Common Genetic Variation In Cellular Transport Genes and Epithelial Ovarian Cancer (EOC) Risk

Background

Defective cellular transport processes can lead to aberrant accumulation of trace elements, iron, small molecules and hormones in the cell, which in turn may promote the formation of reactive oxygen species, promoting DNA damage and aberrant expression of key regulatory cancer genes. As DNA damage and uncontrolled proliferation are hallmarks of cancer, including epithelial ovarian cancer (EOC), we hypothesized that inherited variation in the cellular transport genes contributes to EOC risk.

Methods

In total, DNA samples were obtained from 14,525 case subjects with invasive EOC and from 23,447 controls from 43 sites in the Ovarian Cancer Association Consortium (OCAC). Two hundred seventy nine SNPs, representing 131 genes, were genotyped using an Illumina Infinium iSelect BeadChip as part of the Collaborative Oncological Gene-environment Study (COGS). SNP analyses were conducted using unconditional logistic regression under a log-additive model, and the FDR q<0.2 was applied to adjust for multiple comparisons.

Results

The most significant evidence of an association for all invasive cancers combined and for the serous subtype was observed for SNP rs17216603 in the iron transporter gene HEPH (invasive: OR = 0.85, P = 0.00026; serous: OR = 0.81, P = 0.00020); this SNP was also associated with the borderline/low malignant potential (LMP) tumors (P = 0.021). Other genes significantly associated with EOC histological subtypes (p<0.05) included the UGT1A (endometrioid), SLC25A45 (mucinous), SLC39A11 (low malignant potential), and SERPINA7 (clear cell carcinoma). In addition, 1785 SNPs in six genes (HEPH, MGST1, SERPINA, SLC25A45, SLC39A11 and UGT1A) were imputed from the 1000 Genomes Project and examined for association with INV EOC in white-European subjects. The most significant imputed SNP was rs117729793 in SLC39A11 (per allele, OR = 2.55, 95% CI = 1.5-4.35, p = 5.66x10^-4).

Conclusion

These results, generated on a large cohort of women, revealed associations between inherited cellular transport gene variants and risk of EOC histologic subtypes.     

Discovery Analysis of TCGA Data Reveals Association between Germline Genotype and Survival in Ovarian Cancer Patients

Background

Ovarian cancer remains a significant public health burden, with the highest mortality rate of all the gynecological cancers. This is attributable to the late stage at which the majority of ovarian cancers are diagnosed, coupled with the low and variable response of advanced tumors to standard chemotherapies. To date, clinically useful predictors of treatment response remain lacking. Identifying the genetic determinants of ovarian cancer survival and treatment response is crucial to the development of prognostic biomarkers and personalized therapies that may improve outcomes for the late-stage patients who comprise the majority of cases.

Methods

To identify constitutional genetic variations contributing to ovarian cancer mortality, we systematically investigated associations between germline polymorphisms and ovarian cancer survival using data from The Cancer Genome Atlas Project (TCGA). Using stage-stratified Cox proportional hazards regression, we examined 650,000 SNP loci for association with survival. We additionally examined whether the association of significant SNPs with survival was modified by somatic alterations.

Results

Germline polymorphisms at rs4934282 (AGAP11/C10orf116) and rs1857623 (DNAH14) were associated with stage-adjusted survival ( = 1.12e-07 and 1.80e-07, FDR  = 1.2e-04 and 2.4e-04, respectively). A third SNP, rs4869 (C10orf116), was additionally identified as significant in the exome sequencing data; it is in near-perfect LD with rs4934282. The associations with survival remained significant when somatic alterations.

Conclusions

Discovery analysis of TCGA data reveals germline genetic variations that may play a role in ovarian cancer survival even among late-stage cases. The significant loci are located near genes previously reported as having a possible relationship to platinum and taxol response. Because the variant alleles at the significant loci are common (frequencies for rs4934282 A/C alleles = 0.54/0.46, respectively; rs1857623 A/G alleles = 0.55/0.45, respectively) and germline variants can be assayed noninvasively, our findings provide potential targets for further exploration as prognostic biomarkers and individualized therapies.     

