Mycobacterium bovis bacillus Calmette–Guerin (BCG) remains at the forefront of immunotherapy for treating bladder cancer patients. However, the incidence of recurrence and progression to invasive cancer is commonly observed. There are no established effective intravesical therapies available for patients, whose tumors recur following BCG treatment, representing an important unmet clinical need. In addition, there are very limited options for patients who do not respond to or tolerate chemotherapy due to toxicities, resulting in poor overall treatment outcomes. Within this context, nanotechnology is an emergent and promising tool for: (1) controlling drug release for extended time frames, (2) combination therapies due to the ability to encapsulate multiple drugs simultaneously, (3) reducing systemic side effects, (4) increasing bioavailability, (5) and increasing the viability of various routes of administration. Moreover, bladder cancer is often characterized by high mutation rates and over expression of tumor antigens on the tumor cell surface. Therapeutic targeting of these biomolecules may be improved by nanotechnology strategies. In this mini-review, we discuss how nanotechnology can help overcome current obstacles in bladder cancer treatment, and how nanotechnology can facilitate combination chemotherapeutic and BCG immunotherapies for the treatment of non-muscle invasive urothelial bladder cancer. Bladder cancer (BC) is the second most common malignancy of the urinary tract, the fourth most common cancer in men with a yearly incidence rate of 330, 380 cases, and the 11th most common among women with a yearly incidence rate of 99,413. Worldwide, carcinomas of the bladder represent the ninth most common cause of cancer, with 430,000 patients diagnosed with BC annually ] are tumors that are restricted to the mucosa, while T1 and T2 are tumors that invade the lamina propria and the muscularis propria, respectively  BC cases are non-muscle-invasive bladder cancers (NMIBC) at diagnosis with the other 25% representing muscle invasive bladder cancers (MIBC) or metastatic cancers  to facilitate removal of the visible tumor  is the treatment of choice for patients with high-risk NMIBC. BCG immunotherapy is the gold standard treatment for NMIBC due to its ability to reduce recurrence and progression to MIBC  to increase the therapeutic effectiveness and reduce adverse effects of chemotherapy by targeting chemotherapeutic agents to a specific tissue and increasing its bioavailability  also show promise for delivery of quimiotherapic agents to the target tissue  combined with nanotechnology is another promising approach for BC treatment. RNAi technology can be used to inhibit tumor growth through messenger RNA inhibition of several activated oncogenes , produce the opposite effect of RNAi by inducing gene expression  NPs encapsulating BCG developed with the purpose of increasing the antitumor efficacy of BCG following intravesical administration have demonstrated significant advantages for the treatment of BC  used as an immunomodulator in cancer patients  or skeleton. Utilization of octaarginine-modified liposomes incorporating BCG-CW (R8-liposome-BCG-CW) results in increased immunotherapeutic potential of BCG-CW for NMIBC through cellular internalization resulting in growth inhibition Considering the promising results demonstrated by utilizing nanotechnology to develop new BC therapies, including success application of those approaches to BCG therapy, we believe that nanotechnology will provide significant advances for improving BC treatment. In this review, we described the main advances and applications of nanotechnology tools for development of novel treatments against BC, providing evidence that nanotechnology has contributed greatly to this effort by controlling drug release for longer periods, enabling the encapsulation of multiple drugs simultaneously, decreasing side effects, and increasing bioavailability. Nevertheless, we believe that combination therapies show more promise for effective treatment of this complex disease than individual approaches Figure .Although nanotechnology has resulted in significant progress for BCG immunotherapy, including increasing immunotherapeutic effects, prolonging exposure of the bladder tissue, and reducing adverse side effects, we believe this approach can be further enhanced through intravesical BCG delivery using NPs functionalized with antibody molecules against highly expressed receptors on the surface of BC cells such as EGFR to further target drug delivery and avoid systemic exposure and clearance of NPs from the body. Therefore, considering the emerging and motivating results using these approaches to treat BC, we believe that BCG delivery using NPs functionalized with monoclonal antibodies, in particular anti-EGFR, will provide a significantly improved delivery system for treatment of human BC.JB drafted the manuscript. CB wrote the introduction section, KB wrote the bladder cancer treatments section, and all authors, mainly AP, SG, TC, FS, and KB were responsible for conception, manuscript review, and critical intellectual input.