Quantification of multiple steroid hormones in serum and human breast cancer tissue by liquid chromatography-tandem mass spectrometry analysis.

Introduction: Systemic and local steroid hormone levels may function as novel prognostic and predictive biomarkers in breast cancer patients. We aimed at developing a novel liquid chromatography-tandem mass spectrometry (LC-MS/MS) method for the simultaneous measurement of multiple, biologically pivotal steroid hormones in human serum and breast cancer tissue. Methods: The quantitative method consisted of liquid-liquid extraction, Sephadex LH-20 chromatography for tissue extracts, and analysis of steroid hormones by liquid-chromatography-tandem mass spectrometry. We analyzed serum and tissue steroid hormone levels in 16 and 40 breast cancer patients, respectively, and assessed their correlations with clinical parameters. Results: The method included quantification of nine steroid hormones in serum [including cortisol, cortisone, corticosterone, estrone (E1), 17ß-estradiol (E2), 17α-hydroxyprogesterone, androstenedione (A4), testosterone and progesterone) and six (including cortisone, corticosterone, E1, E2, A4, and testosterone) in cancer tissue. The lower limits of quantification were between 0.003-10 ng/ml for serum (250 µl) and 0.038-125 pg/mg for tissue (20 mg), respectively. Accuracy was between 98%-126%, intra-assay coefficient of variations (CV) was below 15%, and inter-assay CV were below 11%. The analytical recoveries for tissue were between 76%-110%. Tissue levels of E1 were positively correlated with tissue E2 levels (p<0.001), and with serum levels of E1, E2 and A4 (p<0.01). Tissue E2 levels were positively associated with serum E1 levels (p=0.02), but not with serum E2 levels (p=0.12). The levels of tissue E2 and ratios of E1 to A4 levels (an index for aromatase activity) were significantly higher in patients with larger tumors (p=0.03 and p=0.02, respectively). Conclusions: The method was convenient and suitable for a specific and accurate profiling of clinically important steroid hormones in serum. However, the sensitivity of the profile method in steroid analysis in tissue samples is limited, but it can be used for the analysis of steroids in breast cancer tissues if the size of the sample or its steroid content is sufficient.

Highly Sensitive Detection of Hydrogen Peroxide in Cancer Tissue Based on 3D Reduced Graphene Oxide-MXene-Multi-Walled Carbon Nanotubes Electrode.

Hydrogen peroxide (H2O2) is a signaling molecule that has the capacity to control a variety of biological processes in organisms. Cancer cells release more H2O2 during abnormal tumor growth. There has been a considerable amount of interest in utilizing H2O2 as a biomarker for the diagnosis of cancer tissue. In this study, an electrochemical sensor for H2O2 was constructed based on 3D reduced graphene oxide (rGO), MXene (Ti3C2), and multi-walled carbon nanotubes (MWCNTs) composite. Three-dimensional (3D) rGO-Ti3C2-MWCNTs sensor showed good linearity for H2O2 in the ranges of 1-60 µM and 60 µM-9.77 mM at a working potential of -0.25 V, with sensitivities of 235.2 µA mM-1 cm-2 and 103.8 µA mM-1 cm-2, respectively, and a detection limit of 0.3 µM (S/N = 3). The sensor exhibited long-term stability, good repeatability, and outstanding immunity to interference. In addition, the modified electrode was employed to detect real-time H2O2 release from cancer cells and cancer tissue ex vivo.

Cellular memory function from 3D to 2D: Three-dimensional high density collagen microfiber cultures induce their resistance to reactive oxygen species.

Cell properties generally change when the culture condition is changed. However, mesenchymal stem cells cultured on a hard material surface maintain their differentiation characteristics even after being cultured on a soft material surface. This phenomenon suggests the possibility of a cell culture material to memorize stem cell function even in changing cell culture conditions. However, there are no reports about cell memory function in three-dimensional (3D) culture. In this study, colon cancer cells were cultured with collagen microfibers (CMF) in 3D to evaluate their resistance to reactive oxygen species (ROS) in comparison with a monolayer (2D) culture condition and to understand the effect of 3D-culture on cell memory function. The ratio of ROS-negative cancer cells in 3D culture increased with increasing amounts of CMF and the highest amount of CMF was revealed to be 35-fold higher than that of the 2D condition. The ROS-negative cells ratio was maintained for 7 days after re-seeding in a 2D culture condition, suggesting a 3D-memory function of ROS resistance. The findings of this study will open up new opportunities for 3D culture to induce cell memory function.

