Predictors of Raised Viral Load during Antiretroviral Therapy in Patients with and without Prior Antiretroviral Use: A Cross-Sectional Study

Objectives

In Lagos, Nigeria, Médecins Sans Frontières (MSF) and the Ministry of Health (MoH) commenced free antiretroviral treatment (ART) in a hospital-based clinic. We performed a cross-sectional study to compare factors associated with raised viral load between patients with (“experienced”) and without (“naïve”) prior antiretroviral (ARV) exposure at commencement of ART at the clinic. We also examined factors influencing ARV adherence in experienced patients prior to clinic entry.

Methods

We included adult patients receiving ART from MSF who answered a questionnaire about previous antiretroviral use. Multivariate logistic regression was used to estimate odds ratios (OR) for raised viral load (≥1000 copies/mL).

Results

1246 (96%) patients answered: 1075 (86%) reported no, and 171 (14%) some, prior ARV exposure. ARV-naïve patients were more immunosuppressed at baseline: 65% vs 37% (p<0.001) had CD4<200; 17% vs 9% (p = 0.013) were WHO stage 4. Proportionately more experienced than naïve patients had raised viral loads (20% vs 9%, p<0.001) on ART in the MSF/MoH clinic. Raised viral load was associated with prior ARV experience (adjusted OR = 3.74, 95%CI 2.09–6.70, p<0.001) and complete interruption of current ART (adjusted OR = 3.71, 95%CI 2.06–6.68, p<0.001). Higher CD4 at time of VL and a higher self-rated score of recent adherence were associated with lower OR of a raised viral load. Among experienced patients who missed pills before joining MSF/MoH, most common reasons were because ARVS were not affordable (58%) or available (33%), with raised viral load associated with being unsure how to take them (OR = 3.16, 95%CI 1.10–9.12, p = 0.033).

Conclusions

Patients previously exposed to ARVs had increased OR of raised viral load. The cost and availability of ARVs were common reasons for missing ARVs before joining the MSF/MoH clinic, and inadequate patient knowledge was associated with raised viral load.     

Human ovarian cancer, lymphoma spleen, and bovine milk GlcNAc:beta1,4Gal/GalNAc transferases: two molecular species in ovarian tumor and induction of GalNAcbeta1,4Glc synthesis by alpha-lactalbumin

Affinity Gel-UDP was utilized to purify GlcNAc:beta1,4Gal/GalNAc transferases (Ts) from human lymphoma spleen, ovarian tumor, and ovarian cancer sera. Mn(2+) was found to be an absolute requirement for activity. Two molecular species containing both beta1,4Gal/GalNAc-T activities were discernible when the purified ovarian tumor microsomal enzyme was subjected to Sephacryl S-100 HR column chromatography as well as native polyacylamide gel-electrophoresis. Acceptor specificity studies of the affinity-purified lymphoma spleen and ovarian tumor microsomal enzymes and the conventionally purified, as well as the cloned, bovine milk GlcNAc:beta1,4Gal-Ts using a number of synthetic acceptors showed that the beta(1,6)-linked GlcNAc moiety to alpha-GalNAc was the most efficient acceptor. As compared to the purified milk enzyme, the recombinant form exhibited sixfold GlcNAc:beta1,4 GalNAc-T activity and up to eightfold GlcNAc6SO3beta-:beta1,4Gal-T activity. Further, the recombinant enzyme catalyzed the transfer of GalNAc to the terminal beta-linked GlcNAc6SO3 moiety. Alpha-lactalbumin (alpha-LA) inhibited up to 85%, the transfer of Gal to the GlcNAc moiety linked either to Man or GlcNAc. On the contrary, alpha-LA had no significant influence on the transfer of GalNAc to the above acceptors. alpha-LA had no appreciable effect on the recombinant enzyme, except for the transfer of Gal or GalNAc to Glc. Both alpha- and beta-glucosides, as well as alpha-N-acetylglucosaminide, did not serve as acceptors.     