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Over the past decade, research into the unique ways, in which cancer cells skew their metabolism, has had a renaissance—for the repeated time over more than 80 years since the discovery of an inherent preference for glycolysis. Importantly, the Warburg effect that arises in primary neoplasms is not the sole prominent metabolic phenomenon. Once the transformed cells are shed from their initial growth and begin the process of metastasis, their energy requirements change and they adapt to the increased demand for adenosine triphosphate, which if not satisfied would lead to anoikis. At that stage, oxidoreductases and the respiratory chain are activated. Furthermore, the intrinsic metabolic characteristics of tumor cells may be influenced by extrinsic factors, comprising metabolite secretions from stromal cells or acidification and nutrient deprivation in the late-stage hypoxic environment. While there is metabolic adjustment in cancer cells throughout the disease history, its phenotypic manifestation changes at various times. This stage selectivity has implications for pharmacotherapy ambitions. Recent research has rediscovered the metabolic changes that occur in tumor cells during transformation. Numerous publications have studied the glycolytic preference of cellular energy pathways that is prevalent even under normoxic conditions. Yet, this so-called Warburg effect  is not the only metabolic alteration that can arise in cancer cells. While some skewing of the metabolism seems to be inevitable in transformation, its presentation changes over the course of the disease. It is important to differentiate the various manifestations of cancer-associated metabolic adjustments .The metabolic pathways within tumor cells can be altered endogenously, which is the case in the Warburg effect . During tumor progression, when deadhesion occurs it poses a dramatically increased adenosine triphosphate (ATP) requirement that forces the upregulation of energy production. Alternatively, the microenvironment can affect the tumor cell metabolism when stromal cells secrete abundant lactate that is then taken up by the transformed cells. Obviously, the hypoxic, acidic, low-glucose environment of late-stage cancers also has a direct effect on the metabolic processes inside the cancer cells. The connotations of these four scenarios  differ among each other in underlying mechanisms and resulting phenotypes Table . ConsecuThe evolution of respiration has equipped us with a tremendous advantage. The oxidative breakdown of glucose, the fuel in bioenergetics, yields 36–38 molecules of ATP per molecule of glucose, as opposed to 4–6 molecules of ATP resulting from glycolysis. Initially, it seemed paradoxical that tumors, which need more chemical energy than healthy cells due to their rapid proliferation, would preferentially engage the much less efficient glycolytic energy production. Two fundamental questions need to be addressed to understand this Warburg effect (aerobic glycolysis). What causes it and what are its consequences?c oxidase complex embedded in the inner mitochondrial membrane. The P53-inducible gene TIGAR codes for a protein that downregulates the cellular fructose-2,6-bisphosphate levels. As fructose-2,6-bisphosphate is an allosteric effector of 6-phosphofructose-1-kinase (PFK-1), which promotes glycolysis, TIGAR expression attenuates this pathway. Loss of P53 function is common in human cancers. TP53-deficient tumor cells do not have functional SCO2 or TIGAR and display a glycolytic metabolism phenotype . Furthermore, pyruvate kinase M2 expression provides a selective growth advantage for tumor cells in vivo .The reliance by rapidly growing cancer cells on anaerobic glycolysis seems counterintuitive. Hence, teleological explanations for why and how the preferred glycolytic metabolism in transformation may advance tumor initiation or tumor growth have been scant. Two possible justifications associate cancer cell glycolysis either with mitochondrial hyperpolarization and anti-apoptosis or with the synthesis of essential biomolecules. In some cancers, the aerobic glycolysis may support oncogenic transcription.via peroxide to Kv channels is involved in oxygen sensing as well as in the promotion of apoptosis. Cancer cells would be at risk of cell death if the rapid proliferation relied on energy production by the mitochondria, thus generating high levels of superoxide and—derived from it—hydrogen peroxide. However, mitochondrial hyperpolarization occurs in these transformed cells and leads to anti-apoptosis, because low hydrogen peroxide and high NFAT suppress the plasma membrane potassium channels (The cell membrane contains a voltage-gated family of potassium channels (Kv), which due to its redox sensitivity can be regulated by the mitochondria. As a by-product of respiration, the mitochondria produce superoxide, which may be dismutated to hydrogen peroxide that activates these channels, thereby regulating the voltage-dependent influx of calcium and the activity of caspases. The connection of mitochondria channels .Among the genes that can initiate tumorigenesis, many are closely linked to metabolic regulation. In this context, the biosynthetic processes required to divide and create daughter cells are equally important for tumor growth as is bioenergetics. Because of the preference for aerobic glycolysis in cancer cells, the glucose-derived metabolite feed into the tricarboxylic acid cycle is reduced. Thus, cancer cells typically have an increased reliance on alternative biomolecules to replenish Krebs cycle intermediates, and the