Bimetal-organic framework-integrated electrochemical sensor for on-chip detection of H2S and H2O2 in cancer tissues.

Studies on the interaction between hydrogen sulfide (H2S) and hydrogen peroxide (H2O2) in redox signaling motivate the development of a sensitive sensing platform for their discriminatory and dynamic detection. Herein, we present a fully integrated microfluidic on-chip electrochemical sensor for the online and simultaneous monitoring of H2S and H2O2 secreted by different biological samples. The sensor utilizes a cicada-wing-like RuCu bimetal-organic framework with uniform nanorods architecture that grows on a flexible carbon fiber microelectrode. Owing to the optimized electronic structural merits and satisfactory electrocatalytic properties, the resultant microelectrode shows remarkable electrochemical sensing performance for sensitive and selective detection of H2S and H2O2 at the same time. The result exhibits low detection limits of 0.5 µM for H2S and 0.1 µM for H2O2, with high sensitivities of 61.93 µA cm-2 mM-1 for H2S, and 75.96 µA cm-2 mM-1 for H2O2. The integration of this biocompatible microelectrode into a custom wireless microfluidic chip enables the construction of a miniature intelligent system for in situ monitoring of H2S and H2O2 released from different living cells to differentiate between cancerous and normal cells. When applied for real-time tracking of H2S and H2O2 secreted by colorectal cancer tissues, it allows the evaluation of their chemotherapeutic efficacy. These findings hold paramount implications for disease diagnosis and therapy.

Spectroscopic diagnosis and metabolite characterization of cisplatin resistance regulated by FDFT1 in bladder cancer tissue.

As is the case for most solid tumours, chemotherapy remains the backbone in the management of metastatic disease. However, the occurrence of chemotherapy resistance is a cause to worry, especially in bladder cancer. Extensive evidence indicates molecular changes in bladder cancer cells to be the underlying cause of chemotherapy resistance, including the reduced expression of farnesyl-diphosphate farnesyltransferase 1 (FDFT1) - a gene involved in cholesterol biosynthesis. This can likely be a hallmark in examining the resistance and sensitivity of chemotherapy drugs. This work performs spectroscopic analysis and metabolite characterization on resistant, sensitive, stable-disease and healthy bladder tissues. Raman spectroscopy has detected peaks at around 1003 cm-1 (squalene), 1178 cm-1 (cholesterol), 1258 cm-1 (cholesteryl ester), 1343 cm-1 (collagen), 1525 cm-1 (carotenoid), 1575 cm-1 (DNA bases) and 1608 cm-1 (cytosine). The peak parameters were examined, and statistical analysis was performed on the peak features, attaining significant differences between the sample groups. Small-angle x-ray scattering (SAXS) measurements observed the triglyceride peak together with 6th, 7th and 8th - order collagen peaks; peak parameters were also determined. Neutron activation analysis (NAA) detected seven trace elements. Carbon (Ca), magnesium (Mg), chlorine (Cl) and sodium (Na) have been found to have the greatest concentration in the sample groups, suggestive of a role as a biomarker for cisplatin resistance studies. Results from the present research are suggested to provide an important insight into understanding the development of drug resistance in bladder cancer, opening up the possibility of novel avenues for treatment through personalised interventions.

DeepDecon accurately estimates cancer cell fractions in bulk RNA-seq data.

Understanding the cellular composition of a disease-related tissue is important in disease diagnosis, prognosis, and downstream treatment. Recent advances in single-cell RNA-sequencing (scRNA-seq) technique have allowed the measurement of gene expression profiles for individual cells. However, scRNA-seq is still too expensive to be used for large-scale population studies, and bulk RNA-seq is still widely used in such situations. An essential challenge is to deconvolve cellular composition for bulk RNA-seq data based on scRNA-seq data. Here, we present DeepDecon, a deep neural network model that leverages single-cell gene expression information to accurately predict the fraction of cancer cells in bulk tissues. It provides a refining strategy in which the cancer cell fraction is iteratively estimated by a set of trained models. When applied to simulated and real cancer data, DeepDecon exhibits superior performance compared to existing decomposition methods in terms of accuracy.

