Spherical, multicellular aggregates of tumor cells, or three-dimensional (3D) tumor models, can be grown from established cell lines or dissociated cells from tissues in a serum-free medium containing appropriate growth factors. Air–liquid interfaces (ALIs) represent a 3D approach that mimics and supports the differentiation of respiratory tract and skin 3D models in vitro. Many 3D tumor cell models are cultured in conjunction with supporting cell types, such as fibroblasts, endothelial cells, or immune cells. To further mimic the in vivo situation, several extracellular matrix models are utilized to support tumor cell growth. Scaffolds used for 3D tumor cell culture growth include both natural and synthetic hydrogels. Three-dimensional cell culture experiments in vitro provide more accurate data on cell-to-cell interactions, tumor characteristics, drug discovery, metabolic profiling, stem cell research, and diseases. Moreover, 3D models are important for obtaining reliable precision data on therapeutic candidates in human clinical trials before predicting drug cytotoxicity. This review focuses on the recent literature on three different tissue types of 3D tumor models, i.e., tumors from a colorectal site, prostate, and skin. We will discuss the establishment of 3D tumor cell cultures in vitro and the requirement for additional growth support.

In vitro cultured 3D models of CRC have been demonstrated to hold considerable worth in drug discovery, drug resistance analysis, and in studying cell-cell and cell-matrix interactions that occur in the tumor microenvironment. The 3D models resemble the in vivo physiological microenvironment by replicating the cell type composition and tissue architecture. Molecularly imprinted polymers (MIPs) have been investigated for use instead of antibodies against small non-immunogenic structures, such as sialic acid (SA). Glyco-conjugates including SA are present on all cells, and often deregulated on cancer cells. Here, we present a novel approach for targeting and detecting colorectal cancer cells (CRC) by using in vitro cultured HT29 3D spheroids co-cultured in vitro with either fluorescent MIPs targeting SA, SA-MIPs, or the two lectins targeting SA, MAL I, and SNA. Both formaldehyde-fixed and viable HT29 3D spheroids with or without SA-MIPs were imaged in 3D by confocal microscopy. The results revealed a preserved cell morphology and viability of the HT29 3D spheroids co-cultured in vitro with SA-MIPs. However, the lectins MAL I and SNA targeting the a-2,3 or a-2,6 SA glycosidic linkages, respectively, affected the cell viability when co-cultured with the viable HT29 3D spheroids, and no living cells could be detected. Here, we have shown that the SA-MIPs could be used as a safe and low-cost diagnostic tool for targeting and detecting cancer cells in a physiologically relevant 3D cancer model in vitro.

BACKGROUND AND OBJECTIVES: L was investigated both in normal and malignant skin cells.

METHODS: Antioxidant activity of the extracts was analyzed by using the Trolox Equivalent Antioxidant Capacity (TEAC) assay. High-Performance Thin-Layer Chromatography (HPTLC) was performed to demonstrate the phytochemical profile, and the total flavonoid content was analyzed with an aluminum chloride colorimetric method. The anti-inflammatory effect was investigated by cell treatments using the plant extracts. Thereafter, the possible suppression of induced IL-6 response was measured from the cultured skin cancer cell lines A2058 and A431, and normal primary keratinocytes with Enzyme-Linked Immunosorbent Assay (ELISA).

RESULTS: also had the highest flavonoid content and showed the highest antioxidant activity of the three extracts tested.

CONCLUSION: possess properties such as antioxidant and anti-inflammatory activities in both normal and malignant keratinocytes, and thus could be a promising agent controlling the pro-inflammatory IL-6 production.

Molecularly imprinted polymers (MIPs) and the imprinting technique provide polymeric material with recognition elements similar to natural antibodies. The template of choice (i.e., the antigen) can be almost any type of smaller or larger molecule, protein, or even tissue. There are various formats of MIPs developed for different medical purposes, such as targeting, imaging, assay diagnostics, and biomarker detection. Biologically applied MIPs are widely used and currently developed for medical applications, and targeting the antigen with MIPs can also help in personalized medicine. The synthetic recognition sites of the MIPs can be tailor-made to function as analytics, diagnostics, and drug delivery systems. This review will cover the promising clinical applications of different MIP systems recently developed for disease diagnosis and treatment.