Gene Expression Profile for Predicting Survival in Advanced-Stage Serous Ovarian Cancer Across Two Independent Datasets

Background

Advanced-stage ovarian cancer patients are generally treated with platinum/taxane-based chemotherapy after primary debulking surgery. However, there is a wide range of outcomes for individual patients. Therefore, the clinicopathological factors alone are insufficient for predicting prognosis. Our aim is to identify a progression-free survival (PFS)-related molecular profile for predicting survival of patients with advanced-stage serous ovarian cancer.

Methodology/Principal Findings

Advanced-stage serous ovarian cancer tissues from 110 Japanese patients who underwent primary surgery and platinum/taxane-based chemotherapy were profiled using oligonucleotide microarrays. We selected 88 PFS-related genes by a univariate Cox model (p<0.01) and generated the prognostic index based on 88 PFS-related genes after adjustment of regression coefficients of the respective genes by ridge regression Cox model using 10-fold cross-validation. The prognostic index was independently associated with PFS time compared to other clinical factors in multivariate analysis [hazard ratio (HR), 3.72; 95% confidence interval (CI), 2.66–5.43; p<0.0001]. In an external dataset, multivariate analysis revealed that this prognostic index was significantly correlated with PFS time (HR, 1.54; 95% CI, 1.20–1.98; p = 0.0008). Furthermore, the correlation between the prognostic index and overall survival time was confirmed in the two independent external datasets (log rank test, p = 0.0010 and 0.0008).

Conclusions/Significance

The prognostic ability of our index based on the 88-gene expression profile in ridge regression Cox hazard model was shown to be independent of other clinical factors in predicting cancer prognosis across two distinct datasets. Further study will be necessary to improve predictive accuracy of the prognostic index toward clinical application for evaluation of the risk of recurrence in patients with advanced-stage serous ovarian cancer.     

Cortical Thickness in Dementia with Lewy Bodies and Alzheimer's Disease: A Comparison of Prodromal and Dementia Stages

Objectives

To assess and compare cortical thickness (CTh) of patients with prodromal Dementia with Lewy bodies (pro-DLB), prodromal Alzheimer''s disease (pro-AD), DLB dementia (DLB-d), AD dementia (AD-d) and normal ageing.

Methods

Study participants(28 pro-DLB, 27 pro-AD, 31 DLB-d, 54 AD-d and 33 elderly controls) underwent 3Tesla T1 3D MRI and detailed clinical and cognitive assessments. We used FreeSurfer analysis package to measure CTh and investigate patterns of cortical thinning across groups.

Results

Comparison of CTh between pro-DLB and pro-AD (p<0.05, FDR corrected) showed more right anterior insula thinning in pro-DLB, and more bilateral parietal lobe and left parahippocampal gyri thinning in pro-AD. Comparison of prodromal patients to healthy elderly controls showed the involvement of the same regions. In DLB-d (p<0.05, FDR corrected) cortical thinning was found predominantly in the right temporo-parietal junction, and insula, cingulate, orbitofrontal and lateral occipital cortices. In AD-d(p<0.05, FDR corrected),the most significant areas affected included the entorhinal cortices, parahippocampal gyri and parietal lobes. The comparison of AD-d and DLB-d demonstrated more CTh in AD-d in the left entorhinal cortex (p<0.05, FDR corrected).

Conclusion

Cortical thickness is a sensitive measure for characterising patterns of grey matter atrophy in early stages of DLB distinct from AD. Right anterior insula involvement may be a key region at the prodromal stage of DLB and needs further investigation.     

Tumor T1 Relaxation Time for Assessing Response to Bevacizumab Anti-Angiogenic Therapy in a Mouse Ovarian Cancer Model

Purpose

To assess whether T₁ relaxation time of tumors may be used to assess response to bevacizumab anti-angiogenic therapy. Procedures: 12 female nude mice bearing subcutaneous SKOV3ip1-LC ovarian tumors were administered bevacizumab (6.25ug/g, n=6) or PBS (control, n=6) therapy twice a week for two weeks. T₁ maps of tumors were generated before, two days, and 2 weeks after initiating therapy. Tumor weight was assessed by MR and at necropsy. Histology for microvessel density, proliferation, and apoptosis was performed.