SCNVSim: somatic copy number variation and structure variation simulator

Background

Somatically acquired structure variations (SVs) and copy number variations (CNVs) can induce genetic changes that are directly related to tumor genesis. Somatic SV/CNV detection using next-generation sequencing (NGS) data still faces major challenges introduced by tumor sample characteristics, such as ploidy, heterogeneity, and purity. A simulated cancer genome with known SVs and CNVs can serve as a benchmark for evaluating the performance of existing somatic SV/CNV detection tools and developing new methods.

Results

SCNVSim is a tool for simulating somatic CNVs and structure variations SVs. Other than multiple types of SV and CNV events, the tool is capable of simulating important features related to tumor samples including aneuploidy, heterogeneity and purity.

Conclusions

SCNVSim generates the genomes of a cancer cell population with detailed information of copy number status, loss of heterozygosity (LOH), and event break points, which is essential for developing and evaluating somatic CNV and SV detection methods in cancer genomics studies.     

Diagnosis of early stage ovarian cancer by 1H NMR metabonomics of serum explored by use of a microflow NMR probe

We show that (1)H NMR based metabonomicsof serum allows the diagnosis of early stage I/II epithelial ovarian cancer (EOC) required for successful treatment. Because patient specimens are highly precious, we conducted an exploratory study using a microflow probe requiring only 20 μL of serum. By use of logistic regression on principal components (PCs) of the NMR profiles, we built a 4-variable model for early stage EOC prediction (training set: 69 EOC specimens, 84 healthy controls; test set: 40 EOC, 44 controls) with operating characteristics estimated for the test set at 80% specificity [95% confidence interval (CI): 65-90%], 63% sensitivity (95% CI: 46-77%), and an area under the Receiver Operator Characteristic Curve (AUC) of 0.796. Independent validation (50 EOC, 50 controls) of the model yielded 95% specificity (95% CI: 86-99.5%), 68% sensitivity (95% CI: 53-80%) and an AUC of 0.949. A test on cancer type specificity showed that women diseased with renal cell carcinoma were not incorrectly diagnosed with EOC, indicating that metabonomics bears significant potential for cancer type-specific diagnosis. Our model can potentially be applied for women at high risk for EOC, and our study promises to contribute to developing a screening protocol for the general population.     

Split T cell tolerance against a self/tumor antigen: spontaneous CD4+ but not CD8+ T cell responses against p53 in cancer patients and healthy donors

Analyses of NY-ESO-1-specific spontaneous immune responses in cancer patients revealed that antibody and both CD4(+) and CD8(+) T cell responses were induced together in cancer patients. To explore whether such integrated immune responses are also spontaneously induced for other tumor antigens, we have evaluated antibody and T cell responses against self/tumor antigen p53 in ovarian cancer patients and healthy individuals. We found that 21% (64/298) of ovarian cancer patients but no healthy donors showed specific IgG responses against wild-type p53 protein. While none of 12 patients with high titer p53 antibody showed spontaneous p53-specific CD8(+) T cell responses following a single in vitro sensitization, significant p53-specific IFN-γ producing CD4(+) T cells were detected in 6 patients. Surprisingly, similar levels of p53-specific CD4(+) T cells but not CD8(+) T cells were also detected in 5/10 seronegative cancer patients and 9/12 healthy donors. Importantly, p53-specific CD4(+) T cells in healthy donors originated from a CD45RA(-) antigen-experienced T cell population and recognized naturally processed wild-type p53 protein. These results raise the possibility that p53-specific CD4(+) T cells reflect abnormalities in p53 occurring in normal individuals and that they may play a role in processes of immunosurveillance or immunoregulation of p53-related neoplastic events.     

