PATIENTS AND METHODS: CGA data was collected from 249 Asian patients aged 70 years or older. Nutritional risk was assessed based on the Nutrition Screening Initiative (NSI) checklist. Univariate and multivariate logistic regression analyses were applied to assess the association between patient clinical factors together with domains within the CGA and moderate to high nutritional risk. Goodness of fit was assessed using Hosmer-Lemeshow test. Discrimination ability was assessed based on the area under the receiver operating characteristics curve (AUC). Internal validation was performed using simulated datasets via bootstrapping.
RESULTS: Among the 249 patients, 184 (74%) had moderate to high nutritional risk. Multivariate logistic regression analysis identified stage 3-4 disease (Odds Ratio [OR] 2.54; 95% CI, 1.14-5.69), ECOG performance status of 2-4 (OR 3.04; 95% CI, 1.57-5.88), presence of depression (OR 5.99; 95% CI, 1.99-18.02) and haemoglobin levels <12 g/dL (OR 3.00; 95% CI 1.54-5.84) as significant independent factors associated with moderate to high nutritional risk. The model achieved good calibration (Hosmer-Lemeshow test's p = 0.17) and discrimination (AUC = 0.80). It retained good calibration and discrimination (bias-corrected AUC = 0.79) under internal validation.
CONCLUSION: Having advanced stage of cancer, poor performance status, depression and anaemia were found to be predictors of moderate to high nutritional risk. Early identification of patients with these risk factors will allow for nutritional interventions that may improve treatment tolerance, quality of life and survival outcomes.
METHODS: Restriction fragment length polymorphism-polymerase chain reaction (RFLP-PCR) was used to genotype all the aforementioned gene polymorphisms. Kaplan-Meier survival function, log-rank test and Cox regression were used to investigate the effect of gene polymorphisms on the all-cause survival of NPC.
RESULTS: NPC cases carrying T/T genotype of ITGA2 C807T have poorer all-cause survival compared to those with C/C genotypes, with an adjusted HR of 2.06 (95% CI = 1.14-3.72) in individual model. The 5-year survival rate of C/C carriers was 55% compared to those with C/T and T/T where the survival rates were 50% and 43%, respectively.
CONCLUSION: The finding from the present study showed that ITGA2 C807T polymorphism could be potentially useful as a prognostic biomarker for NPC. However, the prognostic value of ITGA2 C807T polymorphism has to be validated by well-designed further studies with larger patient numbers.
METHODS: In total, 80 samples of tumor and matched adjacent normal tissues were collected from breast cancer patients at Seberang Jaya Hospital (SJH) and Kepala Batas Hospital (KBH), both in Penang, Malaysia. The protein expression profiles of breast cancer and normal tissues were mapped by sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE). The Gel-Eluted Liquid Fractionation Entrapment Electrophoresis (GELFREE) Technology System was used for the separation and fractionation of extracted proteins, which also were analyzed to maximize protein detection. The protein fractions were then analyzed by tandem mass spectrometry (LC-MS/MS) analysis using LC/MS LTQ-Orbitrap Fusion and Elite. This study identified the proteins contained within the tissue samples using de novo sequencing and database matching via PEAKS software. We performed two different pathway analyses, DAVID and STRING, in the sets of proteins from stage 2 and stage 3 breast cancer samples. The lists of molecules were generated by the REACTOME-FI plugin, part of the CYTOSCAPE tool, and linker nodes were added in order to generate a connected network. Then, pathway enrichment was obtained, and a graphical model was created to depict the participation of the input proteins as well as the linker nodes.
RESULTS: This study identified 12 proteins that were detected in stage 2 tumor tissues, and 17 proteins that were detected in stage 3 tumor tissues, related to their normal counterparts. It also identified some proteins that were present in stage 2 but not stage 3 and vice versa. Based on these results, this study clarified unique proteins pathways involved in carcinogenesis within stage 2 and stage 3 breast cancers.
CONCLUSIONS: This study provided some useful insights about the proteins associated with breast cancer carcinogenesis and could establish an important foundation for future cancer-related discoveries using differential proteomics profiling. Beyond protein identification, this study considered the interaction, function, network, signaling pathway, and protein pathway involved in each profile. These results suggest that knowledge of protein expression, especially in stage 2 and stage 3 breast cancer, can provide important clues that may enable the discovery of novel biomarkers in carcinogenesis.
METHODS: Using a panel of antibodies to CD10, Bcl-6, MUM1 and CD138, consecutive cases of primary UAT DLBCL were stratified into subgroups of germinal centre B-cell-like (GCB) and non-GCB, phenotype profile patterns A, B and C, as proposed by Hans et al. and Chang et al., respectively. EBER in situ hybridisation technique was applied for the detection of EBV in the tumours.
RESULTS: In this series of 32 cases of UAT DLBCL, 34% (11/32) were GCB, and 66% (21/32) were non-GCB types; 59% (19/32) had combined patterns A and B, and 41% (13/32) had pattern C. Statistical analysis revealed no significant difference in the occurrence of these prognostic subgroups in the UAT when compared with series of de novo DLBCL from all sites. There was also no site difference in phenotype protein expressions, with the exception of MUM1. EBER in situ hybridisation stain demonstrated only one EBV infected case.
CONCLUSIONS: Prognostic subgroup distribution of UAT DLBCL is similar to de novo DLBCL from all sites, and EBV association is very infrequent.