and CCK-8 assays. A mouse spleen infection liver metastasis model was generated to confirm the role of PPP2R1B in the progression of liver metastasis in vivo.

RESULTS

According to bioinformatics analysis, PPP2R1B is significantly associated with liver metastasis and survival in CRC patients, and these findings were further verified via immunohistochemistry (IHC), qPCR and Western blotting. Pathway enrichment and LC‒MS/MS analysis revealed that PPP2R1B is negatively associated with the MAPK/ERK signalling pathway. Additionally, PD98059, a MAPK/ERK pathway inhibitor, inhibited EMT in vitro by reversing the changes in key proteins involved in EMT signalling (ZEB1, E-cadherin and Snail) and ERK/MAPK signalling (p-ERK) mediated by PPP2R1B. Oxaliplatin sensitivity prediction and validation revealed that PPP2R1B silencing decreased Oxaliplatin chemosensitivity, and these effects were reversed by PD98059 treatment. Moreover, PPP2R1B was coimmunoprecipitated with p-ERK in vitro. A negative correlation between PPP2R1B and p-ERK expression was also observed in clinical CRC samples, and the low PPP2R1B/high p-ERK coexpression pattern indicated a poor prognosis in CRC patients. In vivo, PPP2R1B silencing significantly promoted liver metastasis.

CONCLUSIONS

This study revealed that PPP2R1B induces dephosphorylation of the p-ERK protein, inhibits liver metastasis and increases Oxaliplatin sensitivity in CRC patients and could be a potential candidate for therapeutic application in CRC.

Interstitial flow potentiates TGF-β/Smad-signaling activity in lung cancer spheroids in a 3D-microfluidic chip

Within the tumor microenvironment (TME), cancer cells use mechanotransduction pathways to convert biophysical forces to biochemical signals. However, the underlying mechanisms and functional significance of these pathways remain largely unclear. The upregulation of mechanosensitive pathways from biophysical forces such as interstitial flow (IF), leads to the activation of various cytokines, including transforming growth factor-β (TGF-β). TGF-β promotes in part via a Smad-dependent signaling pathway the epithelial-mesenchymal transition (EMT) in cancer cells. The latter process is linked to increased cancer cell motility and invasion. Current research models have limited ability to investigate the combined effects of biophysical forces (such as IF) and cytokines (TGF-β) in a 3D microenvironment. We used a 3D-matrix based microfluidic platform to demonstrate the potentiating effect of IF on exogenous TGF-β induced upregulation of the Smad-signaling activity and the expression of mesenchymal marker vimentin in A549 lung cancer spheroids. To monitor this, we used stably integrated fluorescent based reporters into the A549 cancer cell genome. Our results demonstrate that IF enhances exogenous TGF-β induced Smad-signaling activity in lung cancer spheroids embedded in a matrix microenvironment. In addition, we observed an increased cell motility for A549 spheroids when exposed to IF and TGF-β. Our 3D-microfluidic model integrated with real-time imaging provides a powerful tool for investigating cancer cell signaling and motility associated with invasion characteristics in a physiologically relevant TME.

Mathematical Modeling of Non-Small-Cell Lung Cancer Biology through the Experimental Data on Cell Composition and Growth of Patient-Derived Organoids

Mathematical models of non-small-cell lung cancer are powerful tools that use clinical and experimental data to describe various aspects of tumorigenesis. The developed algorithms capture phenotypic changes in the tumor and predict changes in tumor behavior, drug resistance, and clinical outcomes of anti-cancer therapy. The aim of this study was to propose a mathematical model that predicts the changes in the cellular composition of patient-derived tumor organoids over time with a perspective of translation of these results to the parental tumor, and therefore to possible clinical course and outcomes for the patient. Using the data on specific biomarkers of cancer cells (PD-L1), tumor-associated macrophages (CD206), natural killer cells (CD8), and fibroblasts (αSMA) as input, we proposed a model that accurately predicts the cellular composition of patient-derived tumor organoids at a desired time point. Combining the obtained results with "omics" approaches will improve our understanding of the nature of non-small-cell lung cancer. Moreover, their implementation into clinical practice will facilitate a decision-making process on treatment strategy and develop a new personalized approach in anti-cancer therapy.