amino acid glutamine is such a metabolite . The anaThe transcription factors YAP and TAZ, mediators of the Hippo pathway, promote organ growth, tumor cell proliferation, and cancer aggressiveness. When cells actively incorporate glucose and route it through glycolysis, YAP/TAZ transcription is fully active. When glucose metabolism is blocked or glycolysis is reduced, YAP/TAZ activity is decreased. Accordingly, glycolysis is required to sustain YAP/TAZ pro-tumorigenic functions, and YAP/TAZ is required for the full deployment of glucose growth-promoting activity .The dissemination of transformed cells is an integral characteristic of cancers, but it is absent from benign growths. Metastases manifest clinically at advanced disease stages. While the major limiting factor in cancer spread is the death of the tumor cells before their implantation into target organs –16, a frTo accomplish survival after deadhesion, metastasis genes affect metabolic adjustments that are distinct from the Warburg effect. Untransformed non-hematopoietic cells (with the exception of tissue-resident stem cells) undergo anoikis consecutive to losing contact with their substratum. In these healthy cells, anchorage deprivation causes an impairment in glucose transport, a deficit in ATP  and consecutive programed cell death (anoikis) . Cancer via osteopontin-c upregulates peroxides as well as intermediates of the hexose monophosphate shunt and glycolysis, which utilize the available glucose and can feed into the tricarboxylic acid cycle. Consecutively, the cellular ATP levels are elevated  can be activated by hydrogen peroxide in the mitochondrial membrane and exert anti-apoptotic effects, thus linking bioenergetics and survival. Either one of these interactions (potassium channels or caveolin) could account for the oxidative effects of osteopontin-c.Elevated levels of hydrogen peroxide mediate metabolic changes that allow increased energy production, deadherent survival, and consecutive metastatic spread. Whereas research has widely focused on the potential pro-apoptotic functions of hydrogen peroxide , a growing literature that describes peroxide as essential for cancer metastasis  has recevia peroxides. The mitochondria generate reactive oxygen species, predominantly through their complex III. These are required for K-RAS-mediated anchorage-independent growth, which is accomplished via regulation of the ERK/MAPK signaling pathway  to target these α subunits for proteasomal degradation, thus preempting a low-oxygen response. Under hypoxic conditions, prolyl hydroxylase activity is suppressed, resulting in HIF-α stabilization and translocation to the nucleus. There, HIF-α subunits dimerize with aryl hydrocarbon receptor nuclear translocator, recruit transcriptional coactivators such as p300/CBP, and bind to hypoxia-responsive elements in target genes to activate transcription. They induce gene expression programs, which regulate glucose uptake and metabolism to affect proliferation and survival.Once a cancer mass has grown to a certain size, the genetic programs of transformation act in a non-conducive environment. The characteristic metabolic conditions of advanced tumors  activate unique intracellular signals . BecauseHIF activity in hypoxic cells promotes the conversion of glucose to lactate, thus preventing its utilization in the Krebs cycle. A loss of HIF regulation by VHL, and resultant HIF hyper-activation, is sufficient to switch the input onto the Krebs cycle from mostly glucose derived to glutamine derived. Intracellular citrate deficiency may promote this switch. Cancer cells in this state use glutamine to generate citrate and lipids through the reductive carboxylation of glutamine-derived α-ketoglutarate. Consistently, VHL deficiency sensitizes cancer cells to the inhibition of glutaminase, the enzyme that catalyzes the first step of glutamine metabolism .We have learnt that the intermediary pathways for energy generation are skewed in cancer cells, such that they favor aerobic glycolysis in primary tumors and stimulation of ATP generation in disseminating cancer cells. High-profile publications on glycolysis versus oxidative respiration have attracted scientists in the field and have stimulated additional research into energy pathways. Because the stage was set, the same core pathways that had been pinpointed early on have been investigated over and over Figure . The selBesides the major energy source glucose, transformed cells can use alternative energy supplies. Non-glycolytic pathways are operational in cancers even under hypoxic conditions. Among them, fatty acid oxidation may be a dominant bioenergetic pathway in prostate cancer cells . Fatty avia receptors for PDGF, insulin, MET, and CSF-1, the proto-oncogene product phosphatidylinositol 3′-kinase (PI 3-K) has important metabolic functions  is regulated by the convergence of mevalonate and Hippo pathways onto YAP/TEAD, which controls RHAMM transcription and consequently supports breast cancer cell migration and invasion. Expression of the breast cancer susceptibility gene RHAMM is tightly controlled in healthy tissues but elevated in many tumors, contributing to tumorigenesis and metastases  is an inhibitor of mitochondrial pyruvate dehydrogenase kinase, which inhibits pyruvate dehydrogenase, a gatekeeping enzyme for the entry of pyruvate into the tricarboxylic acid cycle. DCA treatment