Macro-indentation testing of soft biological materials and assessment of hyper-elastic material models from inverse finite element analysis.

Mechanical characterization of hydrogels and ultra-soft tissues is a challenging task both from an experimental and material parameter estimation perspective because they are much softer than many biological materials, ceramics, or polymers. The elastic modulus of such materials is within the 1 - 100 kPa range, behaving as a hyperelastic solid with strain hardening capability at large strains. In the current study, indentation experiments have been performed on agarose hydrogels, bovine liver, and bovine lymph node specimens. This work reports on the reliable determination of the elastic modulus by indentation experiments carried out at the macro-scale (mm) using a spherical indenter. However, parameter identification of the hyperelastic material properties usually requires an inverse finite element analysis due to the lack of an analytical contact model of the indentation test. Hence a comprehensive study on the spherical indentation of hyperelastic soft materials is carried out through robust computational analysis. Neo-Hookean and first-order Ogden hyperelastic material models were found to be most suitable. A case study on known anisotropic hyperelastic material showed the inability of the inverse finite element method to uniquely identify the whole material parameter set.

Establishment of a tissue-engineered colon cancer model for comparative analysis of cancer cell lines.

To overcome the limitations of in vitro two-dimensional (2D) cancer models in mimicking the complexities of the native tumor milieu, three-dimensional (3D) engineered cancer models using biomimetic materials have been introduced to more closely recapitulate the key attributes of the tumor microenvironment. Specifically, for colorectal cancer (CRC), a few studies have developed 3D engineered tumor models to investigate cell-cell interactions or efficacy of anti-cancer drugs. However, recapitulation of CRC cell line phenotypic differences within a 3D engineered matrix has not been systematically investigated. Here, we developed an in vitro 3D engineered CRC (3D-eCRC) tissue model using the natural-synthetic hybrid biomaterial PEG-fibrinogen and three CRC cell lines, HCT 116, HT-29, and SW480. To better recapitulate native tumor conditions, our 3D-eCRC model supported higher cell density encapsulation (20 × 106 cells/mL) and enabled longer term maintenance (29 days) as compared to previously reported in vitro CRC models. The 3D-eCRCs formed using each cell line demonstrated line-dependent differences in cellular and tissue properties, including cellular growth and morphology, cell subpopulations, cell size, cell granularity, migration patterns, tissue growth, gene expression, and tissue stiffness. Importantly, these differences were found to be most prominent from Day 22 to Day 29, thereby indicating the importance of long-term culture of engineered CRC tissues for recapitulation and investigation of mechanistic differences and drug response. Our 3D-eCRC tissue model showed high potential for supporting future in vitro comparative studies of disease progression, metastatic mechanisms, and anti-cancer drug candidate response in a CRC cell line-dependent manner.

Relationship between the Ubiquitin-Proteasome System and Autophagy in Colorectal Cancer Tissue.

BACKGROUND: Dysregulation of the autophagy process via ubiquitin is associated with the occurrence of a number of diseases, including cancer. The present study analyzed the changes in the transcriptional activity of autophagy-related genes and the ubiquitination process (UPS) in colorectal cancer tissue. (2) Methods: The process of measuring the transcriptional activity of autophagy-related genes was analyzed by comparing colorectal cancer samples from four clinical stages I-IV (CS I-IV) of adenocarcinoma to the control (C). The transcriptional activity of genes associated with the UPS pathway was determined via the microarray technique (HG-U133A, Affymetrix). (3) Results: Of the selected genes, only PTEN-induced kinase 1 (PINK1) indicated statistical significance for all groups of colon cancer tissue transcriptome compared to the control. The transcriptional activity of the protein tyrosine phosphatase non-receptor type 22 (PTPN22) gene increased in all stages of the cancer, but the p-value was only less than 0.05 in CSIV vs. C. Forkhead box O1 (FOXO 1) and ubiquitin B (UBB) are statistically overexpressed in CSI. (4) Conclusions: The pathological expression changes in the studied proteins observed especially in the early stages of colorectal cancer suggest that the dysregulation of ubiquitination and autophagy processes occur during early neoplastic transformation. Stopping or slowing down the processes of removal of damaged proteins and their accumulation may contribute to tumor progression and poor prognosis.