Results

Bevacizumab treatment resulted in tumor growth inhibition (p<0.04, n=6), confirming therapeutic efficacy. Tumor T₁ relaxation times increased in bevacizumab treated mice 2 days and 2 weeks after initiating therapy (p<.05, n=6). Microvessel density decreased 59% and cell proliferation (Ki67+) decreased 50% in the bevacizumab treatment group (p<.001, n=6), but not apoptosis.

Conclusions

Findings suggest that increased tumor T₁ relaxation time is associated with response to bevacizumab therapy in ovarian cancer model and might serve as an early indicator of response.     

Serum Protein Profile at Remission Can Accurately Assess Therapeutic Outcomes and Survival for Serous Ovarian Cancer

Background

Biomarkers play critical roles in early detection, diagnosis and monitoring of therapeutic outcome and recurrence of cancer. Previous biomarker research on ovarian cancer (OC) has mostly focused on the discovery and validation of diagnostic biomarkers. The primary purpose of this study is to identify serum biomarkers for prognosis and therapeutic outcomes of ovarian cancer.

Experimental Design

Forty serum proteins were analyzed in 70 serum samples from healthy controls (HC) and 101 serum samples from serous OC patients at three different disease phases: post diagnosis (PD), remission (RM) and recurrence (RC). The utility of serum proteins as OC biomarkers was evaluated using a variety of statistical methods including survival analysis.

Results

Ten serum proteins (PDGF-AB/BB, PDGF-AA, CRP, sFas, CA125, SAA, sTNFRII, sIL-6R, IGFBP6 and MDC) have individually good area-under-the-curve (AUC) values (AUC = 0.69–0.86) and more than 10 three-marker combinations have excellent AUC values (0.91–0.93) in distinguishing active cancer samples (PD & RC) from HC. The mean serum protein levels for RM samples are usually intermediate between HC and OC patients with active cancer (PD & RC). Most importantly, five proteins (sICAM1, RANTES, sgp130, sTNFR-II and sVCAM1) measured at remission can classify, individually and in combination, serous OC patients into two subsets with significantly different overall survival (best HR = 17, p<10⁻³).

Conclusion

We identified five serum proteins which, when measured at remission, can accurately predict the overall survival of serous OC patients, suggesting that they may be useful for monitoring the therapeutic outcomes for ovarian cancer.     

Ovarian Carcinoma Subtypes Are Different Diseases: Implications for Biomarker Studies

Background

Although it has long been appreciated that ovarian carcinoma subtypes (serous, clear cell, endometrioid, and mucinous) are associated with different natural histories, most ovarian carcinoma biomarker studies and current treatment protocols for women with this disease are not subtype specific. With the emergence of high-throughput molecular techniques, distinct pathogenetic pathways have been identified in these subtypes. We examined variation in biomarker expression rates between subtypes, and how this influences correlations between biomarker expression and stage at diagnosis or prognosis.

Methods and Findings

In this retrospective study we assessed the protein expression of 21 candidate tissue-based biomarkers (CA125, CRABP-II, EpCam, ER, F-Spondin, HE4, IGF2, K-Cadherin, Ki-67, KISS1, Matriptase, Mesothelin, MIF, MMP7, p21, p53, PAX8, PR, SLPI, TROP2, WT1) in a population-based cohort of 500 ovarian carcinomas that was collected over the period from 1984 to 2000. The expression of 20 of the 21 biomarkers differs significantly between subtypes, but does not vary across stage within each subtype. Survival analyses show that nine of the 21 biomarkers are prognostic indicators in the entire cohort but when analyzed by subtype only three remain prognostic indicators in the high-grade serous and none in the clear cell subtype. For example, tumor proliferation, as assessed by Ki-67 staining, varies markedly between different subtypes and is an unfavourable prognostic marker in the entire cohort (risk ratio [RR] 1.7, 95% confidence interval [CI] 1.2%–2.4%) but is not of prognostic significance within any subtype. Prognostic associations can even show an inverse correlation within the entire cohort, when compared to a specific subtype. For example, WT1 is more frequently expressed in high-grade serous carcinomas, an aggressive subtype, and is an unfavourable prognostic marker within the entire cohort of ovarian carcinomas (RR 1.7, 95% CI 1.2%–2.3%), but is a favourable prognostic marker within the high-grade serous subtype (RR 0.5, 95% CI 0.3%–0.8%).

