Paired comparison of the analytical performance between the Oncomine™ Comprehensive Assay v3 and whole-exome sequencing of ovarian cancer tissue.

BACKGROUND: Next-generation sequencing (NGS) has been implemented in clinical oncology as a personalized medicine tool to identify targetable genetic alterations and to guide treatment decisions. However, the optimal NGS test strategy and target genes for clinical use are still being discussed. The aim was to compare the performance of the Oncomine™ Comprehensive Assay v3 (OCAv3) (targeted gene panel) and whole-exome sequencing (WES) to investigate somatic single and multiple nucleotide variants and small indels in ovarian cancer patients. METHODS AND RESULTS: Genomic DNA was isolated from fresh frozen samples of five high-grade serous (HGSC) and three clear cell ovarian (oCCC) cancer patients. Exome sequencing libraries were prepared by using the Ion AmpliSeq Exome RDY kit, whereas libraries for OCAv3 were prepared using by Ion AmpliSeq™ Library Kit Plus. Sequencing was performed using the Ion S5XL System (Thermo Fisher Scientific). When including only variants classified as pathogenic, likely pathogenic or unknown significance based on ClinVar database verdicts and comparing overlapping regions covered both by the OCAv3 assay and WES, 23 variants were detected by both assays. However, OCAv3 detected additionally two variants: ARID1A: p.Gln563Ter and TP53: p.Ser261ValfsTer84 that have not passed WES filtering criteria due to low coverage. CONCLUSIONS: With the present treatment possibilities, OCAv3 panel testing provided higher diagnostic yield due to better coverage. Our study emphasizes that WES, although offering the potential to identify novel findings in genes not covered by OCAv3, might overlook variants in genes relevant for OC.

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.

Tumor cells express pauci- and oligomannosidic N-glycans in glycoproteins recognized by the mannose receptor (CD206).

The macrophage mannose receptor (CD206, MR) is an endocytic lectin receptor which plays an important role in homeostasis and innate immunity, however, the endogenous glycan and glycoprotein ligands recognized by its C-type lectin domains (CTLD) have not been well studied. Here we used the murine MR CTLD4-7 coupled to the Fc-portion of human IgG (MR-Fc) to investigate the MR glycan and glycoprotein recognition. We probed 16 different cancer and control tissues using the MR-Fc, and observed cell- and tissue-specific binding with varying intensity. All cancer tissues and several control tissues exhibited MR-Fc ligands, intracellular and/or surface-located. We further confirmed the presence of ligands on the surface of cancer cells by flow cytometry. To characterize the fine specificity of the MR for glycans, we screened a panel of glycan microarrays. Remarkably, the results indicate that the CTLD4-7 of the MR is highly selective for specific types of pauci- and oligomannose N-glycans among hundreds of glycans tested. As lung cancer tissue and the lung cancer cell line A549 showed intense MR-Fc binding, we further investigated the MR glycoprotein ligands in those cells by immunoprecipitation and glycoproteomic analysis. All enriched glycoproteins, of which 42 were identified, contained pauci- or oligomannose N-glycans, confirming the microarray results. Our study demonstrates that the MR CTLD4-7 is highly selective for pauci- and oligomannosidic N-glycans, structures that are often elevated in tumor cells, and suggest a potential role for the MR in tumor biology.

Better Agreement of Human Transcriptomic and Proteomic Cancer Expression Data at the Molecular Pathway Activation Level.