may reactivate mitochondrial respiration in tumor cells, induce their selective killing, and suppress cancer growth . The preDichloroacetate is used to treat hyperglycemia in diabetes mellitus, because it stimulates peripheral glucose utilization and inhibits gluconeogenesis through its effect on pathways of the intermediary metabolism. By decreasing circulating lipid and lipoprotein levels, it suppresses lipogenesis and cholesterolgenesis in patients with acquired or hereditary disorders of the lipoprotein metabolism. By stimulating the activity of pyruvate dehydrogenase, DCA facilitates the oxidation of lactate and decreases morbidity in acquired and congenital forms of lactic acidosis. The drug is dehalogenated to monochloroacetate and glyoxylate, from which it can be further catabolized to glycolate, glycine, oxalate, and carbon dioxide. At sustained, higher doses, there is an increased risk of neurotoxicity and gait disturbance. DCA can cause a reversible peripheral neuropathy that may be related to thiamine deficiency and may be ameliorated or prevented with thiamine supplementation. At high doses, the drug itself can be carcinogenic.The indazole carboxylate lonamidamine suppresses aerobic glycolysis in cancer cells but enhances it in untransformed cells, likely through the inhibition of mitochondrial hexokinase. This causes a reduction in cellular ATP levels. The drug may also act as a putative ligand for adenine nucleotide translocator  that triggers apoptosis. Lonidamine is in clinical trials for the treatment of brain tumors.N--acetamide) is a sulfonamide derivate that inhibits tumor-associated CAIX , metastasizing cancer cells (peroxide-driven ATP production), tumor cells under stromal influence , and late-stage cancers (hypoxia) so as to direct anti-metabolism agents safely and efficaciously.Historically, the challenge for anticancer therapy has been the lack of qualitative differences between tumor cells and host cells. In infectious diseases, antibiotic therapy has been so successful because it targets molecules of the pathogens that are highly distinct from humans, thus achieving very manageable adverse effects. As cancer cells are derived from self, this benefit was long not available to anticancer drug treatment. Therefore, conventional chemotherapy drugs, which rather non-specifically target cell division or DNA synthesis, have been fraught with high toxicity  and moderate efficacy due to inevitable dose limitations. One of the major accomplishments in translating molecular biology research into clinical applications has been the targeting of mutated molecules that are causative and specific for cancer cells, including BCR-ABL, mutated EGFR, and HER2. Similarly, anti-metastasis drugs neutralize molecules that are rarely expressed in the adult healthy organism, such as VEGF or integrin αThe author confirms being the sole contributor of this work and approved it for publication.The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Precision medicine attempts to individualize cancer therapy by matching tumor-specific genetic changes with effective targeted therapies. A crucial first step in this process is the reliable identification of cancer-relevant variants, which is considerably complicated by the impurity and heterogeneity of clinical tumor samples. We compared the impact of admixture of non-cancerous cells and low somatic allele frequencies on the sensitivity and precision of 19 state-of-the-art SNV callers. We studied both whole exome and targeted gene panel data and up to 13 distinct parameter configurations for each tool. We found vast differences among callers. Based on our comprehensive analyses we recommend joint tumor-normal calling with MuTect, EBCall or Strelka for whole exome somatic variant calling, and HaplotypeCaller or FreeBayes for whole exome germline calling. For targeted gene panel data on a single tumor sample, LoFreqStar performed best. We further found that tumor impurity and admixture had a negative impact on precision, and in particular, sensitivity in whole exome experiments. At admixture levels of 60% to 90% sometimes seen in pathological biopsies, sensitivity dropped significantly, even when variants were originally present in the tumor at 100% allele frequency. Sensitivity to low-frequency SNVs improved with targeted panel data, but whole exome data allowed more efficient identification of germline variants. Effective somatic variant calling requires high-quality pathological samples with minimal admixture, a consciously selected sequencing strategy, and the appropriate variant calling tool with settings optimized for the chosen type of data. The promise of personalized cancer medicine is to formulate effective treatment options based on the individual genetic makeup of patient and tumor –5. UnderThis issue has immediate consequences for the methodologies used to analyze next-generation sequencing data from tumors. They must be able to reliably separate a few tens to hundreds of tumor-relevant mutations from thousands of mostly non-informative germline mutations , 11, andIdeally, the pipeline identifies all cancer-relevant mutations present in the tumor  but avoids calling misleading false positives due to artifacts and contaminations in the raw data . Previous comparisons of SNV callers –20 alreaOur results provide novel benchmarking data sets that can be used for future