Conclusions

The association of biomarker expression with survival varies substantially between subtypes, and can easily be overlooked in whole cohort analyses. To avoid this effect, each subtype within a cohort should be analyzed discretely. Ovarian carcinoma subtypes are different diseases, and these differences should be reflected in clinical research study design and ultimately in the management of ovarian carcinoma.     

Multivariate Analysis of Prognostic Biomarkers in Surgically Treated Endometrial Cancer

Objective

The aim of this study was to identify biomarkers with prognostic value in the setting of surgically treated endometrial cancer.

Methods

Medical data for 282 patients with surgically treated endometrial cancer were reviewed retrospectively. Preoperative concentrations of six serum biomarkers (CA125, CA15-3, C-reactive protein [CRP], D-dimer [D-D], platelet-to-lymphocyte ratio [PLR], and neutrophil-to-lymphocyte ratio [NLR]) were analysed to determine potential associations with clinicopathologic characteristics and to assess prognostic values separately via Kaplan-Meier method and multivariate Cox regression.

Results

In univariate analyses, the 5-year overall survival (OS) rate was 86.5% for a maximum follow-up period of 75 months. High concentrations of CA125, CA15-3, CRP, D-D, PLR, and NLR each proved significantly predictive of poor survival (log-rank test, P<0.01). CRP and D-D were identified as independent prognosticators, using a Cox regression model. Study patients were then stratified (based on combined independent risk factors) into three tiers (P<0.001), marked by 5-year OS rates of 92.1%, 78.4%, and 33.3%.

Conclusions

All serum biomarkers assessed (CA125, CA15-3, CRP, D-D, PLR, and NLR) proved to be valid prognostic indices of surgically treated endometrial cancer. A novel prognostic grouping system, incorporating independent risk factors (CRP and D-D Concentrations), may have merit in assessing these patients preoperatively, providing a biologic basis for improved clinical staging.     

Analysis of a Urinary Biomarker Panel for Clinical Outcomes Assessment in Cirrhosis

Background

Biomarkers are potentially useful in assessment of outcomes in patients with cirrhosis, but information is very limited. Given the large number of biomarkers, adequate choice of which biomarker(s) to investigate first is important.

Aim

Analysis of potential usefulness of a panel of urinary biomarkers in outcome assessment in cirrhosis.

Patients and Methods

Fifty-five patients with acute decompensation of cirrhosis were studied: 39 had Acute Kidney Injury (AKI) (Prerenal 12, type-1 HRS (hepatorenal syndrome) 15 and Acute Tubular Necrosis (ATN) 12) and 16 acute decompensation without AKI. Thirty-four patients had Acute-on-chronic liver failure (ACLF). A panel of 12 urinary biomarkers was assessed, using a multiplex assay, for their relationship with ATN, ACLF and mortality.

Results

Biomarker with best accuracy for ATN diagnosis was NGAL (neutrophil-gelatinase associated lipocalin): 36 [26-125], 104 [58-208] and 1807 [494-3,716] μg/g creatinine in Prerenal-AKI, type-1 HRS and ATN, respectively; p<0.0001 (AUROC 0.957). Other attractive biomarkers for ATN diagnosis were IL-18, albumin, trefoil-factor-3 (TFF-3) and glutathione-S-transferase-π (GST-π) Biomarkers with less accuracy for ATN AUCROC<0.8 were β2-microglobulin, calbindin, cystatin-C, clusterin and KIM-1 (kidney injury molecule-1). For ACLF, the biomarker with the best accuracy was NGAL (ACLF vs. No-ACLF: 165 [67-676] and 32 [19-40] μg/g creatinine; respectively; p<0.0001; AUROC 0.878). Interestingly, other biomarkers with high accuracy for ACLF were osteopontin, albumin, and TFF-3. Biomarkers with best accuracy for prognosis were those associated with ACLF.