Colorectal cancer tissue-originated spheroids reveal tumor intrinsic signaling pathways and mimic patient clinical chemotherapeutic response as a rapid and valid model.

Locally advanced colorectal cancer requires preoperative chemotherapy to reduce local recurrence and metastasis rates, but it remains difficult to predict the tumor will be sensitive to which treatments. The patient-derived organoids (PDOs) are considered an effective platform for predicting tumor drug responses in precision oncology. However, it has the limitation of being time-consuming in practical applications, especially in neoadjuvant treatment. Here we used cancer tissue-originated spheroids (CTOS) method to establish organoids from a heterogeneous population of colorectal cancer specimens, and evaluated the capacity of CTOS to predict clinical drug responses. By analyzing the relationship of the activities of drug-treated CTOS, drug targets and target-related pathways, tumor intrinsic effective-target-related pathways can be identified. These pathways were highly matched to the abnormal pathways indicated by whole-exome sequencing. Based on this, we used half effective concentration gradients to classify CTOS as sensitive or resistant to chemotherapy regimens within a week, for predicting neoadjuvant treatment outcomes for colorectal cancer patients. The drug sensitivity test results are highly matched to the clinical responses to treatment in individual patients. Thus, our data suggested that CTOS models can be effectively screened ex vivo to identify pathways sensitive to chemotherapies. These data also supported organoid research for personalized clinical medication guidance immediately after diagnosis in patients with advanced colorectal cancer.

Oral tongue squamous cell carcinoma diagnosis from tissue metabolic profiling.

OBJECTIVE: Disease metabolomes have been studied for identifying diagnostic and predictive biomarkers of pathology. Oral tongue squamous cell carcinoma (OTSCC) is one of the most prevalent subtypes of head and neck squamous cell carcinoma, yet the profile and diagnostic value of its tissue metabolite are unclear. SUBJECTS AND METHODS: Tumor tissue samples and matched normal mucosal tissue samples were collected from 40 OTSCC patients. Untargeted metabolic analysis by liquid chromatography-mass spectrometry/mass spectrometry, in positive and negative ion modes, was used to identify dysregulated metabolites in OTSCC. Further, utilizing LASSO regression and receiver operating characteristic analyses, biomarker metabolites were selected and validated, and a diagnostic model was established. RESULTS: One hundred and ninety metabolites were detected. The OTSCC had a total of 89 dysregulated metabolites, of which 73 were elevated. A diagnostic panel of nine metabolites was subsequently created that could accurately identify OTSCC with 100% sensitivity of 100%, 100% specificity and an AUC of 1.00. CONCLUSIONS: This study identified distinct metabolic characteristics of OTSCC and established a diagnostic model. Our research also contributes to the investigation of the pathogenesis of OTSCC.

Screening differential circular RNA expression profiles and the potential role of hsa_circ_0085465 in liver cancer.

Aims: This study aimed to screen the circular RNAs (circRNAs) that are differentially expressed between liver cancer and paired paracarcinoma tissues and then elucidate their role in cancer progression. Materials and Methods: High-throughput sequencing of cancer and paired paracarcinoma tissues was followed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses of the parental genes of the differentially expressed circRNAs, which were also verified via real-time quantitative polymerase chain reaction analysis of the tissues. In addition, the function of selected circRNAs was determined using 3-(4,5-dimethylthiazol-2-yl)-5-(3-carboxymethoxyphenyl)-2-(4- sulfophenyl)-2H-tetrazolium (MTS) and transwell assays. Results: Total 218 and 121 circRNAs were differentially upregulated and downregulated, respectively; these were mainly enriched with GO and KEGG terms related to biological functions. From five representatives of the differentially expressed circRNAs, we selected hsa_circ_0085465 for further analysis, discovering that its overexpression promoted the proliferation, migration, and invasion of 97 L cells. Conclusion: Taken together, our results suggest that hsa_circ_0085465 is relevant to liver cancer progression.

[Retracted] Increased resistin suggests poor prognosis and promotes development of lung adenocarcinoma.

Following the publication of this paper, it was drawn to the Editor's attention by a concerned reader that the colony formation assay data shown in Fig. 3A on p. 3399 were strikingly similar to data that were already under consideration for publication in another article written by different authors at different research institutes. Owing to the fact that the contentious data in the above article were already under consideration for publication prior to its submission to Oncology Reports, the Editor has decided that this paper should be retracted from the Journal. The authors were asked for an explanation to account for these concerns, but the Editorial Office did not receive a satisfactory reply. The Editor apologizes to the readership for any inconvenience caused. [Oncology Reports 40: 3392­3404, 2018; DOI: 10.3892/or.2018.6736].