Complex Segregation Analysis of Pedigrees from the Gilda Radner Familial Ovarian Cancer Registry Reveals Evidence for Mendelian Dominant Inheritance

Background

Familial component is estimated to account for about 10% of ovarian cancer. However, the mode of inheritance of ovarian cancer remains poorly understood. The goal of this study was to investigate the inheritance model that best fits the observed transmission pattern of ovarian cancer among 7669 members of 1919 pedigrees ascertained through probands from the Gilda Radner Familial Ovarian Cancer Registry at Roswell Park Cancer Institute, Buffalo, New York.

Methodology/Principal Findings

Using the Statistical Analysis for Genetic Epidemiology program, we carried out complex segregation analyses of ovarian cancer affection status by fitting different genetic hypothesis-based regressive multivariate logistic models. We evaluated the likelihood of sporadic, major gene, environmental, general, and six types of Mendelian models. Under each hypothesized model, we also estimated the susceptibility allele frequency, transmission probabilities for the susceptibility allele, baseline susceptibility and estimates of familial association. Comparisons between models were carried out using either maximum likelihood ratio test in the case of hierarchical models, or Akaike information criterion for non-nested models. When assessed against sporadic model without familial association, the model with both parent-offspring and sib-sib residual association could not be rejected. Likewise, the Mendelian dominant model that included familial residual association provided the best-fitting for the inheritance of ovarian cancer. The estimated disease allele frequency in the dominant model was 0.21.

Conclusions/Significance

This report provides support for a genetic role in susceptibility to ovarian cancer with a major autosomal dominant component. This model does not preclude the possibility of polygenic inheritance of combined effects of multiple low penetrance susceptibility alleles segregating dominantly.     

Metabolomic prediction of endometrial cancer

Introduction

Endometrial cancer (EC) is associated with metabolic disturbances including obesity, diabetes and metabolic syndrome. Identifying metabolite biomarkers for EC detection has a crucial role in reducing morbidity and mortality.

Objective

To determine whether metabolomic based biomarkers can detect EC overall and early-stage EC.

Methods

We performed NMR and mass spectrometry based metabolomic analyses of serum in EC cases versus controls. A total of 46 early-stage (FIGO stages I–II) and 10 late-stage (FIGO stages III–IV) EC cases constituted the study group. A total of 60 unaffected control samples were used. Patients and controls were divided randomly into a discovery group (n?=?69) and an independent validation group (n?=?47). Predictive algorithms based on biomarkers and demographic characteristics were generated using logistic regression analysis.

Results

A total of 181 metabolites were evaluated. Extensive changes in metabolite levels were noted in the EC versus the control group. The combination of C14:2, phosphatidylcholine with acyl-alkyl residue sum C38:1 (PCae C38:1) and 3-hydroxybutyric acid had an area under the receiver operating characteristics curve (AUC) (95% CI)?=?0.826 (0.706–0.946) and a sensitivity?=?82.6%, and specificity?=?70.8% for EC overall. For early EC prediction: BMI, C14:2 and PC ae C40:1 had an AUC (95% CI)?=?0.819 (0.689–0.95) and a sensitivity?=?72.2% and specificity?=?79.2% in the validation group.

Conclusions

EC is characterized by significant perturbations in important cellular metabolites. Metabolites accurately detected early-stage EC cases and EC overall which could lead to the development of non-invasive biomarkers for earlier detection of EC and for monitoring disease recurrence.

     

Metabolomics of biomarker discovery in ovarian cancer: a systematic review of the current literature

Introduction

Metabolomics is the emerging member of “omics” sciences advancing the understanding, diagnosis and treatment of many cancers, including ovarian cancer (OC).

Objectives

To systematically identify the metabolomic abnormalities in OC detection, and the dominant metabolic pathways associated with the observed alterations.

Methods

An electronic literature search was performed, up to and including January 15th 2016, for studies evaluating the metabolomic profile of patients with OC compared to controls. QUADOMICS tool was used to assess the quality of the twenty-three studies included in this systematic review.