testing exercises of heterogeneous and admixed tumor data and represent best practice guidelines to deal with the challenges encountered in clinical tumor samples, particularly those posed by low somatic variant frequencies.To emulate realistic genomes of cancer patients, we implanted 5,381,311 SNVs, insertions and deletions representing the European-Caucasian ancestry  into theFor each tumor data set, we used Wessim  to generWe specifically included callers that could deal with paired tumor-control data and that could account for tumor heterogeneity. Moreover, we considered software that is actively maintained and that could be easily installed and run without errors. Our test considered SNV calling methodologies ranging from Bayesian models and heuristic models to statistical tests on variant counts. Using ten simulated tumor admixture data sets and the control, we performed three sets of benchmarking experiments: germline SNV calling from a single (non-tumor) sample, calling any SNVs (germline and somatic) from a single tumor sample without control sample, and somatic SNV calling from paired tumor-control samples. We thus evaluated 11 germline, 10 tumor-only, and 13 paired tumor-control SNV callers. Next, we investigated how the SNV callers that had the best results on the synthetic data performed on realistic laboratory data. To be able to calculate sensitivity and precision, we obtained two genomic data sets, HG001 and HG002, for which highly reliable golden standard SNVs are available. The Genome in a Bottle consortium made these high-quality data sets  publicly available specifically for the purpose of analytical validation . To prodFor each caller and data set we compared the SNVs obtained from the caller with the known “gold standard” variants we implanted into the data sets. For the germline and somatic callers we compared against the known germline and somatic SNVs, respectively. For the tumor callers, we restricted the evaluation on somatic SNVs as the performance of calling germline SNVs, which are more abundant compared to somatic SNVs, would mask the performance of calling somatic SNVs. We determined the number of (i) true positives (TP), or SNVs called at the correct position; (ii) false positives (FP), or SNVs called but not present in the gold standard set and (iii) false negatives (FN), SNVs that were not called by the evaluated method. Using these counts, we calculated (i) sensitivity, We obtained one control and ten tumor data sets with admixture levels varying between 0 (pure tumor) and 90% . For each caller, we compared a set of 1 to 13 parameter settings, depending on the number of available parameters . In the For germline data, all but three callers had sensitivity and precision above 90% and 99% on exome data, respectively, and even higher average sensitivities on panel data for similar precision  admixture, all tools together were able to find 90.1% of SNVs . At 90% We next looked at the performance of SNV calling on a single tumor exome sample. Although these tools called both somatic and germline SNVs, we focused the sensitivity and precision analysis on the somatic calls only. Here, we also saw declining sensitivity with increasing admixture levels for all tools . The effAlthough this is rarely done in clinical practice, we also investigated the sensitivity and precision of calling SNVs from paired tumor-control targeted gene panels. In these experiments, we observed an increased senstivity compared to the exome data, particularly for increasing levels of contamination of normal tissue . InteresFinally, we investigated the performance of SNV calling on more typical (unpaired) targeted gene panel data, which excludes a control sample but has increased coverage. With this type of data we also saw high variability among callers and declining sensitivity with increasing admixture levels for all tools . PrecisiOur comparison of parameter settings across tools and data types showed that parameters related to base-quality cutoffs can be used to tweak the balance between finding low-frequency SNVs and avoiding false positives. Too high cutoffs resulted in loss of low-frequency SNVs, whereas too low ones introduced false positives. Nevertheless, in germline exome data, base quality thresholds only slightly lowered the sensitivity of HaplotypeCaller and SAMtools. In all of the somatic SNV experiments, raising base quality and variant coverage thresholds increased sensitivity to somatic variants at the cost of additional false positives. At the highest admixture levels (starting from 70%), the influence of parameters was negligible because the calls were dominated by false positives.The GiaB consortium provides reference DNA with associated validated SNV calls that can be used as golden standard for evaluating novel analytical approaches against a known standard. We tested LoFreqStar, VarDict and VarScan, which performed best on targeted panel sequencing data derived from the synthetic genomes, on sequences derived from 4 replicates of 1:7 proportional mixtures of the DNA of the two GiaB reference samples , Fig 6. Genomic pipelines in cancer precision medicine need to discover all cancer-relevant mutations while avoiding misleading false positives. This study aimed to investigate the impact of low somatic allele frequencies and tumor-germline admixture on the sensitivity and precision of somatic SNV