Emerging technology for intraoperative margin assessment and post-operative tissue diagnosis for breast-conserving surgery.

INTRODUCTION: Tissue-preserving surgery is utilized progressively in cancer therapy, where a clear surgical margin is critical to avoid cancer recurrence, specifically in breast cancer (BC) surgery. The Intraoperative pathologic approaches that rely on tissue segmenting and staining have been recognized as the ground truth for BC diagnosis. Nevertheless, these methods are constrained by its complication and timewasting for tissue preparation. OBJECTIVE: We present a non-invasive optical imaging system incorporating a hyperspectral (HS) camera to discriminate between cancerous and non-cancerous tissues in ex-vivo breast specimens, which could be an intraoperative diagnostic technique to aid surgeons during surgery and later a valuable tool to assist pathologists. METHODS: We have established a hyperspectral Imaging (HSI) system comprising a push-broom HS camera at wavelength 380∼1050 nm with source light 390∼980 nm. We have measured the investigated samples' diffuse reflectance (Rd), fixed on slides from 30 distinct patients incorporating mutually normal and ductal carcinoma tissue. The samples were divided into two groups, stained tissues during the surgery (control group) and unstained samples (test group), both captured with the HSI system in the visible and near-infrared (VIS-NIR) range. Then, to address the problem of the spectral nonuniformity of the illumination device and the influence of the dark current, the radiance data were normalized to yield the radiance of the specimen and neutralize the intensity effect to focus on the spectral reflectance shift for each tissue. The selection of the threshold window from the measured Rd is carried out by exploiting the statistical analysis by calculating each region's mean and standard deviation. Afterward, we selected the optimum spectral images from the HS data cube to apply a custom K-means algorithm and contour delineation to identify the regular districts from the BC regions. RESULTS: We noticed that the measured spectral Rd for the malignant tissues of the investigated case studies versus the reference source light varies regarding the cancer stage, as sometimes the Rd is higher for the tumor or vice versa for the normal tissue. Later, from the analysis of the whole samples, we found that the most appropriate wavelength for the BC tissues was 447 nm, which was highly reflected versus the normal tissue. However, the most convenient one for the normal tissue was at 545 nm with high reflection versus the BC tissue. Finally, we implement a moving average filter for noise reduction and a custom K-means clustering algorithm on the selected two spectral images (447, 551 nm) to identify the various regions and effectively-identified spectral tissue variations with a sensitivity of 98.95%, and specificity of 98.44%. A pathologist later confirmed these outcomes as the ground truth for the tissue sample investigations. CONCLUSIONS: The proposed system could help the surgeon and the pathologist identify the cancerous tissue margins from the non-cancerous tissue with a non-invasive, rapid, and minimum time method achieving high sensitivity up to 98.95%.

Nanoscale Prognosis of Colorectal Cancer Metastasis from AFM Image Processing of Histological Sections.

Early ascertainment of metastatic tumour phases is crucial to improve cancer survival, formulate an accurate prognostic report of disease advancement, and, most importantly, quantify the metastatic progression and malignancy state of primary cancer cells with a universal numerical indexing system. This work proposes an early improvement to metastatic cancer detection with 97.7 nm spatial resolution by indexing the metastatic cancer phases from the analysis of atomic force microscopy images of human colorectal cancer histological sections. The procedure applies variograms of residuals of Gaussian filtering and theta statistics of colorectal cancer tissue image settings. This methodology elucidates the early metastatic progression at the nanoscale level by setting metastatic indexes and critical thresholds based on relatively large histological sections and categorising the malignancy state of a few suspicious cells not identified with optical image analysis. In addition, we sought to detect early tiny morphological differentiations indicating potential cell transition from epithelial cell phenotypes of low metastatic potential to those of high metastatic potential. This metastatic differentiation, which is also identified in higher moments of variograms, sets different hierarchical levels for metastatic progression dynamics.

Nanoindentation study of the viscoelastic properties of human triple negative breast cancer tissues: Implications for mechanical biomarkers.