Conclusions

A number of biomarkers appear promising for differential diagnosis between ATN and other types of AKI. The most interesting biomarkers for ACLF and prognosis are NGAL, osteopontin, albumin, and TFF-3. These results support the role of major inflammatory reaction in the pathogenesis of ACLF.     

Low Serum High Density Lipoprotein Cholesterol Concentration is an Independent Predictor for Enhanced Inflammation and Endothelial Activation

Background

Inflammation, endothelial activation and oxidative stress have been established as key events in the initiation and progression of atherosclerosis. High-density lipoprotein cholesterol (HDL-c) is protective against atherosclerosis and coronary heart disease, but its association with inflammation, endothelial activation and oxidative stress is not well established.

Objectives

(1) To compare the concentrations of biomarkers of inflammation, endothelial activation and oxidative stress in subjects with low HDL-c compared to normal HDL-c; (2) To examine the association and correlation between HDL-c and these biomarkers and (3) To determine whether HDL-c is an independent predictor of these biomarkers.

Methods

422 subjects (mean age±SD = 43.2±11.9years) of whom 207 had low HDL-c concentrations (HDL-c <1.0mmol/L and <1.3mmol/L for males and females respectively) and 215 normal controls (HDL-c ≥1.0 and ≥1.3mmol/L for males and females respectively) were recruited in this study. The groups were matched for age, gender, ethnicity, smoking status, diabetes mellitus and hypertension. Fasting blood samples were collected for analysis of biomarkers of inflammation [high-sensitivity C-reactive protein (hsCRP) and Interleukin-6 (IL-6)], endothelial activation [soluble Vascular Cell Adhesion Molecule-1 (sVCAM-1), soluble Intercellular Adhesion Molecule-1 (sICAM-1) and E-selectin)] and oxidative stress [F2-Isoprostanes, oxidized Low Density Lipoprotein (ox-LDL) and Malondialdehyde (MDA)].

Results

Subjects with low HDL-c had greater concentrations of inflammation, endothelial activation and oxidative stress biomarkers compared to controls. There were negative correlations between HDL-c concentration and biomarkers of inflammation (IL-6, p = 0.02), endothelial activation (sVCAM-1 and E-selectin, p = 0.029 and 0.002, respectively), and oxidative stress (MDA and F₂-isoprostane, p = 0.036 and <0.0001, respectively). Multiple linear regression analysis showed HDL-c as an independent predictor of IL-6 (p = 0.02) and sVCAM-1 (p<0.03) after correcting for various confounding factors.

Conclusion

Low serum HDL-c concentration is strongly correlated with enhanced status of inflammation, endothelial activation and oxidative stress. It is also an independent predictor for enhanced inflammation and endothelial activation, which are pivotal in the pathogenesis of atherosclerosis and atherosclerosis-related complications.     

Screening and Identification of Biomarkers in Ascites Related to Intrinsic Chemoresistance of Serous Epithelial Ovarian Cancers

Objective

The ability to predict responses to chemotherapy for serous epithelial ovarian cancer (EOC) would be valuable since intrinsically chemoresistant EOC patients (persistent or recurrent disease within 6 months) gain little benefit from standard chemotherapy. The aim of this study was to screen and identify distinctive biomarkers in ascites of serous EOC associated with intrinsic chemoresistance.

Methods

Protein samples from ascites of 12 chemosensitive and 7 intrinsically chemoresistant serous EOC patients were analyzed using two-dimensional fluorescence difference in gel electrophoresis (2-D DIGE) coupled with matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF/TOF MS). Furthermore, the identified proteins were validated by ELISA in ascites samples from 19 chemosensitive and 9 intrinsically chemoresistant EOC patients.