Results

Biological samples utilized for metabolomic analysis include: serum/plasma (n = 13), urine (n = 4), cyst fluid (n = 3), tissue (n = 2) and ascitic fluid (n = 1). Metabolites related to cellular respiration, carbohydrate, lipid, protein and nucleotide metabolism were significantly altered in OC. Increased levels of tricarboxylic acid cycle intermediates and altered metabolites of the glycolytic pathway pointed to perturbations in cellular respiration. Alterations in lipid metabolism included enhanced fatty acid oxidation, abnormal levels of glycerolipids, sphingolipids and free fatty acids with common elevations of palmitate, oleate, and myristate. Increased levels of glutamine, glycine, cysteine and threonine were commonly reported while enhanced degradations of tryptophan, histidine and phenylalanine were found. N-acetylaspartate, a brain amino acid, was found elevated in primary and metastatic OC tissue and ovarian cyst fluid. Further, elevated levels of ketone bodies including 3-hydroxybutyrate were commonly reported. Increased levels of nucleotide metabolites and tocopherols were consistent through out the studies.

Conclusion

Metabolomics presents significant new opportunities for diagnostic biomarker development, elucidating previously unknown mechanisms of OC pathogenesis.

     

DNA hypomethylation-mediated activation of Cancer/Testis Antigen 45 (CT45) genes is associated with disease progression and reduced survival in epithelial ovarian cancer

Epithelial ovarian cancer (EOC) is a highly lethal malignancy due to a lack of early detection approaches coupled with poor outcomes for patients with clinically advanced disease. Cancer-testis (CT) or cancer-germline genes encode antigens known to generate spontaneous anti-tumor immunity in cancer patients. CT45 genes are a recently discovered 6-member family of X-linked CT genes with oncogenic function. Here, we determined CT45 expression in EOC and fully defined its epigenetic regulation by DNA methylation. CT45 was silent and hypermethylated in normal control tissues, but a large subset of EOC samples showed increased CT45 expression in conjunction with promoter DNA hypomethylation. In contrast, copy number status did not correlate with CT45 expression in the TCGA database for EOC. CT45 promoter methylation inversely correlated with both CT45 mRNA and protein expression, the latter determined using IHC staining of an EOC TMA. CT45 expression was increased and CT45 promoter methylation was decreased in late-stage and high-grade EOC, and both measures were associated with poor survival. CT45 hypomethylation was directly associated with LINE-1 hypomethylation, and CT45 was frequently co-expressed with other CT antigen genes in EOC. Decitabine treatment induced CT45 mRNA and protein expression in EOC cells, and promoter transgene analyses indicated that DNA methylation directly represses CT45 promoter activity. These data verify CT45 expression and promoter hypomethylation as possible prognostic biomarkers, and suggest CT45 as an immunological or therapeutic target in EOC. Treatment with decitabine or other epigenetic modulators could provide a means for more effective immunological targeting of CT45.     

Regulating mammalian target of rapamycin to tune vaccination-induced CD8(+) T cell responses for tumor immunity

Vaccine strategies aimed at generating CD8(+) T cell memory responses are likely to show augmented efficacy against chronic challenges like tumor. The abundance in variety of memory CD8(+) T cells behooves development of vaccine strategies that generate distinct memory responses and evaluate them for tumor efficacy. In this study, we demonstrate the ability of a variety of rapamycin treatment regimens to regulate virus vaccination-induced CD8(+) T cell memory responses and tumor efficacy. Strikingly, a short course of high-dose, but not low-dose, rapamycin treatment transiently blocks viral vaccination-induced mammalian target of rapamycin activity in CD8(+) T cells favoring persistence and Ag-recall responses over type 1 effector maturation; however, prolonged high-dose rapamycin administration abrogated memory responses. Furthermore, a short course of high-dose rapamycin treatment generated CD8(+) T cell memory responses that were independent of IL-15 and IL-7 and were programmed early for sustenance and greater tumor efficacy. These results demonstrate the impact a regimen of rapamycin treatment has on vaccine-induced CD8(+) T cell responses and indicates that judicious application of rapamycin can augment vaccine efficacy for chronic challenges.