Previously, we have shown that the aggregation of RNA-level gene expression profiles into quantitative molecular pathway activation metrics results in lesser batch effects and better agreement between different experimental platforms. Here, we investigate whether pathway level of data analysis provides any advantage when comparing transcriptomic and proteomic data. We compare the paired proteomic and transcriptomic gene expression and pathway activation profiles obtained for the same human cancer biosamples in The Cancer Genome Atlas (TCGA) and the NCI Clinical Proteomic Tumor Analysis Consortium (CPTAC) projects, for a total of 755 samples of glioblastoma, breast, liver, lung, ovarian, pancreatic, and uterine cancers. In a CPTAC assay, expression levels of 15,112 protein-coding genes were profiled using the Thermo QE series of mass spectrometers. In TCGA, RNA expression levels of the same genes were obtained using the Illumina HiSeq 4000 engine for the same biosamples. At the gene level, absolute gene expression values are compared, whereas pathway-grade comparisons are made between the pathway activation levels (PALs) calculated using average sample-normalized transcriptomic and proteomic profiles. We observed remarkably different average correlations between the primary RNA- and protein expression data for different cancer types: Spearman Rho between 0.017 (p = 1.7 × 10−13) and 0.27 (p < 2.2 × 10−16). However, at the pathway level we detected overall statistically significantly higher correlations: averaged Rho between 0.022 (p < 2.2 × 10−16) and 0.56 (p < 2.2 × 10−16). Thus, we conclude that data analysis at the PAL-level yields results of a greater similarity when comparing high-throughput RNA and protein expression profiles.

Chemical structure modifications and nano-technology applications for improving ADME-Tox properties, a review.

The chemical structure of a drug molecule affects its physicochemical properties and subsequent biological activities. Many pharmacologically active molecules fail to reach the market or have an inconvenient route of administration due to their chemical structure. This is especially important with the recent tendency to develop drug candidates beyond the drug-likeness space for addressing difficult targets such as protein-protein interfaces. The objective of this review is to discuss chemical and pharmaceutical approaches for circumventing structure-related problems and achieving acceptable ADME-Tox properties. The chemical structure-associated limitations are critically discussed. Chemical modifications and pharmaceutical technology applications for improving drug-likeness are illustrated. Attention is paid to modern therapeutic candidates and targets. In conclusion, chemical modifications as well as nanotechnology applications can be used effectively to enhance absorption, permeability, and selective distribution to a body compartment, to improve drug specificity, to limit off-target toxicity as well as to enhance stability and to protect against metabolism. The nano-technology-based solutions are relatively easier to develop over a new molecular entity, but adopting the chemical approach is more established in terms of safety, quality control, and regulatory assessment methods.

A Bayesian approach to determine the composition of heterogeneous cancer tissue.

BACKGROUND: Cancer Tissue Heterogeneity is an important consideration in cancer research as it can give insights into the causes and progression of cancer. It is known to play a significant role in cancer cell survival, growth and metastasis. Determining the compositional breakup of a heterogeneous cancer tissue can also help address the therapeutic challenges posed by heterogeneity. This necessitates a low cost, scalable algorithm to address the challenge of accurate estimation of the composition of a heterogeneous cancer tissue. METHODS: In this paper, we propose an algorithm to tackle this problem by utilizing the data of accurate, but high cost, single cell line cell-by-cell observation methods in low cost aggregate observation method for heterogeneous cancer cell mixtures to obtain their composition in a Bayesian framework. RESULTS: The algorithm is analyzed and validated using synthetic data and experimental data. The experimental data is obtained from mixtures of three separate human cancer cell lines, HCT116 (Colorectal carcinoma), A2058 (Melanoma) and SW480 (Colorectal carcinoma). CONCLUSION: The algorithm provides a low cost framework to determine the composition of heterogeneous cancer tissue which is a crucial aspect in cancer research.

FAM46C Serves as a Predictor of Hepatic Recurrence in Patients with Resectable Gastric Cancer.

BACKGROUND: Gastric cancer (GC) relapse can occur even if curative resection is achieved. Biomarkers predicting recurrence are needed to provide appropriate postoperative surveillance and perioperative therapeutic strategy. METHODS: A global expression profiling was performed using tissues from GC patients with synchronous liver-confined metastasis. Family with sequence similarity 46, member C (FAM46C), was identified as a candidate biomarker. mRNA expression analysis, direct nucleotide sequencing, bisulfite sequencing and copy number assays for FAM46C were performed with eleven GC cell lines. Expression levels of FAM46C in primary GC tissues from 129 patients who underwent curative GC resection were determined and correlated with clinicopathological factors, including postoperative outcome. RESULTS: Levels of FAM46C mRNA differed among GC cell lines. Point mutations in FAM46C were detected in five GC cell lines accompanied with reduced FAM46C transcription. No hypermethylation was found in the promoter region of FAM46C. Copy number alterations were found in six GC cell lines with differing FAM46C transcription levels. Reduced FAM46C mRNA expression levels were detected in 117 (91 %) GC specimens compared with adjacent noncancerous tissues. Low FAM46C expression levels were significantly associated with larger macroscopic GC tumor sizes. The low FAM46C expression group was likely to have shorter disease-free survival than the high group and low FAM46C level was identified as an independent risk factor for recurrence after curative resection. FAM46C expression levels were low in all cases that were later found to have hepatic recurrence. CONCLUSIONS: Reduced GC expression of FAM46C is a potential biomarker to predict hepatic recurrence after curative gastrectomy.

