Circulating tumor cell detection in high-risk non-metastatic prostate cancer

Purpose The detection of circulating tumor cells (CTCs) provides important prognostic information in men with metastatic prostate cancer. We aim to determine the rate of detection of CTCs in patients with high-risk non-metastatic prostate cancer using the CellSearch® method. Method Samples of peripheral blood (7.5 mL) were drawn from 36 men with newly diagnosed high-risk non-metastatic prostate cancer, prior to any initiation of therapy and analyzed for CTCs using the CellSearch® method. Results The median age was 70 years, median PSA was 14.1, and the median Gleason score was 9. The median 5-year risk of progression of disease using a validated nomogram was 39 %. Five out of 36 patients (14 %, 95 % CI 5–30 %) had CTCs detected in their circulation. Four patients had only 1 CTC per 7.5 mL of blood detected. One patient had 3 CTCs per 7.5 mL of blood detected, which included a circulating tumor microemboli. Both on univariate analysis and multivariate analysis, there were no correlations found between CTC positivity and the classic prognostic factors including PSA, Gleason score, T-stage and age. Conclusion This study demonstrates that patients with high-risk, non-metastatic prostate cancer present infrequently with small number of CTCs in peripheral blood. This finding is consistent with the limited literature available in this setting. Other CTC isolation and detection technologies with improved sensitivity and specificity may enable detection of CTCs with mesenchymal phenotypes, although none as yet have been validated for clinical use. Newer assays are emerging for detection of new putative biomarkers for prostate cancer. Correlation of disease control outcomes with CTC detection will be important.

Spectral analysis of pair-correlation bandwidth: Application to cell biology images

Images from cell biology experiments often indicate the presence of cell clustering, which can provide insight into the mechanisms driving the collective cell behaviour. Pair-correlation functions provide quantitative information about the presence, or absence, of clustering in a spatial distribution of cells. This is because the pair-correlation function describes the ratio of the abundance of pairs of cells, separated by a particular distance, relative to a randomly distributed reference population. Pair-correlation functions are often presented as a kernel density estimate where the frequency of pairs of objects are grouped using a particular bandwidth (or bin width), Δ>0. The choice of bandwidth has a dramatic impact: choosing Δ too large produces a pair-correlation function that contains insufficient information, whereas choosing Δ too small produces a pair-correlation signal dominated by fluctuations. Presently, there is little guidance available regarding how to make an objective choice of Δ. We present a new technique to choose Δ by analysing the power spectrum of the discrete Fourier transform of the pair-correlation function. Using synthetic simulation data, we confirm that our approach allows us to objectively choose Δ such that the appropriately binned pair-correlation function captures known features in uniform and clustered synthetic images. We also apply our technique to images from two different cell biology assays. The first assay corresponds to an approximately uniform distribution of cells, while the second assay involves a time series of images of a cell population which forms aggregates over time. The appropriately binned pair-correlation function allows us to make quantitative inferences about the average aggregate size, as well as quantifying how the average aggregate size changes with time.

The mechanisms of human renal epithelial cell modulation of autologous dendritic cell phenotype and function

Proximal tubule epithelial cells (PTEC) of the kidney line the proximal tubule downstream of the glomerulus and play a major role in the re-absorption of small molecular weight proteins that may pass through the glomerular filtration process. In the perturbed disease state PTEC also contribute to the inflammatory disease process via both positive and negative mechanisms via the production of inflammatory cytokines which chemo-attract leukocytes and the subsequent down-modulation of these cells to prevent uncontrolled inflammatory responses. It is well established that dendritic cells are responsible for the initiation and direction of adaptive immune responses. Both resident and infiltrating dendritic cells are localised within the tubulointerstitium of the renal cortex, in close apposition to PTEC, in inflammatory disease states. We previously demonstrated that inflammatory PTEC are able to modulate autologous human dendritic cell phenotype and functional responses. Here we extend these findings to characterise the mechanisms of this PTEC immune-modulation using primary human PTEC and autologous monocyte-derived dendritic cells (MoDC) as the model system. We demonstrate that PTEC express three inhibitory molecules: (i) cell surface PD-L1 that induces MoDC expression of PD-L1; (ii) intracellular IDO that maintains the expression of MoDC CD14, drives the expression of CD80, PD-L1 and IL-10 by MoDC and inhibits T cell stimulatory capacity; and (iii) soluble HLA-G (sHLA-G) that inhibits HLA-DR and induces IL-10 expression by MoDC. Collectively the results demonstrate that primary human PTEC are able to modulate autologous DC phenotype and function via multiple complex pathways. Further dissection of these pathways is essential to target therapeutic strategies in the treatment of inflammatory kidney disorders.

Dacomitinib versus erlotinib in patients with EGFR-mutated advanced nonsmall-cell lung cancer (NSCLC): Pooled subset analyses from two randomized trials

Background: The irreversible epidermal growth factor receptor (EGFR) inhibitors have demonstrated efficacy in NSCLC patients with activating EGFR mutations, but it is unknown if they are superior to the reversible inhibitors. Dacomitinib is an oral, small-molecule irreversible inhibitor of all enzymatically active HER family tyrosine kinases. Methods: The ARCHER 1009 (NCT01360554) and A7471028 (NCT00769067) studies randomized patients with locally advanced/metastatic NSCLC following progression with one or two prior chemotherapy regimens to dacomitinib or erlotinib. EGFR mutation testing was performed centrally on archived tumor samples. We pooled patients with exon 19 deletion and L858R EGFR mutations from both studies to compare the efficacy of dacomitinib to erlotinib. Results: One hundred twenty-one patients with any EGFR mutation were enrolled; 101 had activating mutations in exon 19 or 21. For patients with exon19/21 mutations, the median progression-free survival was 14.6 months [95% confidence interval (CI) 9.0–18.2] with dacomitinib and 9.6 months (95% CI 7.4–12.7) with erlotinib [unstratified hazard ratio (HR) 0.717 (95% CI 0.458–1.124), two-sided log-rank, P = 0.146]. The median survival was 26.6 months (95% CI 21.6–41.5) with dacomitinib versus 23.2 months (95% CI 16.0–31.8) with erlotinib [unstratified HR 0.737 (95% CI 0.431–1.259), two-sided log-rank, P = 0.265]. Dacomitinib was associated with a higher incidence of diarrhea and mucositis in both studies compared with erlotinib. Conclusions: Dacomitinib is an active agent with comparable efficacy to erlotinib in the EGFR mutated patients. The subgroup with exon 19 deletion had favorable outcomes with dacomitinib. An ongoing phase III study will compare dacomitinib to gefitinib in first-line therapy of patients with NSCLC harboring common activating EGFR mutations (ARCHER 1050; NCT01774721). Clinical trials number: ARCHER 1009 (NCT01360554) and A7471028 (NCT00769067).