Browsing by Subject "Biological marker"

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Open Access
Adjuvant autologous melanoma vaccine for macroscopic stage III disease: survival, biomarkers, and improved response to CTLA-4 blockade
(Hindawi Limited, 2016) Lotem, M.; Merims, S.; Frank, S.; Hamburger, T.; Nissan, A.; Kadouri, L.; Cohen, J.; Straussman, R.; Eisenberg, G.; Frankenburg, S.; Carmon, E.; Alaiyan, B.; Shneibaum, S.; Ayyildiz, Z. O.; Isbilen, M.; Senses, K. M.; Ron, I.; Steinberg, H.; Smith, Y.; Shiloni, E.; Gure, A. O.; Peretz, T.
Background. There is not yet an agreed adjuvant treatment for melanoma patients with American Joint Committee on Cancer stages III B and C. We report administration of an autologous melanoma vaccine to prevent disease recurrence. Patients and Methods. 126 patients received eight doses of irradiated autologous melanoma cells conjugated to dinitrophenyl and mixed with BCG. Delayed type hypersensitivity (DTH) response to unmodified melanoma cells was determined on the vaccine days 5 and 8. Gene expression analysis was performed on 35 tumors from patients with good or poor survival. Results. Median overall survival was 88 months with a 5-year survival of 54%. Patients attaining a strong DTH response had a significantly better (p = 0.0001) 5-year overall survival of 75% compared with 44% in patients without a strong response. Gene expression array linked a 50-gene signature to prognosis, including a cluster of four cancer testis antigens: CTAG2 (NY-ESO-2), MAGEA1, SSX1, and SSX4. Thirty-five patients, who received an autologous vaccine, followed by ipilimumab for progressive disease, had a significantly improved 3-year survival of 46% compared with 19% in nonvaccinated patients treated with ipilimumab alone (p = 0.007). Conclusion. Improved survival in patients attaining a strong DTH and increased response rate with subsequent ipilimumab suggests that the autologous vaccine confers protective immunity.
Open Access
Circulating LL37 targets plasma extracellular vesicles to immune cells and intensifies Behçet's disease severity
(Taylor and Francis, 2017-02) Kahraman, T.; Gucluler, G.; Simsek, I.; Yagci, F. C.; Yildirim, M.; Ozen, C.; Dinc, A.; Gursel, M.; Ikromzoda, L.; Sutlu, T.; Gay, S.; Gursel, I.
Behçet's disease (BD) activity is characterised by sustained, over-exuberant immune activation, yet the underlying mechanisms leading to active BD state are poorly defined. Herein, we show that the human cathelicidin derived antimicrobial peptide LL37 associates with and directs plasma extracellular vesicles (EV) to immune cells, thereby leading to enhanced immune activation aggravating BD pathology. Notably, disease activity was correlated with elevated levels of circulating LL37 and EV plasma concentration. Stimulation of healthy PBMC with active BD patient EVs induced heightened IL1β, IFNα, IL6 and IP10 secretion compared to healthy and inactive BD EVs. Remarkably, when mixed with LL37, healthy plasma-EVs triggered a robust immune activation replicating the pathology inducing properties of BD EVs. The findings of this study could be of clinical interest in the management of BD, implicating LL37/EV association as one of the major contributors of BD pathogenesis.
Open Access
A combined ULBP2 and SEMA5A expression signature as a prognostic and predictive biomarker for colon cancer
(Ivyspring International Publisher, 2017) Demirkol, S.; Gomceli, I.; Isbilen, M.; Dayanc, B. E.; Tez, M.; Bostanci, E. B.; Turhan, N.; Akoglu, M.; Ozyerli, E.; Durdu, S.; Konu, O.; Nissan, A.; Gonen, M.; Gure, A. O.
Background: Prognostic biomarkers for cancer have the power to change the course of disease if they add value beyond known prognostic factors, if they can help shape treatment protocols, and if they are reliable. The aim of this study was to identify such biomarkers for colon cancer and to understand the molecular mechanisms leading to prognostic stratifications based on these biomarkers. Methods and Findings: We used an in house R based script (SSAT) for the in silico discovery of stage-independent prognostic biomarkers using two cohorts, GSE17536 and GSE17537, that include 177 and 55 colon cancer patients, respectively. This identified 2 genes, ULBP2 and SEMA5A, which when used jointly, could distinguish patients with distinct prognosis. We validated our findings using a third cohort of 48 patients ex vivo. We find that in all cohorts, a combined ULBP2/SEMA5A classification (SU-GIB) can stratify distinct prognostic sub-groups with hazard ratios that range from 2.4 to 4.5 (p=0.01) when overall- or cancer-specific survival is used as an end-measure, independent of confounding prognostic parameters. In addition, our preliminary analyses suggest SU-GIB is comparable to Oncotype DX colon(®) in predicting recurrence in two different cohorts (HR: 1.5-2; p=0.02). SU-GIB has potential as a companion diagnostic for several drugs including the PI3K/mTOR inhibitor BEZ235, which are suitable for the treatment of patients within the bad prognosis group. We show that tumors from patients with worse prognosis have low EGFR autophosphorylation rates, but high caspase 7 activity, and show upregulation of pro-inflammatory cytokines that relate to a relatively mesenchymal phenotype. Conclusions: We describe two novel genes that can be used to prognosticate colon cancer and suggest approaches by which such tumors can be treated. We also describe molecular characteristics of tumors stratified by the SU-GIB signature.