Limited Clinical Significance of Dimeric Form of Pyruvate Kinase as a Diagnostic and Prognostic Biomarker in Non-small Cell Lung Cancer.

Metabolism of tumor tissue differs from the normal one by the intensity of protein synthesis and glycolysis. The dimeric pyruvate kinase (PKM2) is a specific enzyme for tumor glycolysis. The aim of this study was to determine the relationship between the activity of PKM2 and the type and stage of non-small cell lung cancer (NSCLC). A second objective was to compare the expression of PKM2 with disease progression and prognosis. We studied 65 patients divided into two groups: 45 patients with lung cancer and 20 non-cancer healthy subjects taken as control. The serum activity of PKM2 was assessed spectrophotometrically. We found that PKM2 activity was greater, on average, by 136 % for adenocarcinoma and for 126 % for squamous cell carcinoma compared with that present in control subjects. The higher PKM2 activity was associated only with Stage III of cancer (p < 0.001). Sensitivity of PKM2 as a cancer marker was 79 % for adenocarcinoma and 81 % for squamous cell carcinoma and specificity was 50 % for both cancer types. We conclude that PKM2 activity is higher in patients with NSCLC than in healthy subjects. The level of PKM2 activity is associated with advanced stage of cancer. Nonetheless, low specificity of PKM2 assessment makes it of limited utility in NSCLC diagnosis or evaluation of cancer progression.

Genome-wide mitochondrial DNA sequence variations and lower expression of OXPHOS genes predict mitochondrial dysfunction in oral cancer tissue.

Several studies reported that mtDNA mutations may play important roles in carcinogenesis although the mechanism is not clear yet. Most of the studies compared mtDNA sequences in a tumor with those in normal tissues from different individuals ignoring inter-individual variations. In this study, 271 SNPs, 7 novel SNPs (or SNVs), and 15 somatic mutations were detected in mtDNA of 8 oral cancer tissues with respect to reference (rCRS) and adjacent normal tissues, respectively, using Ion PGM next generation sequencing method. Most of the sequence variations (76 SNPs and 1 somatic) are present in D-loop region followed by CyB (36 SNPs), ATP6 (24 SNPs), ND5 (17 SNPs and 5 somatic), ND4 (18 coding and 2 somatic) and other non-coding and coding DNA sequences. A total of 53 and 8 non-synonymous SNPs and somatic mutations, respectively, were detected in tumor tissues and some of these variations may have deleterious effects on the protein function as predicted by bioinformatic analysis. Moreover, significantly low mtDNA contents and expression of several mitochondrial genes in tumor compared to adjacent normal tissues may have also affected mitochondrial functions. Taken together, this study suggests that mtDNA mutations as well as low expression of mtDNA coded genes may play important roles in tumor growth. Although the sample size is low, an important aspect of the study is the use of adjacent control tissues to find out somatic mutations and a change in the expression of mitochondrial genes, to rule out inter-individual and inter-tissue variations which are important issues in the study of mitochondrial genomics.

Proteomics of differential extraction fractions enriched for chromatin-binding proteins from colon adenoma and carcinoma tissues.