calling. Based on a comprehensive and systematic analysis of 19 state-of-the-art tools each with up to 13 distinct parameter settings, we here present a set of best practice recommendations for optimizing somatic SNV calling from tumor samples.We found vast differences among tools regarding the number and type of calls across germline and somatic SNVs, both in whole exome and in targeted panel data. Previous studies also reported that somatic callers tend to identify a small, common set of high-confidence core mutations , 18 combBased on our analysis of about 3,700 SNV calling experiments and the literature, we therefore recommend the following best practices. For whole exome germline data, HaplotypeCaller and FreeBayes are the most reliable tools. On germline gene panel data, SAMtools is slightly more sensitive than the other two. For tumor whole exome data, joint tumor-normal calling using MuTect optimizes sensitivity and minimizes false positives. However, MuTect does not report germline variants, which could be hereditary cancer-relevant mutations such as BRCA1, BRCA2, TP53 or HER2 –50. FailThe analysis of parameter settings across tools further demonstrated that the quality and purity of the sample had a much stronger influence on the performance of the SNV callers than particular settings. Similarly, algorithm choice had more impact on the discovery of low-frequency variants than tweaking parameters such as minimal variant coverage and base quality scores in any particular tool. Nevertheless, adjusting these parameters for the tool that is optimal for a given type of data does allow the researcher to balance sensitivity and precision according to his or her preferences, but this only impacts a very small  fraction of the total variants called by any method.Combining caller outputs for somatic variant calling did not improve results much, as the most sensitive callers called both “core” and low-frequency mutations, whereas other tools produced many false positives. This remains a contentious issue, with several authors agreeing in favor , 17, 20 Our results emphasize that precision medicine pipelines need to pay special attention to admixture of tumor samples with germline cells, especially for exome data with low coverage. Admixture may be caused by biological factors, as tumor tissues often contain epithelial, stromal and vascular cells that play a role in tumor growth and progression . MoreoveTaken together, our results caution that admixture represents a significant quality issue for precision medicine that may hamper the ability of pipelines to deliver complete, reliable and actionable results. Unfortunately, current clinical practice often does not foresee later genetic analysis . The futFinally, low frequency variants may also be an intrinsic property of genetically heterogeneous tumors –14. At tIn conclusion, our study of SNV callers within the context of low-frequency somatic variants showed that developing reliable genomic pipelines is far from trivial. Whole exome analyses offer the advantage of covering a large part of the genome, which increases the likelihood of finding (rare) cancer-relevant mutations. It often includes a non-cancerous tissue or blood sample that allows efficient separation of somatic from germline mutations and the determination of cancer-predisposing germline mutations. Targeted gene panels are more cost-effective than whole exome data and are more sensitive to low-frequency variants due to higher coverage, but do not always allow efficient identification of germline variants and by definition miss somatic variants in genomic regions not covered by the panel. Based on a case-per-case basis, genomic pipelines need to balance a tradeoff between sensitivity to low-frequency variants and calling too many false positives, according to the type, quality and admixture of the data that is being analyzed. Finally, we caution that the reliability of precision medicine pipelines depends at least as much on the quality and purity of the tumor sample as on optimization of the methods and parameters within the pipeline. Using a standard pipeline that is not optimized for the data at hand as a first step in precision medicine risks missing relevant cancer mutations and may negatively impact the quality of treatment recommendations.S1 FigConcordance among SNVs callers for exome and targeted gene panel data. A. Germline exome (left) and germline targeted gene panel (right). B. Paired tumor-control exome, C. single tumor targeted gene panel, D. paired tumor-control targeted gene panel data, and E. single tumor targeted gene panel. Each slice represents the proportion of calls shared by the corresponding number of callers relative to the total calls made by all callers. The legend gives the number of callers supporting a set of calls. Numbers above pie charts represent different admixture levels (0 to 90%).(TIFF)Click here for additional data file.S1 FileMolecular Health Pan-Cancer Gene Panel covering 542 cancer-relevant genes.(TXT)Click here for additional data file.S2 FileContains the parameters used for running the SNV callers.(ZIP)Click here for additional data file.S3 FileContains the evaluation of SNV calls per caller and parameter set combination.(ZIP)Click here for additional data file.


