Longitudinal course of circulating donor-specific T-cell precursor frequencies in LTx-recipients.

<p>CFSE-labeled PBMC of 13 LTx-recipients obtained before transplantation (Pre), or at 1 week (W1), 1 month (M1), 3 months (M3) or 1 year (Y1) after transplantation, were co-cultured for 6 days with donor-derived splenic CD40-B cells, 3^rd party splenic CD40-B cells or autologous PBMC-derived CD40-B cells. PF of CD3⁺, CD4⁺ and CD8⁺ T cells responding to these stimulators were determined. Recipients and donors differed on the average in 1.5 HLA-AB alleles and in 1.7 HLA-DR alleles. Third-party stimulators were mismatched with recipients in 1.7 HLA-AB alleles and 1.8 HLA-DR alleles. Donor-derived and 3^rd party-derived stimulator cells differed on the average at 1.8 HLA-AB loci and 1.5 HLA-DR loci. A. Numbers of T-cell precursors responding to donor-derived CD40-B cells increased significantly 1 week after transplantation in all T-cell subsets, followed by a decrease to values below pre-transplant levels. B. Non-specific variations in allo-responses were determined by stimulating patient PBMC with third-party spleen-derived CD40-B cells. Changes in PF of CD4⁺ and CD8⁺ T cells responding to 3^rd party CD40-B cells between subsequent time points were generally smaller compared to those in donor-specific PF. C. Donor-specific responses were calculated by dividing PF responding to donor-alloantigen by third-party PF to obtain the relative responses (RR). RR increased significantly 1 week after transplantation in all T-cell subsets, followed by a significant decrease at 1 year after LTX. D. Comparison of relative CD3⁺, CD4⁺ and CD8⁺ T-cell responses (RR) of 18 LTx-recipients before and 1 year after LTx. Five additional patients were analyzed, and their data were added to the data of the 13 patients shown in C. Donor-derived and 3^rd party-derived stimulator cells used in assaying the 5 additional patients were fully MHC mismatched.</p

Comparison of IFN-γ production by T cells in CFSE-MLR before and 1 year after LTx.

<p>CFSE-labeled PBMC from 5 LTx-patients were stimulated with donor-derived or 3^rd party CD40-B cells, and re-stimulated with the same allo-antigens at day 5 of culture for 24 hours. During the last 15 hours Brefeldin A was added, and CFSE-dilution and intracellular IFN-γ was determined at day 6. Depicted are the percentages of T cells producing IFN-γ in response to donor-derived CD40-B cells and 3^rd party-derived CD40-B cells, and the RR of IFN-γ producing T cells. No statistically significant differences were observed in comparing RR at 1 year after LTx versus before LTx (p≥0.44).</p

Relative contributions of naïve and memory T cells to the allo-response in CFSE-MLR upon stimulation with CD40-B cells.

<p>CFSE-labelled naïve CD3⁺CD45RA⁺and CD3⁺CD45RO⁺ memory T cells were isolated from PBMC of healthy individuals by flowcytometric sorting, and stimulated with allogeneic CD40-B cells for 6 days. A. Purity of CD3⁺CD45RO⁺ and CD3⁺CD45RA⁺ T cells after sorting. B. PF of CD3⁺CD45RO⁺ and CD3⁺CD45RA⁺ T cells proliferating upon stimulation with allogeneic CD40-B cells. Depicted are means ± SD of data from two independent experiments, each with 3 replicates.</p

Analysis of CFSE-dilution patterns by ModFit® software.

<p>ModFit-derived CFSE-pattern of CD3⁺ T cells after 6 days of stimulation with allogeneic CD40-B cells. The software draws peaks within the CFSE-histogram centered on halving intensity values from the parental peak CFSE-intensity. Non-divided T cells are CFSE^high and are depicted blue, while the peaks left from it correspond to divided cells. Based on the enumerated proportions of T cells detected in each generation ( = % under each peak) and the total number of CD3⁺ T cells analyzed by the flowcytometer, the program calculates the absolute numbers of daughter T cells in each generation. The numbers of precursors which gave rise to the daughter cells are extrapolated by dividing the absolute numbers of T cells in each generation by 2ⁿ, in which n stands for the division cycle ( = absolute # of precursors). The PF is calculated by dividing the numbers of precursors from generation 2 onwards ( = B) by the total number of precursors in all generations including the parent peak and generation 1 ( = A). In this example the calculated PF =  (362,302 – (337,620 + 8925)/362,302) ×100 = 4.3%. The fit of the derived Gaussian peaks in the CFSE-dilution pattern is indicated by the reduced chi-square value. Values below 5 were considered as a good fit according to the manufacturer's instructions, and were included in the analysis.</p

Kinetics of allogeneic T-cell responses to CD40-B cell stimulation.