BACKGROUND: Altered nuclear and genomic structure and function are hallmarks of cancer cells. Research into nuclear proteins in human tissues could uncover novel molecular processes in cancer. Here, we examine biochemical tissue fractions containing chromatin-binding (CB) proteins in the context of colorectal cancer (CRC) progression. METHODS: CB protein-containing fractions were biochemically extracted from human colorectal tissues, including carcinomas with chromosomal instability (CIN), carcinomas with microsatellite instability (MIN), and adenomas. The CB proteins were subjected to label-free LC-MS/MS and the data were analyzed by bioinformatics. RESULTS: Over 1700 proteins were identified in the CB fraction from colonic tissues, including 938 proteins associated with nuclear annotation. Of the latter, 169 proteins were differential between adenomas and carcinomas. In this adenoma-versus-carcinoma comparison, apart from specific changes in components of the splicing and protein translational machineries, we also identified significant changes in several proteins associated with chromatin-directed functions. Furthermore, several key cell cycle proteins as well as those involved in cellular stress were increased, whereas specific components of chromosome segregation and DNA recombination/repair systems were decreased. CONCLUSIONS: Our study identifies proteomic changes at the subnuclear level that are associated with CRC and may be further investigated. This article is part of a Special Issue entitled: Biomarkers: A Proteomic Challenge.

MAGEA10 gene expression in non-small cell lung cancer and A549 cells, and the affinity of epitopes with the complex of HLA-A(∗)0201 alleles.

MAGEA10, a cancer/testis antigens expressed in tumors but not in normal tissues with the exception of testis and placenta, represents an attractive target for cancer immunotherapy. However, suppressive cytoenvironment and requirement of specific HLA-alleles presentation frequently led to immunotherapy failure. In this study MAGEA10 was scarcely expressed in cancer patients, but enhanced by viili polysaccharides, which indicates a possibility of increasing epitopes presentation. Furthermore the correlation of gene expression with methylation, indicated by R(2) value for MAGEA10 that was 3 times higher than the value for other MAGE genes tested, provides an explanation of why MAGEA10 was highly inhibited, this is also seen by Kaplan-Meier analysis because MAGEA10 did not change the patients' lifespan. By using Molecular-Docking method, 3 MAGEA10 peptides were found binding to the groove position of HLA-A(∗)0210 as same as MAGEA4 peptide co-crystallized with HLA-A(∗)0210, which indicates that they could be promising for HLA-A(∗)0201 presentation in immunotherapy.

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.

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.

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.

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.

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.

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.

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.

Proteomic profiling of a mouse model of acute intestinal Apc deletion leads to identification of potential novel biomarkers of human colorectal cancer (CRC).

Colorectal cancer (CRC) is the fourth most common cause of cancer-related death worldwide. Accurate non-invasive screening for CRC would greatly enhance a population's health. Adenomatous polyposis coli (Apc) gene mutations commonly occur in human colorectal adenomas and carcinomas, leading to Wnt signalling pathway activation. Acute conditional transgenic deletion of Apc in murine intestinal epithelium (AhCre(+)Apc(fl)(/)(fl)) causes phenotypic changes similar to those found during colorectal tumourigenesis. This study comprised a proteomic analysis of murine small intestinal epithelial cells following acute Apc deletion to identify proteins that show altered expression during human colorectal carcinogenesis, thus identifying proteins that may prove clinically useful as blood/serum biomarkers of colorectal neoplasia. Eighty-one proteins showed significantly increased expression following iTRAQ analysis, and validation of nine of these by Ingenuity Pathaway Analysis showed they could be detected in blood or serum. Expression was assessed in AhCre(+)Apc(fl)(/)(fl) small intestinal epithelium by immunohistochemistry, western blot and quantitative real-time PCR; increased nucelolin concentrations were also detected in the serum of AhCre(+)Apc(fl)(/)(fl) and Apc(Min)(/)(+) mice by ELISA. Six proteins; heat shock 60kDa protein 1, Nucleolin, Prohibitin, Cytokeratin 18, Ribosomal protein L6 and DEAD (Asp-Glu-Ala-Asp) box polypeptide 5,were selected for further investigation. Increased expression of 4 of these was confirmed in human CRC by qPCR. In conclusion, several novel candidate biomarkers have been identified from analysis of transgenic mice in which the Apc gene was deleted in the intestinal epithelium that also showed increased expression in human CRC. Some of these warrant further investigation as potential serum-based biomarkers of human CRC.