Cancer Tissue Engineering: A Novel 3D Polystyrene Scaffold for In Vitro Isolation and Amplification of Lymphoma Cancer Cells from Heterogeneous Cell Mixtures

Isolation and amplification of primary lymphoma cells in vitro setting is technically and biologically challenging task. To optimize culture environment and mimic in vivo conditions, lymphoma cell lines were used as a test case and were grown in 3-dimension (3D) using a novel 3D tissue culture polystyrene scaffold with neonatal stromal cells to represent a lymphoma microenvironment. In this model, the cell proliferation was enhanced more than 200-fold or 20,000% neoplastic surplus in 7 days when less than 1% lymphoma cells were cocultured with 100-fold excess of neonatal stroma cells, representing 3.2-fold higher proliferative rate than 2D coculture model. The lymphoma cells grew and aggregated to form clusters during 3D coculture and did not maintained the parental phenotype to grow in single-cell suspension. The cluster size was over 5-fold bigger in the 3D coculture by day 4 than 2D coculture system and contained less than 0.00001% of neonatal fibroblast trace. This preliminary data indicate that novel 3D scaffold geometry and coculturing environment can be customized to amplify primary cancer cells from blood or tissues related to hematological cancer and subsequently used for personalized drug screening procedures

Prediction of clinical outcomes using the pyrolysis, gas chromatography, and differential mobility spectrometry (Py-GC-DMS) system

AbstractBiological and molecular heterogeneity of human diseases especially cancers contributes to variations in treatment response, clinical outcome, and survival. The addition of new disease- and condition-specific biomarkers to existing clinical markers to track cancer heterogeneity provides possibilities for further assisting clinicians in predicting clinical outcomes and making choices of treatment options. Ionization patterns derived from biological specimens can be adapted for use with existing clinical markers for early detection, patient risk stratification, treatment decision making, and monitoring disease progression. In order to demonstrate the application of pyrolysis, gas chromatography, and differential mobility spectrometry (Py-GC-DMS) for human diseases to predict the outcome of diseases, we analyzed the ionized spectral signals generated by instrument ACB2000 (ACBirox universal detector 2000, ACBirox LLC, NJ, USA) from the serum samples of Mantle Cell Lymphoma (MCL) patients. Here, we have used mantle cell lymphoma as a disease model for a conceptual study only and based on the ionization patterns of the analyzed serum samples, we developed a multivariate algorithm comprised of variable selection and reduction steps followed by receiver operating characteristic curve (ROC) analysis to predict the probability of a good or poor clinical outcome as a means of estimating the likely success of a particular treatment option. Our preliminary study performed with small cohort provides a proof of concept demonstrating the ability of this system to predict the clinical outcome for human diseases with high accuracy suggesting the promising application of pyrolysis, gas chromatography, and differential mobility spectrometry (Py-GC-DMS) in the field of medicine

Fibroblast growth factor-2 (FGF2) and syndecan-1 (SDC1) are potential biomarkers for putative circulating CD15+/CD30+ cells in poor outcome Hodgkin lymphoma patients.

BACKGROUND: High risk, unfavorable classical Hodgkin lymphoma (cHL) includes those patients with primary refractory or early relapse, and progressive disease. To improve the availability of biomarkers for this group of patients, we investigated both tumor biopsies and peripheral blood leukocytes (PBL) of untreated (chemo-naïve, CN) Nodular Sclerosis Classic Hodgkin Lymphoma (NS-cHL) patients for consistent biomarkers that can predict the outcome prior to frontline treatment. METHODS AND MATERIALS: Bioinformatics data mining was used to generate 151 candidate biomarkers, which were screened against a library of 10 HL cell lines. Expression of FGF2 and SDC1 by CD30+ cells from HL patient samples representing good and poor outcomes were analyzed by qRT-PCR, immunohistochemical (IHC), and immunofluorescence analyses. RESULTS: To identify predictive HL-specific biomarkers, potential marker genes selected using bioinformatics approaches were screened against HL cell lines and HL patient samples. Fibroblast Growth Factor-2 (FGF2) and Syndecan-1 (SDC1) were overexpressed in all HL cell lines, and the overexpression was HL-specific when compared to 116 non-Hodgkin lymphoma tissues. In the analysis of stratified NS-cHL patient samples, expression of FGF2 and SDC1 were 245 fold and 91 fold higher, respectively, in the poor outcome (PO) group than in the good outcome (GO) group. The PO group exhibited higher expression of the HL marker CD30, the macrophage marker CD68, and metastatic markers TGFβ1 and MMP9 compared to the GO group. This expression signature was confirmed by qualitative immunohistochemical and immunofluorescent data. A Kaplan-Meier analysis indicated that samples in which the CD30+ cells carried an FGF2+/SDC1+ immunophenotype showed shortened survival. Analysis of chemo-naive HL blood samples suggested that in the PO group a subset of CD30+ HL cells had entered the circulation. These cells significantly overexpressed FGF2 and SDC1 compared to the GO group. The PO group showed significant down-regulation of markers for monocytes, T-cells, and B-cells. These expression signatures were eliminated in heavily pretreated patients. CONCLUSION: The results suggest that small subsets of circulating CD30+/CD15+ cells expressing FGF2 and SDC1 represent biomarkers that identify NS-cHL patients who will experience a poor outcome (primary refractory and early relapsing)