Differences in chromatin states are critical to the multiplicity of cell states. Recently genome-wide histone modification maps of diverse human developmental stages and tissues have been charted.http://www.tongjidmb.com/human/index.html). It also includes genome-wide expression data of different conditions, reference gene annotations, GC content and CpG island information. By providing an intuitive and user-friendly query interface, iHMS enables comprehensive query and comparative analysis based on gene names, genomic region locations, histone modification marks and cell types. Moreover, it offers an efficient browser that allows users to visualize and compare multiple genome-wide histone modification maps and related expression profiles across different developmental stages and tissues.To facilitate the investigation of epigenetic dynamics and regulatory mechanisms in cellular differentiation processes, we developed iHMS, an integrated human histone modification database that incorporates massive histone modification maps spanning different developmental stages, lineages and tissues (iHMS is of great helpfulness to understand how global histone modification state transitions impact cellular phenotypes across different developmental stages and tissues in the human genome. This extensive catalog of histone modification states thus presents an important resource for epigenetic and developmental studies. Nearly all cells of an organism share the same genome but exhibit diverse phenotypes and carry out dramatically different functions. In eukaryotic cells the genome is organized into chromatin. Cell-type specific chromatin organization enables differential access and activity of regulatory elements and the manifestation of unique cellular phenotypes , 2. ReceLarge-scale mapping of histone modifications has emerged as a powerful means for characterizing chromatin structures. The technology of chromatin immunoprecipitation followed by sequencing (Chip-Seq) can interrogate chromatin structure across the genome , which iBearing these promises, a fundamental problem is to integrate histone modification maps of diverse developmental stages and tissues in the public domain. Over the past years, a few epigenomic databases have been developed for the integration of various human epigenomic data from different tissues and experiments –25. ThesHere, we report a database iHMS that integrates human histone modification data covering diverse developmental stages and primary tissues. It also includes genome-wide expression data of different conditions and reference genes, GC content and CpG island information. iHMS has an intuitive and user-friendly query interface, which enables both basic and advanced search based on gene names/genomic region locations, histone modification marks and cell types, as three major query options. Moreover, it allows users to visualize and compare multiple genome-wide histone modification maps and related expression profiles at different developmental stages and tissues via a powerful browser. Thus, iHMS can provide a systematic view of the dynamic histone modification landscapes during cellular differentiation and development, which is useful for researchers to compare the variability of histone modification states with underlying gene expression, to identify cell-type-specific histone modification states and their regulatory implications for cellular phenotypes across different developmental stages and tissues.In human, the study of epigenetic mechanisms underlying the regulation of early embryonic development requires access to large amounts of epigenomic data in different developmental stages. iHMS is a web-based integrated platform that enables users to query, compare, analyze and visualize genome-wide histone modification patterns across different human developmental stages and representative tissues. Figure In the data preprocessing layer, we reorganize and compress the collected raw data. This process is of great importance to reduce the redundancy among different datasets, to improve query efficiency, and to facilitate data usage in the follow-up analysis. In the second layer, the compressed histone modification maps are imported and stored into a relational database. All histone modification maps are stored in tables to enable efficient management, search and representation. The related expression data and genomic annotations, including reference genes, GC content and CpG island information, are stored in file system for quick access by the JBrowse visualization system . To bridThe integrated system iHMS is built with LampServer (Linux+Apache+MySQL +PHP). LampServer is a fast and open source development environment, allowing users to develop web applications with Apache, PHP and MySQL. Raw datasets of histone modification maps are reorganized and compressed by Perl and Python scripts. The core database of iHMS is implemented with MySQL relational database system (version 5.6.12). To facilitate efficient management and query, all histone modification maps are stored in MySQL tables, whereas the expression data and genomic annotations are stored in files for quick access by JBrowse. The computing unit is implemented by PHP, a server-side scripting language designed for web development. The browser-based interfaces are developed with a collection of web development techniques, including JavaScript, CSS and Ajax. These powerful techniques make data access simple and efficient. To display histone modification