Results

The number of spots detected in all 2-D DIGE gels ranged from 1523–1711 using DeCyder software analysis. Thirty-four spots were differentially expressed based on the criteria of an average ratio of more than 1.5 and a student t-test P value <0.05. After MALDI-TOF/TOF MS analysis, 11 differentially expressed proteins, including 3 up-regulated and 8 down-regulated proteins, in ascites of chemoresistant tumors were successfully identified. Of the four selected proteins (ceruloplasmin, apoliprotein A-IV, transthyretin and haptoglobin) in ascites tested by ELISA, only ceruloplasmin was present at significantly different levels between the chemoresistant and chemosensitive ascites samples with average concentrations of 192.2 µg/ml and 157.5 µg/ml, respectively (P = 0.001).

Conclusion

The significantly up-regulated level of ceruloplasmin in the ascites fluid of intrinsic chemoresistant serous EOC patients suggests its potential as a prognostic biomarker for responses to chemotherapy. This finding prompts further investigation with a larger study in order to validate the clinical utility of ceruloplasmin.     

Early Clinical Response after 2 Weeks of Sorafenib Therapy Predicts Outcomes and Anti-Tumor Response in Patients with Advanced Hepatocellular Carcinoma

Background & Aims

We evaluated the relationship between the early clinical response after 2 weeks of sorafenib therapy and the outcomes and anti-tumor response in patients with advanced hepatocellular carcinoma.

Methods

Fifty-seven patients who had intrahepatic hypervascular hepatocellular carcinoma and Child-Pugh (CP) class A disease at baseline were enrolled in this prospective, multicenter, observational, non-interventional study. As an early clinical response after 2 weeks of sorafenib therapy, changes in intra-tumor blood flow on contrast-enhanced computed tomography (CE-CT), alpha-fetoprotein (AFP) levels, and remnant liver function were investigated.

Results

After 2 weeks of sorafenib therapy, there were 26 patients (45.6%) without disappearance of arterial tumor enhancement on CE-CT, 15 patients (26.3%) with an AFP ratio of >1.2, and seven patients (12.3%) with two or more increments in the CP score. Multivariate analysis showed that the absence of disappearance of arterial tumor enhancement on CE-CT, AFP ratio of >1.2, and two or more increments in the CP score after 2 weeks of sorafenib therapy were significant and independent predictors of worse survival. Upon scoring these three variables as "poor prognostic factors", patients with poor prognostic score 4, 3 or 2 (n = 17) had significantly worse outcomes and a significantly higher progressive disease (PD) rate based on modified Response Evaluation Criteria in Solid Tumors at 6 weeks after sorafenib therapy than those with poor prognostic score 1 or 0 (n = 40) (median overall survival: 194 days vs. 378 days; p = 0.0010, PD rate: 70.6% vs. 20.0%; p = 0.0003, respectively).

Conclusions

Changes in intra-tumor blood flow on CE-CT, AFP levels, and remnant liver function after 2 weeks of sorafenib therapy may be useful for predicting the outcomes and anti-tumor response to sorafenib in patients with advanced hepatocellular carcinoma.     

Evaluation of mRNA Biomarkers to Identify Risk of Hospital Acquired Infections in Children Admitted to Paediatric Intensive Care Unit

Objectives

Hospital-acquired infections (HAI) are associated with significant mortality and morbidity and prolongation of hospital stay, adding strain on limited hospital resources. Despite stringent infection control practices some children remain at high risk of developing HAI. The development of biomarkers which could identify these patients would be useful. In this study our objective was to evaluate mRNA candidate biomarkers for HAI prediction in a pediatric intensive care unit.

Design

Serial blood samples were collected from patients admitted to pediatric intensive care unit between March and June 2012. Candidate gene expression (IL1B, TNF, IL10, CD3D, BCL2, BID) was quantified using RT-qPCR. Comparisons of relative gene expression between those that did not develop HAI versus those that did were performed using Mann Whitney U-test.