Open Access
Functional genomics in translational cancer research: focus on breast cancer
(Oxford University Press, 2008) Yulug, I. G.; Gur-Dedeoglu, B.
Conventional molecular and genetic methods for studying cancer are limited to the analysis of one locus at a time. A cluster of genes that are regulated together can be identified by DNA microarray, and the functional relationships can uncover new aspects of cancer biology. Breast cancer can be used to provide a model to demonstrate the current approaches to the molecular analysis of cancer. Meta-analysis is an important tool for the identification and validation of differentially expressed genes to increase power in clinical and biological studies across different sets of data. Recently, meta-analysis approaches have been applied to large collections of microarray datasets to investigate molecular commonalities of multiple cancer types not only to find the common molecular pathways in tumour development but also to compare the individual datasets to other cancer datasets to identify new sets of genes. Several investigators agree that microarray results should be validated. One commonly used method is quantitative reverse transcription PCR (qRT-PCR) to validate the expression profiles of the target genes obtained through microarray experiments. qRT-PCR is attractive for clinical use, since it can be automated and performed on fresh or archived formalin-fixed, paraffin-embedded tissue samples. The outcome of these analyses might accelerate the application of basic research findings into daily clinical practice through translational research and may have an impact on foreseeing the clinical outcome, predicting tumour response to specific therapy, identification of new prognostic biomarkers, discovering targets for the development of novel therapies and providing further insights into tumour biology. © The Author 2008. Published by Oxford University Press.
Open Access
High-resolution magic anglespinning ¹H nuclear magnetic resonance spectroscopy metabolomics of hyperfunctioning parathyroid glands
(Mosby, Inc., 2016) Battini, S.; Imperiale, A.; Taïeb, D.; Elbayed, K.; Cicek, A. E.; Sebag, F.; Brunaud, L.; Namer, Izzie-Jacques
Background Primary hyperparathyroidism (PHPT) may be related to a single gland disease or multiglandular disease, which requires specific treatments. At present, an operation is the only curative treatment for PHPT. Currently, there are no biomarkers available to identify these 2 entities (single vs. multiple gland disease). The aims of the present study were to compare (1) the tissue metabolomics profiles between PHPT and renal hyperparathyroidism (secondary and tertiary) and (2) single gland disease with multiglandular disease in PHPT using metabolomics analysis. Methods The method used was 1H high-resolution magic angle spinning nuclear magnetic resonance spectroscopy. Forty-three samples from 32 patients suffering from hyperparathyroidism were included in this study. Results Significant differences in the metabolomics profile were assessed according to PHPT and renal hyperparathyroidism. A bicomponent orthogonal partial least square-discriminant analysis showed a clear distinction between PHPT and renal hyperparathyroidism (R2Y = 0.85, Q2 = 0.63). Interestingly, the model also distinguished single gland disease from multiglandular disease (R2Y = 0.96, Q2 = 0.55). A network analysis was also performed using the Algorithm to Determine Expected Metabolite Level Alterations Using Mutual Information (ADEMA). Single gland disease was accurately predicted by ADEMA and was associated with higher levels of phosphorylcholine, choline, glycerophosphocholine, fumarate, succinate, lactate, glucose, glutamine, and ascorbate compared with multiglandular disease. Conclusion This study shows for the first time that 1H high-resolution magic angle spinning nuclear magnetic resonance spectroscopy is a reliable and fast technique to distinguish single gland disease from multiglandular disease in patients with PHPT. The potential use of this method as an intraoperative tool requires specific further studies.
Open Access
Impaired toll like receptor-7 and 9 induced immune activation in chronic spinal cord injured patients contributes to immune dysfunction
(Public Library of Science, 2017) Gucluler, G.; Adiguzel, E.; Gungor, B.; Kahraman, T.; Gursel, M.; Yilmaz, B.; Gursel, I.