Thioaptamer Conjugated Liposomes for Tumor Vasculature Targeting

Recent developments in multi-functional nanoparticles offer a great potential for targeted delivery of therapeutic compounds and imaging contrast agents to specific cell types, in turn, enhancing therapeutic effect and minimizing side effects. Despite the promise, site specific delivery carriers have not been translated into clinical reality. In this study, we have developed long circulating liposomes with the outer surface decorated with thioated oligonucleotide aptamer (thioaptamer) against E-selectin (ESTA) and evaluated the targeting efficacy and PK parameters. In vitro targeting studies using Human Umbilical Cord Vein Endothelial Cell (HUVEC) demonstrated efficient and rapid uptake of the ESTA conjugated liposomes (ESTA-lip). In vivo, the intravenous administration of ESTA-lip resulted in their accumulation at the tumor vasculature of breast tumor xenografts without shortening the circulation half-life. The study presented here represents an exemplary use of thioaptamer for targeting and opens the door to testing various combinations of thioaptamer and nanocarriers that can be constructed to target multiple cancer types and tumor components for delivery of both therapeutics and imaging agents

Kallikrein family proteases KLK6 and KLK7 are potential early detection and diagnostic biomarkers for serous and papillary serous ovarian cancer subtypes.

BACKGROUND: Early detection of ovarian cancer remains a challenge due to widespread metastases and a lack of biomarkers for early-stage disease. This study was conducted to identify relevant biomarkers for both laparoscopic and serum diagnostics in ovarian cancer. METHODS: Bioinformatics analysis and expression screening in ovarian cancer cell lines were employed. Selected biomarkers were further validated in bio-specimens of diverse cancer types and ovarian cancer subtypes. For non-invasive detection, biomarker proteins were evaluated in serum samples from ovarian cancer patients. RESULTS: Two kallikrein (KLK) serine protease family members (KLK6 and KLK7) were found to be significantly overexpressed relative to normal controls in most of the ovarian cancer cell lines examined. Overexpression of KLK6 and KLK7 mRNA was specific to ovarian cancer, in particular to serous and papillary serous subtypes. In situ hybridization and histopathology further confirmed significantly elevated levels of KLK6 and KLK7 mRNA and proteins in tissue epithelium and a lack of expression in neighboring stroma. Lastly, KLK6 and KLK7 protein levels were significantly elevated in serum samples from serous and papillary serous subtypes in the early stages of ovarian cancer, and therefore could potentially decrease the high false negative rates found in the same patients with the common ovarian cancer biomarkers human epididymis protein 4 (HE4) and cancer antigen 125 (CA-125). CONCLUSION: KLK6 and KLK7 mRNA and protein overexpression is directly associated with early-stage ovarian tumors and can be measured in patient tissue and serum samples. Assays based on KLK6 and KLK7 expression may provide specific and sensitive information for early detection of ovarian cancer

Protein Calorie Malnutrition, Nutritional Intervention and Personalized Cancer Care

Cancer patients often experience weight loss caused by protein calorie malnutrition (PCM) during the course of the disease or treatment. PCM is expressed as severe if the patient has two or more of the following characteristics: obvious significant muscle wasting, loss of subcutaneous fat; nutritional intake of \u3c50% of recommended intake for 2 weeks or more; bedridden or otherwise significantly reduced functional capacity; weight loss of \u3e2% in 1 week, 5% in 1 month, or 7.5% in 3 months. Cancer anorexiacachexia syndrome (CACS) is a multifactorial condition of advanced PCM associated with underlying illness (in this case cancer) and is characterized by loss of muscle with or without loss of fat mass. Cachexia is defined as weight loss of more than 5% of body weight in 12 months or less in the presence of chronic disease. Hence with a chronic illness on board even a small amount of weight loss can open the door to cachexia. These nutritional challenges can lead to severe morbidity and mortality in cancer patients. In the clinic, the application of personalized medicine and the ability to withstand the toxic effects of anti-cancer therapies can be optimized when the patient is in nutritional homeostasis and is free of anorexia and cachexia. Routine assessment of nutritional status and appropriate intervention are essential components of the effort to alleviate effects of malnutrition on quality of life and survival of patients

Hundreds of variants clustered in genomic loci and biological pathways affect human height

Most common human traits and diseases have a polygenic pattern of inheritance: DNA sequence variants at many genetic loci influence the phenotype. Genome-wide association (GWA) studies have identified more than 600 variants associated with human traits, but these typically explain small fractions of phenotypic variation, raising questions about the use of further studies. Here, using 183,727 individuals, we show that hundreds of genetic variants, in at least 180 loci, influence adult height, a highly heritable and classic polygenic trait. The large number of loci reveals patterns with important implications for genetic studies of common human diseases and traits. First, the 180 loci are not random, but instead are enriched for genes that are connected in biological pathways (P = 0.016) and that underlie skeletal growth defects (P < 0.001). Second, the likely causal gene is often located near the most strongly associated variant: in 13 of 21 loci containing a known skeletal growth gene, that gene was closest to the associated variant. Third, at least 19 loci have multiple independently associated variants, suggesting that allelic heterogeneity is a frequent feature of polygenic traits, that comprehensive explorations of already-discovered loci should discover additional variants and that an appreciable fraction of associated loci may have been identified. Fourth, associated variants are enriched for likely functional effects on genes, being over-represented among variants that alter amino-acid structure of proteins and expression levels of nearby genes. Our data explain approximately 10% of the phenotypic variation in height, and we estimate that unidentified common variants of similar effect sizes would increase this figure to approximately 16% of phenotypic variation (approximately 20% of heritable variation). Although additional approaches are needed to dissect the genetic architecture of polygenic human traits fully, our findings indicate that GWA studies can identify large numbers of loci that implicate biologically relevant genes and pathways.