Patients

Exclusion criteria were: age <28 days or ≥16 years, expected length of stay < 24 hours, expected survival < 28 days, end-stage renal disease and end-stage liver disease. Finally, 45 children were included in this study.

Main Results

The overall HAI rate was 30% of which 62% were respiratory infections. Children who developed HAI had a three-fold increase in hospital stay compared to those who did not (27 days versus 9 days, p<0.001). An increased expression of cytokine genes (IL1B and IL10) was observed in patients who developed HAI, as well as a pro-apoptosis pattern (higher expression of BID and lower expression of BCL2). CD3D, a key TCR co-factor was also significantly down-modulated in patients who developed HAI.

Conclusions

To our knowledge, this is the first study of mRNA biomarkers of HAI in the paediatric population. Increased mRNA expressions of anti-inflammatory cytokine and modulation of apoptotic genes suggest the development of immunosuppression in critically ill children. Immune monitoring using a panel of genes may offer a novel stratification tool to identify HAI risk.     

Potential tumor biomarkers identified in ovarian cyst fluid by quantitative proteomic analysis,iTRAQ

Background

Epithelial-derived ovarian adenocarcinoma (EOC) is the most deadly gynecologic tumor, and the principle cause of the poor survival rate is diagnosis at a late stage. Screening and diagnostic biomarkers with acceptable specificity and sensitivity are lacking. Ovarian cyst fluid should harbor early ovarian cancer biomarkers because of its closeness to the tumor. We investigated ovarian cyst fluid as a source for discovering biomarkers for use in the diagnosis of EOC.

Results

Using quantitative mass spectrometry, iTRAQ MS, we identified 837 proteins in cyst fluid from benign, EOC stage I, and EOC stage III. Only patients of serous histology were included in the study. Comparing the benign (n = 5) with the malignant (n = 10) group, 87 of the proteins were significantly (p < 0.05) differentially expressed. Two proteins, serum amyloid A-4 (SAA4) and astacin-like metalloendopeptidase (ASTL), were selected for verification of the iTRAQ method and external validation with immunoblot in a larger cohort with mixed histology, in plasma (n = 68), and cyst fluid (n = 68). The protein selections were based on either high significance and high fold change or abundant appearance and several peptide recognitions in the sample sets (p = 0.04, FC = 1.95) and (p < 0.001, FC = 8.48) for SAA4 and ASTL respectively. Both were found to be significantly expressed (p < 0.05), but the methods did not correlate concerning ASTL.

Conclusions

Fluid from ovarian cysts connected directly to the primary tumor harbor many possible new tumor-specific biomarkers. We have identified 87 differentially expressed proteins and validated two candidates to verify the iTRAQ method. However several of the proteins are of interest for validation in a larger setting.     

Long-Term Cochlear Implant Outcomes in Children with GJB2 and SLC26A4 Mutations

Objectives

To investigate speech and language outcomes in children with cochlear implants (CIs) who had mutations in common deafness genes and to compare their performances with those without mutations.

Study Design

Prospective study.

Methods

Patients who received CIs before 18 years of age and had used CIs for more than 3 years were enrolled in this study. All patients underwent mutation screening of three common deafness genes: GJB2, SLC26A4 and the mitochondrial 12S rRNA gene. The outcomes with CIs were assessed at post-implant years 3 and 5 using the Categories of Auditory Performance (CAP) scale, Speech Intelligibility Rating (SIR) scale, speech perception tests and language skill tests.

Results

Forty-eight patients were found to have confirmative mutations in GJB2 or SLC26A4, and 123 without detected mutations were ascertained for comparison. Among children who received CIs before 3.5 years of age, patients with GJB2 or SLC26A4 mutations showed significantly higher CAP/SIR scores than those without mutations at post-implant year 3 (p = 0.001 for CAP; p = 0.004 for SIR) and year 5 (p = 0.035 for CAP; p = 0.038 for SIR). By contrast, among children who received CIs after age 3.5, no significant differences were noted in post-implant outcomes between patients with and without mutations (all p > 0.05).