Colorectal cancer (CRC) is the second most metastatic disease with the majority of cases detected in Western countries. Metastases are formed by circulating altered phenotype tumor cells causing 20% of CRC related deaths. Metastatic cells may show higher expression of surface molecules such as CD44, and changes in morphological properties are associated with increased invasiveness and poor prognosis. In this study, we intended to mimic the environment for metastasizing cells. Here, we used digital holographic cytometry (DHC) analysis to determine cellular morphological properties of three metastatic and two non-metastatic colorectal cancer cell lines to show differences in morphology between the CRC cells and peripheral blood mononuclear cells (PBMCs). By establishing differences in cell area, cell thickness, cell volume, and cell irregularity even when the CRC cells were in minority (5% out of PBMCs), DHC does discriminate between CRC cells and the PBMCs in vitro. We also analyzed the epithelial marker EpCAM and migration marker CD44 using flow cytometry and demonstrate that the CRC cell lines and PBMC cells differ in EpCAM and CD44 expression. Here, we present DHC as a new powerful tool in discriminating cells of different sizes in suspension together with a combination of biomarkers.

Low affinity immunoglobulin gamma Fc region receptor III-A (FcγRIIIa) is a cell surface protein that belongs to a family of Fc receptors that facilitate the protective function of the immune system against pathogens. However, the role of FcγRIIIa in prostate cancer (PCa) progression remained unknown. In this study, we found that FcγRIIIa expression was present in PCa cells and its level was significantly higher in metastatic lesions than in primary tumors from the PCa cohort (p=0.006). PCa patients with an elevated level of FcγRIIIa expression had poorer biochemical recurrence (BCR)-free survival compared with those with lower FcγRIIIa expression, suggesting that FcγRIIIa is of clinical importance in PCa. We demonstrated that overexpression of FcγRIIIa increased the proliferative ability of PCa cell line C4-2 cells, which was accompanied by the upregulation of androgen receptor (AR) and phosphatidylinositol-4-phosphate 5-kinase alpha (PIP5Kα), which are the key players in controlling PCa progression. Conversely, targeted inhibition of FcγRIIIa via siRNA-mediated knockdown or using its inhibitory antibody suppressed growth of xenograft PC-3 and PC-3M prostate tumors and reduced distant metastasis in xenograft mouse models. We further showed that elevated expression of AR enhanced FcγRIIIa expression, whereas inhibition of AR activity using enzalutamide led to a significant downregulation of FcγRIIIa protein expression. Similarly, inhibition of PIP5K1α decreased FcγRIIIa expression in PCa cells. FcγRIIIa physically interacted with PIP5K1α and AR via formation of protein-protein complexes, suggesting that FcγRIIIa is functionally associated with AR and PIP5K1α in PCa cells. Our study identified FcγRIIIa as an important factor in promoting PCa growth and invasion. Further, the elevated activation of FcγRIII and AR and PIP5K1α pathways may cooperatively promote PCa growth and invasion. Thus, FcγRIIIa may serve as a potential new target for improved treatment of metastatic and castration-resistant PCa.

Sialic acid (SA) is a monosaccharide usually linked to the terminus of glycan chains on the cell surface. It plays a crucial role in many biological processes, and hypersialylation is a common feature in cancer. Lectins are widely used to analyze the cell surface expression of SA. However, these protein molecules are usually expensive and easily denatured, which calls for the development of alternative glycan-specific receptors and cell imaging technologies. In this study, SA-imprinted fluorescent core-shell molecularly imprinted polymer particles (SA-MIPs) were employed to recognize SA on the cell surface of cancer cell lines. The SA-MIPs improved suspensibility and scattering properties compared with previously used core-shell SA-MIPs. Although SA-imprinting was performed using SA without preference for the α2,3- and α2,6-SA forms, we screened the cancer cell lines analyzed using the lectins Maackia Amurensis Lectin I (MAL I, α2,3-SA) and Sambucus Nigra Lectin (SNA, α2,6-SA). Our results show that the selected cancer cell lines in this study presented a varied binding behavior with the SA-MIPs. The binding pattern of the lectins was also demonstrated. Moreover, two different pentavalent SA conjugates were used to inhibit the binding of the SA-MIPs to breast, skin, and lung cancer cell lines, demonstrating the specificity of the SA-MIPs in both flow cytometry and confocal fluorescence microscopy. We concluded that the synthesized SA-MIPs might be a powerful future tool in the diagnostic analysis of various cancer cells.