Reduced immune activation or immunosuppression is seen in patients withneurological diseases. Urinary and respiratory infections mainly manifested as septicemia and pneumonia are the most frequent complications following spinal cord injuries and they account for the majority of deaths. The underlying reason of these losses is believed to arise due to impaired immune responses to pathogens. Here, we hypothesized that susceptibility to infections of chronic spinal cord injured (SCI) patients might be due to impairment in recognition of pathogen associated molecular patterns and subsequently declining innate and adaptive immune responses that lead to immune dysfunction. We tested our hypothesis on healthy and chronic SCI patients with a level of injury above T-6. Donor PBMCs were isolated and stimulated with different toll like receptor ligands and T-cell inducers aiming to investigate whether chronic SCI patients display differential immune activation to multiple innate and adaptive immune cell stimulants. We demonstrate that SCI patients' B-cell and plasmacytoid dendritic cells retain their functionality in response to TLR7 and TLR9 ligand stimulation as they secreted similar levels of IL6 and IFNα. The immune dysfunction is not probably due to impaired T-cell function, since neither CD4+ T-cell dependent IFNγ producing cell number nor IL10 producing regulatory T-cells resulted different outcomes in response to PMA-Ionomycin and PHA-LPS stimulation, respectively. We showed that TLR7 dependent IFNγ and IP10 levels and TLR9 mediated APC function reduced substantially in SCI patients compared to healthy subjects. More importantly, IP10 producing monocytes were significantly fewer compared to healthy subjects in response to TLR7 and TLR9 stimulation of SCI PBMCs. When taken together this work implicated that these defects could contribute to persistent complications due to increased susceptibility to infections of chronic SCI patients. © 2017 Gucluler et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Open Access
Iterative H-minima-based marker-controlled watershed for cell nucleus segmentation
(John Wiley & Sons, Inc., 2016) Koyuncu, Can Fahrettin; Akhan, Ece; Ersahin, T.; Cetin Atalay, R.; Gunduz Demir, Çiğdem
Automated microscopy imaging systems facilitate high-throughput screening in molecular cellular biology research. The first step of these systems is cell nucleus segmentation, which has a great impact on the success of the overall system. The marker-controlled watershed is a technique commonly used by the previous studies for nucleus segmentation. These studies define their markers finding regional minima on the intensity/gradient and/or distance transform maps. They typically use the h-minima transform beforehand to suppress noise on these maps. The selection of the h value is critical; unnecessarily small values do not sufficiently suppress the noise, resulting in false and oversegmented markers, and unnecessarily large ones suppress too many pixels, causing missing and undersegmented markers. Because cell nuclei show different characteristics within an image, the same h value may not work to define correct markers for all the nuclei. To address this issue, in this work, we propose a new watershed algorithm that iteratively identifies its markers, considering a set of different h values. In each iteration, the proposed algorithm defines a set of candidates using a particular h value and selects the markers from those candidates provided that they fulfill the size requirement. Working with widefield fluorescence microscopy images, our experiments reveal that the use of multiple h values in our iterative algorithm leads to better segmentation results, compared to its counterparts.
Open Access
p53 codon 72 polymorphism in bladder cancer-No evidence of association with increased risk or invasiveness
(Springer, 2001) Törüner, G. A.; Uçar, A.; Tez, M.; Çetinkaya, M.; Özen, H.; Özçelik, T.
We studied the effect of the p53 gene Arg72Pro polymorphism on bladder cancer susceptibility in a case control study of 121 bladder cancer patients and 114 age-sex matched controls to determine whether this polymorphism is a biomarker for the risk and how aggressive the disease is. Genomic DNA was obtained from venous blood samples for genotype determination by PCR and restriction digestion. The genotype frequencies in the patient group were Arg/Arg: 0.3553, Arg/Pro: 0.4711, Pro/Pro: 0.1736, and in the control group Arg/Arg: 0.3684, Arg/Pro: 0.4825, Pro/Pro: 0.1491. The distribution of genotypes between the two groups was not statistically different (χ2 = 0.260, df: 2, P = 0.878). The patient group was subdivided into two groups as superficial bladder cancer (n = 88) and invasive bladder cancer (n = 33), according to the presence of muscle invasion. The distribution of genotypes in the superficial group was Arg/Arg: 0.3409, Arg/Pro: 0.5114, Pro/Pro: 0.1477 and in the invasive group Arg/Arg: 0.3940, Arg/Pro: 0.3636, Pro/Pro: 0.2424. No association was observed with the invasiveness of the tumor (χ2 = 2.542, df: 2, P = 0.281). Stratification of the data by tobacco exposure did not result in a significant difference in genotype frequencies. These data do not support an association between the p53 Arg72Pro polymorphism and bladder cancer.