<p>CFSE-labeled PBMC from a healthy individual were cultured for 7 days with allogeneic splenocyte-derived CD40-B cells. A. CFSE-dilution patterns of CD3⁺, CD4⁺, CD8⁺ T cells were analyzed daily, and PF were calculated with ModFit® software. B. Intracellular granzyme B and perforin expression were analyzed daily in CD8⁺ T cells. Depicted are the percentages of CD8⁺CFSE^low T cells that expressed granzyme B and/or perforin. C. Absolute numbers CD3⁺, CD4⁺ and CD8⁺ T cells during co-culture of CFSE-labelled PBMC with allogeneic CD40-B cells. Vital PBMC were counted daily using trypan blue, and proportions of CD3⁺, CD4⁺ and CD8⁺ T cells were analyzed by flowcytometry. Absolute numbers of T-cell subsets were calculated by multiplying the number of vital PBMC with the proportions of T cells obtained from flowcytometric analysis.</p

Expansion and differentiation of B cells using L-CD40L cells.

<p>A. Human splenocytes or PBMC were co-cultured with L-CD40L cells, IL-4 and CsA. Within 3 weeks, a 10⁴ fold increase of the numbers of B cells was obtained with a purity of >95%. T cells did not expand due to the presence of CsA. The current graph represents expansion from PBMC, splenocytes gave similar results. B. Cell surface marker expression on CD40-B cells harvested at day 12 of culture. CD40L-expanded B cells were activated (CD38⁺) and expressed the co-stimulatory molecules CD80 and CD86, and MHC class-II, indicating that they became professional APC. However, they did not become plasma cells, since they lacked CD138. Solid lines represent the expression of surface markers at day 0; dotted lines represent the expression at day 12 after culture. C. Donor splenocytes contained about 50% of HLA-DR⁺ APC, however these lacked CD80 and showed low expression of CD86.</p

Bioinformatic analysis reveals pancreatic cancer molecular subtypes specific to the tumor and the microenvironment

<p>Pancreatic ductal adenocarcinoma (PDAC) is a lethal disease characterized by a dense desmoplastic reaction surrounding malignant epithelial cells. Interaction between the epithelial and stromal compartments is suggested to enhance its aggressive nature. Indeed, therapies targeting the stroma, as well as the tumor cells, may improve survival outcomes for patients. The evaluated study by Moffitt <i>et al</i>. used bioinformatic techniques to separate gene expression patterns of normal tissues from PDAC and stroma in a large cohort of samples. The researchers identified two different subtypes of PDAC (‘classical’ and ‘basal-like’) and surrounding stroma (‘normal’ and ‘activated’). The basal-like subtype was associated with worse prognosis and a trend towards better response to adjuvant therapy. Hopefully, the molecular stratification of PDAC will potentially allow more personalized treatment strategies and guide clinical decision making.</p

Dynamics of methylated cell-free DNA in the urine of non-small cell lung cancer patients

High levels of methylated DNA in urine represent an emerging biomarker for non-small cell lung cancer (NSCLC) detection and are the subject of ongoing research. This study aimed to investigate the circadian variation of urinary cell-free DNA (cfDNA) abundance and methylation levels of cancer-associated genes in NSCLC patients. In this prospective study of 23 metastatic NSCLC patients with active disease, patients were asked to collect six urine samples during the morning, afternoon, and evening of two subsequent days. Urinary cfDNA concentrations and methylation levels of CDO1, SOX17, and TAC1 were measured at each time point. Circadian variation and between- and within-subject variability were assessed using linear mixed models. Variability was estimated using the Intraclass Correlation Coefficient (ICC), representing reproducibility. No clear circadian patterns could be recognized for cfDNA concentrations or methylation levels across the different sampling time points. Significantly lower cfDNA concentrations were found in males (p=0.034). For cfDNA levels, the between- and within-subject variability were comparable, rendering an ICC of 0.49. For the methylation markers, ICCs varied considerably, ranging from 0.14 to 0.74. Test reproducibility could be improved by collecting multiple samples per patient. In conclusion, there is no preferred collection time for NSCLC detection in urine using methylation markers, but single measurements should be interpreted carefully, and serial sampling may increase test performance. This study contributes to the limited understanding of cfDNA dynamics in urine and the continued interest in urine-based liquid biopsies for cancer diagnostics.</p

Additional file 1: of Minimally invasive versus open distal pancreatectomy (LEOPARD): study protocol for a randomized controlled trial

SPIRIT 2013 checklist: recommended items to address in a clinical trial protocol and related documents. (DOC 112 kb