Intrinsic variability in the detection of micrometastases in lymph nodes for re-staging of colorectal cancer: effect of individual markers and tissue samples

In this study, we investigated whether (a) carcinoembryonic antigen (CEA), cytokeratin-20 (CK-20) and guanylyl cyclase C (GCC) are clinically useful markers for the molecular detection of submicroscopic metastases in colorectal cancer (CRC) and (b) whether overexpression of CEA, CK-20 and GCC can be reliably detected in formalin-fixed, paraffin-embedded tissues as well as frozen lymph nodes. We studied 175 frozen lymph nodes and 158 formalin-fixed, paraffin-embedded lymph nodes from 28 cases of CRC. CEA or CK-20 or GCC-specific polymerase chain reaction (PCR) was carried out on mRNA transcripts extracted from the nodal tissues. Ten out of I I Dukes' B CRC cases had detectable CEA and CK-20 while 6 out of 11 Dukes' B CRC cases had detectable GCC. In general, the difference of re-staged cases when comparing frozen and paraffin-embedded samples was marked; the only statistically significant correlation between frozen and paraffin tissue was for the CEA marker. Our results indicated a high incidence (>50%) of detecting micrometastases in histologically-negative lymph nodes at the molecular level. (C) 2003 Elsevier Science Ltd. All rights reserved.

Iron intake and markers of iron status and risk of Barrett's esophagus and esophageal adenocarcinoma

Objective To investigate the association between iron intake and iron status with Barrett's esophagus (BE) and esophageal adenocarcinoma (EAC).

The expression and prognostic impact of CXC-chemokines in stage II and III colorectal cancer epithelial and stromal tissue

BACKGROUND: The CXC-chemokine expression is linked with colorectal cancer (CRC) progression but their significance in resected CRC is unclear. We explored the prognostic impact of such expression in stage II and III CRC.

Diagnostic and prognostic biomarker discovery strategies for autoimmune disorders.

Current clinical, laboratory or radiological parameters cannot accurately diagnose or predict disease outcomes in a range of autoimmune disorders. Biomarkers which can diagnose at an earlier time point, predict outcome or help guide therapeutic strategies in autoimmune diseases could improve clinical management of this broad group of debilitating disorders. Additionally, there is a growing need for a deeper understanding of multi-factorial autoimmune disorders. Proteomic platforms offering a multiplex approach are more likely to reflect the complexity of autoimmune disease processes. Findings from proteomic based studies of three distinct autoimmune diseases are presented and strategies compared. It is the authors' view that such approaches are likely to be fruitful in the movement of autoimmune disease treatment away from reactive decisions and towards a preventative stand point.

Development and independent validation of a prognostic assay for stage ii colon cancer using formalin-fixed paraffin-embedded tissue

Purpose: Current prognostic factors are poor at identifying patients at risk of disease recurrence after surgery for stage II colon cancer. Here we describe a DNA microarray-based prognostic assay using clinically relevant formalin-fixed paraffin-embedded (FFPE) samples. Patients and Methods: A gene signature was developed from a balanced set of 73 patients with recurrent disease (high risk) and 142 patients with no recurrence (low risk) within 5 years of surgery. Results: The 634-probe set signature identified high-risk patients with a hazard ratio (HR) of 2.62 (P <.001) during cross validation of the training set. In an independent validation set of 144 samples, the signature identified high-risk patients with an HR of 2.53 (P <.001) for recurrence and an HR of 2.21 (P = .0084) for cancer-related death. Additionally, the signature was shown to perform independently from known prognostic factors (P <.001). Conclusion: This gene signature represents a novel prognostic biomarker for patients with stage II colon cancer that can be applied to FFPE tumor samples. © 2011 by American Society of Clinical Oncology.

Patient selection for oncology phase I trials: a multi-institutional study of prognostic factors.

PURPOSE The appropriate selection of patients for early clinical trials presents a major challenge. Previous analyses focusing on this problem were limited by small size and by interpractice heterogeneity. This study aims to define prognostic factors to guide risk-benefit assessments by using a large patient database from multiple phase I trials. PATIENTS AND METHODS Data were collected from 2,182 eligible patients treated in phase I trials between 2005 and 2007 in 14 European institutions. We derived and validated independent prognostic factors for 90-day mortality by using multivariate logistic regression analysis. Results The 90-day mortality was 16.5% with a drug-related death rate of 0.4%. Trial discontinuation within 3 weeks occurred in 14% of patients primarily because of disease progression. Eight different prognostic variables for 90-day mortality were validated: performance status (PS), albumin, lactate dehydrogenase, alkaline phosphatase, number of metastatic sites, clinical tumor growth rate, lymphocytes, and WBC. Two different models of prognostic scores for 90-day mortality were generated by using these factors, including or excluding PS; both achieved specificities of more than 85% and sensitivities of approximately 50% when using a score cutoff of 5 or higher. These models were not superior to the previously published Royal Marsden Hospital score in their ability to predict 90-day mortality. CONCLUSION Patient selection using any of these prognostic scores will reduce non-drug-related 90-day mortality among patients enrolled in phase I trials by 50%. However, this can be achieved only by an overall reduction in recruitment to phase I studies of 20%, more than half of whom would in fact have survived beyond 90 days.