This paper presents the results of a combined experimental and theoretical study of the structure and viscoelastic properties of human non-tumorigenic mammary breast tissues and triple negative breast cancer (TNBC) tissues of different histological grades. A combination of immunofluorescence and confocal microscopy, and atomic force microscopy is used to study the actin cytoskeletal structures of non-tumorigenic and tumorigenic breast tissues (grade I to grade III). A combination of nanoindentation and statistical techniques is then used to measure viscoelastic properties of non-tumorigenic and human TNBC of different histological grades. A Standard Fluid Model/Anti-Zener Model II is also used to characterize the viscoelastic properties of the non-tumorigenic and tumorigenic TNBC tissues of different grades. The implications of the results are discussed for the potential application of nanoindentation and statistical deconvolution techniques to the development of mechanical biomarkers for TNBC detection/cancer diagnosis. STATEMENT OF SIGNIFICANCE: There is increasing interest in the development of mechanical biomarkers for cancer diagnosis. Here, we show that nanoindentation techniques can be used to characterize the viscoelastic properties of normal breast tissue and TNBC tissues of different histological grades. The Standard Fluid Model (Anti-Zener Model II) is used to classify the viscoelastic properties of breast tissues of different TNBC histological grades. Our results suggest that breast tissue and TNBC tissue viscoelastic properties can be used as mechanical biomarkers for the detection of TNBC at different stages.

Adhesion of LHRH/EphA2 to human Triple Negative Breast Cancer tissues.

The adhesive interactions between molecular recognition units (such as specific peptides and antibodies) and antigens or other receptors on the surfaces of tumors are of great value in the design of targeted nanoparticles and drugs for the detection and treatment of specific cancers. In this paper, we present the results of a combined experimental and theoretical study of the adhesion between Luteinizing Hormone Releasing Hormone (LHRH)/Epherin type A2 (EphA2)-AFM coated tips and LHRH/EphA2 receptors that are overexpressed on the surfaces of human Triple Negative Breast Cancer (TNBC) tissues of different histological grades. Following a histochemical and immuno-histological study of human tissue extracts, the receptor overexpression, and their distributions are characterized using Immunohistochemistry (IHC), Immunofluorescence (IF), and a combination of fluorescence microscopy and confocal microscopy. The adhesion forces between LHRH or EphA2 and human TNBC breast tissues are measured using force microscopy techniques that account for the potential effects of capillary forces due to the presence of water vapor. The corresponding adhesion energies are also determined using adhesion theory. The pull off forces and adhesion energies associated with higher grades of TNBC are shown to be greater than those associated with normal/non-tumorigenic human breast tissues, which were studied as controls. The observed increase in adhesion forces and adhesion energies are also correlated with the increasing incidence of LHRH/EphA2 receptors at higher grades of TNBC. The implications of the results are discussed for the development of targeted nanostructures for the detection and treatment of TNBC.

Patient-Derived Breast Cancer Tissue Cultures for Anti-Endocrine Drug Assays.

Breast cancer is a complex and heterogeneous pathology, characterized by a variety of histological and molecular phenotypes. The majority of the breast cancers express the estrogen receptor alpha (ER), which plays a pivotal role in the pathobiology of the disease and are therefore classified as ER-positive (ER+). In fact, targeting of the ER signaling pathway is the main therapeutic strategy for ER+ breast cancer. Despite the success of endocrine therapy, intrinsic and acquired resistance are reported in 30-50% of the ER+ breast cancers. However, the mechanisms underlying ER heterogeneity and therapeutic resistance are far from being fully disclosed, and efficacious clinical strategies to overcome resistance are still pending. One of the hurdles in studying ER+ breast cancer resistance is related with the scarcity of experimental models that can recapitulate ER heterogeneity and signaling. This is the case of ER+ breast cancer cell models, typically based on cells derived from metastasis, which also fail to recapitulate tumor complexity. Primary cultures of patient-derived breast cancer cells are difficult to establish, and generally characterized by stromal fibroblasts overgrowth and rapid loss of phenotypic and molecular traits of the tumor cells, including ER expression. Ex vivo cultures of breast cancer tissue have been reported to retain the tissue architecture, with preservation of the tumor microenvironment (TME) and ER expression for short periods of time.Given the cumulating evidence on the role of the TME in sustaining ER+ tumor cells, we hypothesized that TME preservation in culture would favor the long-term retention of ER expression and signaling. We employed alginate encapsulation to provide a supporting scaffold to breast cancer tissue microstructures, coupled to dynamic culture to improve the lifespan of the culture by avoiding diffusional limitations. In this chapter, we provide a detailed description of this culture methodology, which has been previously published by our group (Cartaxo et al., J Exp Clin Cancer Res 39:161, 2020), based on electrostatically driven breast cancer tissue encapsulation in alginate, coupled to culture under agitation in a defined culture medium. We also describe challenge of the ex vivo model with an ER activator and inhibitors (anti-endocrine drugs) and a gene expression endpoint of drug response using reverse transcription PCR-based analysis of three distinct genes downstream of ER.

