Programmed cell death 6 interacting protein (PDCD6IP) and Rabenosyn-5 (ZFYVE20) are potential urinary biomarkers for upper gastrointestinal cancer

PURPOSE: Cancer of the upper digestive tract (uGI) is a major contributor to cancer-related death worldwide. Due to a rise in occurrence, together with poor survival rates and a lack of diagnostic or prognostic clinical assays, there is a clear need to establish molecular biomarkers. EXPERIMENTAL DESIGN: Initial assessment was performed on urine samples from 60 control and 60 uGI cancer patients using MS to establish a peak pattern or fingerprint model, which was validated by a further set of 59 samples. RESULTS: We detected 86 cluster peaks by MS above frequency and detection thresholds. Statistical testing and model building resulted in a peak profiling model of five relevant peaks with 88% overall sensitivity and 91% specificity, and overall correctness of 90%. High-resolution MS of 40 samples in the 2-10 kDa range resulted in 646 identified proteins, and pattern matching identified four of the five model peaks within significant parameters, namely programmed cell death 6 interacting protein (PDCD6IP/Alix/AIP1), Rabenosyn-5 (ZFYVE20), protein S100A8, and protein S100A9, of which the first two were validated by Western blotting. CONCLUSIONS AND CLINICAL RELEVANCE: We demonstrate that MS analysis of human urine can identify lead biomarker candidates in uGI cancers, which makes this technique potentially useful in defining and consolidating biomarker patterns for uGI cancer screening

Second echelon node predicts metastatic involvement of additional axillary nodes following sentinel node biopsy in early breast cancer

BACKGROUND : In many patients with early breast cancer, the sentinel lymph node (SLN) is the sole site of regional nodal metastasis. This subgroup of patients may not benefit from completion axillary lymph node dissection (CALND). AIMS: This pilot study evaluates the status of 2nd echelon (station) lymph nodes in the axilla as a predictor of additional positive nodes in the axilla in the presence of sentinel node metastasis. SETTINGS AND DESIGN: Cross-sectional study of 40 breast cancer patients. MATERIALS AND METHODS: Forty patients with invasive breast cancer underwent SLN biopsy followed by 2nd echelon lymph node biopsy in the same sitting. SLN mapping was performed using a combined technique of isosulfan blue and 99 mTc-sulfur colloid. SLNs (Station I) were defined as blue and/or hot nodes. These nodes were then injected with 0.1 ml of blue dye using a fine needle and their efferent lymphatic was traced to identify the Station II nodes. Then a complete ALND was performed. All the specimens were sent separately for histopathological evaluation. RESULTS : SLNs (Station I nodes) were successfully identified in 98% (39/40) patients. Of the 17 patients with a positive SLN, 8 (47%) patients had no further positive nodes in the axilla, 9 (53%) patients had additional metastasis in nonsentinel lymph nodes upon CALND. Station II nodes were identified in 76% (13/17) patients with a positive SLN. Station II nodes accurately predicted the status of the remaining axilla in 92% patients (12/13). STATISTICAL ANALYSIS : We calculated the Sensitivity, Negative predictive value, Positive predictive value, False negative rate and Identification rate. CONCLUSION : Station II nodes may predict metastatic involvement of additional nodes in the axilla

Pancreatic cancer and predictors of survival: comparing the CA 19-9/bilirubin ratio with the McGill Brisbane Symptom Score

AbstractIntroductionFew tools predict survival from pancreatic cancer (PAC). The McGill Brisbane Symptom Score (MBSS) based on symptoms at presentation (weight loss, pain, jaundice and smoking) was recently validated. The present study compares the ability of four strategies to predict 9-month survival: MBSS, carbohydrate antigen 19-9 (CA 19-9) alone, CA19-9-to-bilirubin ratio and a combination of MBSS and the CA19-9-to-bilirubin ratio.MethodologyA retrospective review of 133 patients diagnosed with PAC between 2005 and 2011 was performed. Survival was determined from the Quebec civil registry. Blood CA 19-9 and bilirubin values were collected (n = 52) at the time of diagnosis. Receiver-operating characteristic (ROC) curves were used to determine a cutoff for optimal test characteristics of CA 19-9 and CA19-9-to-total bilirubin ratio in predicting survival at 9 months. Predictive characteristics were then calculated for the four strategies.ResultsOf the four strategies, the one with the greatest negative predictive value was the MBSS: negative predictive value (NPV) was 90.2% (76.9–97.3%) and the positive likelihood ratio (LR) was the greatest. The ability of CA 19-9 levels alone, at baseline, to predict survival was low. For the CA19-9-to-bilirubin ratio, the test characteristics improved but remained non-significant. The best performing strategy according to likelihood ratios was the combined MBSS and CA19-9 to the bilirubin ratio.ConclusionCA19-9 levels and the CA19-9-to-bilirubin ratio are poor predictors of survival for PAC, whereas the MBSS is a far better predictor, confirming its clinical value. By adding the CA19-9-to-bilirubin ratio to the MBSS the predictive characteristics improved

Biofluid Diagnostics by FTIR Spectroscopy: A Platform Technology for Cancer Detection

Fourier Transform Infrared Spectroscopy (FTIR) has been largely employed by scientific researchers to improve diagnosis and treatment of cancer, using various biofluids and tissues. The technology has proved to be easy to use, rapid and cost-effective for analysis on human blood serum to discriminate between cancer versus healthy control samples. The high sensitivity and specificity achievable during samples classification aided by machine learning algorithms, offers an opportunity to transform cancer referral pathways, as it has been demonstrated in a unique and recent prospective clinical validation study on brain tumours. We herein highlight the importance of early detection in cancer research using FTIR, discussing the technique, the suitability of serum for analysis and previous studies, with special focus on pre-clinical factors and clinical translation requirements and development