Purpose: Despite the high mortality of metastatic colorectal cancer (mCRC), no new biomarker tools are available for predicting treatment response. We developed gene-mutation-based algorithms as a biomarker classifier to predict treatment response with better precision than the current predictive factors.

Methods: Random forest machine learning (ML) was applied to identify the candidate algorithms using the MSK Cohort (n = 471) as a training set and validated in the TCGA Cohort (n = 221). Logistic regression, progression-free survival (PFS), and univariate/multivariate Cox proportional hazard analyses were performed and the performance of the candidate algorithms was compared with the established risk parameters.

Results: A novel 7-Gene Algorithm based on mutation profiles of seven KRAS-associated genes was identified. The algorithm was able to distinguish non-progressed (responder) vs. progressed (non-responder) patients with AUC of 0.97 and had predictive power for PFS with a hazard ratio (HR) of 16.9 (p < 0.001) in the MSK cohort. The predictive power of this algorithm for PFS was more pronounced in mCRC (HR = 16.9, p < 0.001, n = 388). Similarly, in the TCGA validation cohort, the algorithm had AUC of 0.98 and a significant predictive power for PFS (p < 0.001).

Conclusion: The novel 7-Gene Algorithm can be further developed as a biomarker model for prediction of treatment response in mCRC patients to improve personalized therapies.Keywords: KRAS; algorithm; colorectal cancer biomarkers; colorectal cancer metastasis; colorectal cancer progression; gene mutations.

PURPOSE: There is an urgent need for developing new biomarker tools to accurately predict treatment response of breast cancer, especially the deadly triple-negative breast cancer. We aimed to develop gene-mutation-based machine learning (ML) algorithms as biomarker classifiers to predict treatment response of first-line chemotherapy with high precision.

METHODS: = 807) with up to 220 months follow-up. Subtypes of breast cancer including triple-negative and luminal A (ER+, PR+ and HER2-) were also assessed. The predictive performance of the candidate algorithms as classifiers was further assessed using logistic regression, Kaplan-Meier progression-free survival (PFS) plot, and univariate/multivariate Cox proportional hazard regression analyses.

RESULTS: < 0.0001).

CONCLUSIONS: The novel 12-Gene algorithm based on multitude gene-mutation profiles identified through ML has a potential to predict breast cancer treatment response to therapies, especially in triple-negative subgroups patients, which may assist personalized therapies and reduce mortality.

Molecularly imprinted polymers (MIPs) against sialic acid (SA) have been developed as a detection tool to target cancer cells. Before proceeding to in vivo studies, a better knowledge of the overall effects of MIPs on the innate immune system is needed. The aim of this study thus was to exemplarily assess whether SA-MIPs lead to inflammatory and/or cytotoxic responses when administered to phagocytosing cells in the innate immune system. The response of monocytic/macrophage cell lines to two different reference particles, Alhydrogel and PLGA, was compared to their response to SA-MIPs. In vitro culture showed a cellular association of SA-MIPs and Alhydrogel, as analyzed by flow cytometry. The reference particle Alhydrogel induced secretion of IL-1β from the monocytic cell line THP-1, whereas almost no secretion was provoked for SA-MIPs. A reduced number of both THP-1 and RAW 264.7 cells were observed after incubation with SA-MIPs and this was not caused by cytotoxicity. Digital holographic cytometry showed that SA-MIP treatment affected cell division, with much fewer cells dividing. Thus, the reduced number of cells after SA-MIP treatment was not linked to SA-MIPs cytotoxicity. In conclusion, SA-MIPs have a low degree of inflammatory properties, are not cytotoxic, and can be applicable for future in vivo studies.