Reduced expression of the polymeric immunoglobulin receptor in pancreatic and periampullary adenocarcinoma signifies tumour progression and poor prognosis

The polymeric immunoglobulin receptor (pIgR) is a key component of the mucosal immune system that mediates epithelial transcytosis of immunoglobulins. High pIgR expression has been reported to correlate with a less aggressive tumour phenotype and an improved prognosis in several human cancer types. Here, we examined the expression and prognostic significance of pIgR in pancreatic and periampullary adenocarcinoma. The study cohort encompasses a consecutive series of 175 patients surgically treated with pancreaticoduodenectomy for pancreatic and periampullary adenocarcinoma in Malmö and Lund University Hospitals, Sweden, between 2001-2011. Tissue microarrays were constructed from primary tumours (n = 175) and paired lymph node metastases (n = 105). A multiplied score was calculated from the fraction and intensity of pIgR staining. Classification and regression tree analysis was used to select the prognostic cut-off. Unadjusted and adjusted hazard ratios (HR) for death and recurrence within 5 years were calculated. pIgR expression could be evaluated in 172/175 (98.3%) primary tumours and in 96/105 (91.4%) lymph node metastases. pIgR expression was significantly down-regulated in lymph node metastases as compared with primary tumours (p = 0.018). Low pIgR expression was significantly associated with poor differentiation grade (p < 0.001), perineural growth (p = 0.027), lymphatic invasion (p = 0.016), vascular invasion (p = 0.033) and infiltration of the peripancreatic fat (p = 0.039). In the entire cohort, low pIgR expression was significantly associated with an impaired 5-year survival (HR = 2.99, 95% confidence interval (CI) 1.71-5.25) and early recurrence (HR = 2.89, 95% CI 1.67-4.98). This association remained significant for survival after adjustment for conventional clinicopathological factors, tumour origin and adjuvant treatment (HR = 1.98, 95% CI 1.10-3.57). These results demonstrate, for the first time, that high tumour-specific pIgR expression signifies a more favourable tumour phenotype and that low expression independently predicts a shorter survival in patients with pancreatic and periampullary cancer. The mechanistic basis for the putative tumour suppressing properties of pIgR in these cancers merits further study

Methylation Markers of Early-Stage Non-Small Cell Lung Cancer

Despite of intense research in early cancer detection, there is a lack of biomarkers for the reliable detection of malignant tumors, including non-small cell lung cancer (NSCLC). DNA methylation changes are common and relatively stable in various types of cancers, and may be used as diagnostic or prognostic biomarkers.We performed DNA methylation profiling of samples from 48 patients with stage I NSCLC and 18 matching cancer-free lung samples using microarrays that cover the promoter regions of more than 14,500 genes. We correlated DNA methylation changes with gene expression levels and performed survival analysis.We observed hypermethylation of 496 CpGs in 379 genes and hypomethylation of 373 CpGs in 335 genes in NSCLC. Compared to adenocarcinoma samples, squamous cell carcinoma samples had 263 CpGs in 223 hypermethylated genes and 513 CpGs in 436 hypomethylated genes. 378 of 869 (43.5%) CpG sites discriminating the NSCLC and control samples showed an inverse correlation between CpG site methylation and gene expression levels. As a result of a survival analysis, we found 10 CpGs in 10 genes, in which the methylation level differs in different survival groups.We have identified a set of genes with altered methylation in NSCLC and found that a minority of them showed an inverse correlation with gene expression levels. We also found a set of genes that associated with the survival of the patients. These newly-identified marker candidates for the molecular screening of NSCLC will need further analysis in order to determine their clinical utility

Autoantibody Profiling for Lung Cancer Screening Longitudinal Retrospective Analysis of CT Screening Cohorts

Recommendations for lung cancer screening present a tangible opportunity to integrate predictive blood-based assays with radiographic imaging. This study compares performance of autoantibody markers from prior discovery in sample cohorts from two CT screening trials. One-hundred eighty non-cancer and 6 prevalence and 44 incidence cancer cases detected in the Mayo Lung Screening Trial were tested using a panel of six autoantibody markers to define a normal range and assign cutoff values for class prediction. A cutoff for minimal specificity and best achievable sensitivity were applied to 256 samples drawn annually for three years from 95 participants in the Kentucky Lung Screening Trial. Data revealed a discrepancy in quantile distribution between the two apparently comparable sample sets, which skewed the assay’s dynamic range towards specificity. This cutoff offered 43% specificity (102/237) in the control group and accurately classified 11/19 lung cancer samples (58%), which included 4/5 cancers at time of radiographic detection (80%), and 50% of occult cancers up to five years prior to diagnosis. An apparent ceiling in assay sensitivity is likely to limit the utility of this assay in a conventional screening paradigm. Pre-analytical bias introduced by sample age, handling or storage remains a practical concern during development, validation and implementation of autoantibody assays. This report does not draw conclusions about other logical applications for autoantibody profiling in lung cancer diagnosis and management, nor its potential when combined with other biomarkers that might improve overall predictive accuracy

Peptides from the variable region of specific antibodies are shared among lung cancer patients

textabstractLate diagnosis of lung cancer is still the main reason for high mortality rates in lung cancer. Lung cancer is a heterogeneous disease which induces an immune response to different tumor antigens. Several methods for searching autoantibodies have been described that are based on known purified antigen panels. The aim of our study is to find evidence that parts of the antigen-binding-domain of antibodies are shared among lung cancer patients. This was investigated by a novel approach based on sequencing antigen-binding- fragments (Fab) of immunoglobulins using proteomic techniques without the need of previously known antigen panels. From serum of 93 participants of the NELSON trial IgG was isolated and subsequently digested into Fab and Fc. Fab was purified from the digested mixture by SDS-PAGE. The Fab containing gel-bands were excised, tryptic digested and measured on a nano-LC-Orbitrap-Mass- spectrometry system. Multivariate analysis of the mass spectrometry data by linear canonical discriminant analysis combined with stepwise logistic regression resulted in a 12-antibody-peptide model which was able to distinguish lung cancer patients from controls in a high risk population with a sensitivity of 84% and specificity of 90%. With our Fab-purification combined Orbitrap-mass-spectrometry approach, we found peptides from the variable-parts of antibodies which are shared among lung cancer patients