Conclusion

GJB2 and SLC26A4 mutations are associated with good post-implant outcomes. However, their effects on CI outcomes may be modulated by the age at implantation: the association between mutations and CI outcomes is observed in young recipients who received CIs before age 3.5 years but not in older recipients.     

The Practicability of a Novel Prognostic Index (PI) Model and Comparison with Nottingham Prognostic Index (NPI) in Stage I–III Breast Cancer Patients Undergoing Surgical Treatment

Background

Previous studies have indicated the prognostic value of various laboratory parameters in cancer patients. This study was to establish a prognostic index (PI) model for breast cancer patients based on the potential prognostic factors.

Methods

A retrospective study of 1661 breast cancer patients who underwent surgical treatment between January 2002 and December 2008 at Sun Yat-sen University Cancer Center was conducted. Multivariate analysis (Cox regression model) was performed to determine the independent prognostic factors and a prognostic index (PI) model was devised based on these factors. Survival analyses were used to estimate the prognostic value of PI, and the discriminatory ability of PI was compared with Nottingham Prognostic Index (NPI) by evaluating the area under the receiver operating characteristics curves (AUC).

Results

The mean survival time of all participants was 123.6 months. The preoperative globulin >30.0g/L, triglyceride >1.10mmol/L and fibrinogen >2.83g/L were identified as risk factors for shorter cancer-specific survival. The novel prognostic index model was established and enrolled patients were classified as low- (1168 patients, 70.3%), moderate- (410 patients, 24.7%) and high-risk groups (83 patients, 5.0%), respectively. Compared with the low-risk group, higher risks of poor clinical outcome were indicated in the moderate-risk group [Hazard ratio (HR): 1.513, 95% confidence interval (CI): 1.169–1.959, p = 0.002] and high-risk group (HR: 2.481, 95%CI: 1.653–3.724, p< 0.001).

Conclusions

The prognostic index based on three laboratory parameters was a novel and practicable prognostic tool. It may serve as complement to help predict postoperative survival in breast cancer patients.     

Comparison of Gene Expression by Sheep and Human Blood Stimulated with the TLR4 Agonists Lipopolysaccharide and Monophosphoryl Lipid A

Background

Animal models that mimic human biology are important for successful translation of basic science discoveries into the clinical practice. Recent studies in rodents have demonstrated the efficacy of TLR4 agonists as immunomodulators in models of infection. However, rodent models have been criticized for not mimicking important characteristics of the human immune response to microbial products. The goal of this study was to compare genomic responses of human and sheep blood to the TLR4 agonists lipopolysaccharide (LPS) and monophosphoryl lipid A (MPLA).

Methods

Venous blood, withdrawn from six healthy human adult volunteers (~ 28 years old) and six healthy adult female sheep (~3 years old), was mixed with 30 μL of PBS, LPS (1μg/mL) or MPLA (10μg/mL) and incubated at room temperature for 90 minutes on a rolling rocker. After incubation, 2.5 mL of blood was transferred to Paxgene Blood RNA tubes. Gene expression analysis was performed using an Agilent Bioanalyzer with the RNA6000 Nano Lab Chip. Agilent gene expression microarrays were scanned with a G2565 Microarray Scanner. Differentially expressed genes were identified.

Results

11,431 human and 4,992 sheep probes were detected above background. Among them 1,029 human and 175 sheep genes were differentially expressed at a stringency of 1.5-fold change (p<0.05). Of the 175 sheep genes, 54 had a known human orthologue. Among those genes, 22 had > 1.5-fold changes in human samples. Genes of major inflammatory mediators, such as IL-1, IL-6 and IL-8, TNF alpha, NF-kappaB, ETS2, PTGS2, PTX3, CXCL16, KYNU, and CLEC4E were similarly (>2-fold) upregulated by LPS and MPLA in both species.

Conclusion

The genomic responses of peripheral blood to LPS and MPLA in sheep are quite similar to those observed in humans, supporting the use of the ovine model for translational studies that mimic human inflammatory diseases and the study of TLR-based immunomodulators.