Engineered colorectal cancer tissue recapitulates key attributes of a patient-derived xenograft tumor line.

The development of physiologically relevantin vitrocolorectal cancer (CRC) models is vital for advancing understanding of tumor biology. Although CRC patient-derived xenografts (PDXs) recapitulate key patient tumor characteristics and demonstrate high concordance with clinical outcomes, the use of thisin vivomodel is costly and low-throughput. Here we report the establishment and in-depth characterization of anin vitrotissue-engineered CRC model using PDX cells. To form the 3D engineered CRC-PDX (3D-eCRC-PDX) tissues, CRC PDX tumors were expandedin vivo, dissociated, and the isolated cells encapsulated within PEG-fibrinogen hydrogels. Following PEG-fibrinogen encapsulation, cells remain viable and proliferate within 3D-eCRC-PDX tissues. Tumor cell subpopulations, including human cancer and mouse stromal cells, are maintained in long-term culture (29 days); cellular subpopulations increase ratiometrically over time. The 3D-eCRC-PDX tissues mimic the mechanical stiffness of originating tumors. Extracellular matrix protein production by cells in the 3D-eCRC-PDX tissues resulted in approximately 57% of proteins observed in the CRC-PDX tumors also being present in the 3D-eCRC-PDX tissues on day 22. Furthermore, we show congruence in enriched gene ontology molecular functions and Hallmark gene sets in 3D-eCRC-PDX tissues and CRC-PDX tumors compared to normal colon tissue, while prognostic Kaplan-Meier plots for overall and relapse free survival did not reveal significant differences between CRC-PDX tumors and 3D-eCRC-PDX tissues. Our results demonstrate high batch-to-batch consistency and strong correlation between ourin vitrotissue-engineered PDX-CRC model and the originatingin vivoPDX tumors, providing a foundation for future studies of disease progression and tumorigenic mechanisms.

An Osteosarcoma Model by 3D Printed Polyurethane Scaffold and In Vitro Generated Bone Extracellular Matrix.

Osteosarcoma is a primary bone tumor characterized by a dismal prognosis, especially in the case of recurrent disease or metastases. Therefore, tools to understand in-depth osteosarcoma progression and ultimately develop new therapeutics are urgently required. 3D in vitro models can provide an optimal option, as they are highly reproducible, yet sufficiently complex, thus reliable alternatives to 2D in vitro and in vivo models. Here, we describe 3D in vitro osteosarcoma models prepared by printing polyurethane (PU) by fused deposition modeling, further enriched with human mesenchymal stromal cell (hMSC)-secreted biomolecules. We printed scaffolds with different morphologies by changing their design (i.e., the distance between printed filaments and printed patterns) to obtain different pore geometry, size, and distribution. The printed PU scaffolds were stable during in vitro cultures, showed adequate porosity (55-67%) and tunable mechanical properties (Young's modulus ranging in 0.5-4.0 MPa), and resulted in cytocompatible. We developed the in vitro model by seeding SAOS-2 cells on the optimal PU scaffold (i.e., 0.7 mm inter-filament distance, 60° pattern), by testing different pre-conditioning factors: none, undifferentiated hMSC-secreted, and osteo-differentiated hMSC-secreted extracellular matrix (ECM), which were obtained by cell lysis before SAOS-2 seeding. Scaffolds pre-cultured with osteo-differentiated hMSCs, subsequently lysed, and seeded with SAOS-2 cells showed optimal colonization, thus disclosing a suitable biomimetic microenvironment for osteosarcoma cells, which can be useful both in tumor biology study and, possibly, treatment.