profiles of specified genomic regions, we apply Highcharts.js and CanvasJS, which are both effective and open-source painting galleries. Specifically, the Ajax technique enables data to be transferred between server and browser asynchronously without interfering with the display of the current web page. Meanwhile, we implement and integrate a peak calling method in the interface, allowing users to identify enrichment sites of different histone modification marks. On the basis of the processed bin-based data, the peak calling procedure first determines a significant enrichement threshold by a percentile rank statistic method and utilizes Monte Carlo simulation method to control false discovery rate . For theiHMS integrates a collection of over 200 histone modification maps for phenotypically diverse human developmental stages and tissues, produced by the NIH Roadmap Epigenomics Mapping Consortium , 16. Thehttps://figshare.com/s/f52b6032884637984711).To efficiently integrate and access these datasets, we preprocessed the raw data in the following steps. The whole-genome data were divided into non-overlapping 200 bp bins. Then, we summed neighboring reads and assigned an integer for each bin. We obtained a total 288 genome-wide data sets, including 254 histone modification data sets, 34 RNA-seq data sets, covering 8 early developmental cell lines and 26 primary tissues, representatives of all three germlayers. These integrated datasets enable in-depth investigation of histone modification data, and facilitate users to explore the dynamic histone modifications and transcriptional changes that drive developmental fate decisions. These histone modification datasets were originally classified by cell type and histone modification mark. In this way, the genomic locations were repeatedly recorded, leading to severe data redundancy. Thus, to reduce the redundancy and save the storage cost, we further reorganized and compressed these processed data sets, as shown in Fig. The iHMS database can be accessed through web interface to search for specific histone modification states of any interested regions across different developmental stages and tissues Fig. a. The sWe also designed a batch query option for users, which allows searching for many interested genomic locations at the same time. To conduct batch query, the developmental stages/tissues and the histone modification marks are set as in the single query page. The locations of multiple regions or the interested gene list can be uploaded from files or submitted in the input box Fig. d. AfterTo visualize histone modification maps on a genome-wide scale, iHMS deploys a user-friendly and interactive browser which is built on JBrowse. It provides an integrated visualization tool for viewing different histone modification marks, gene expression, reference gene annotations, GC content and CpG island information Fig. . For allWith the browser, users are able to conduct further analysis. On one hand, the browser is of usefulness to compare the histone modification states of specific genes or regions at different developmental stages by taking account of multiple relevant data tracks. It facilitates users to identify tissue-restricted histone modification patterns, which is important in maintaining the identity of cell/tissue type. On the other hand, as iHMS enable users to visualize high-resolution gene expression data as well as histone modification profiles in an interactive manner, it can also help identify the correlation between histone modification pattern and gene expression level, and develop new hypotheses regarding the regulatory functions of these chromatin features in the cell differentiation process.Considering that researchers may need these datasets for downstream analysis, iHMS provides an effective interface for data download. The whole-genome histone modification maps and gene expression data can be downloaded in the txt format. iHMS allows users to download data by chromosome. Selecting one chromosome, users can download all available histone modification maps and gene expression data at different developmental stages and tissues. The downloaded data is processed and reorganized as matrix. Rows represents the genomic locations, while columns are the histone modification marks of different cell types. Also, genome-wide expression data across all developmental stages and tissues can be downloaded.The expanding body of chromatin data in public domain has fostered many computational efforts that aim to integrate different data types. Different from previous databases, iHMS focuses on (1) integrating the whole genome histone modification maps covering a wide spectrum of developmental states, including embryonic stem cells, early embryonic lineages and somatic primary tissue types; (2) relating histone modification maps with other related omics data, including gene expression data and sequence-based genome annotations, which allows the investigation between histone modification and gene expression; (3) enabling detailed query and comparison of histone modification states of different developmental stages and tissues for specific genomic regions or genes. The query result can be retrieved as matrix, which is convenient for further comparison and analysis; and (4) building an efficient browser for visualization of all types of data in a genome-wide manner. In general, through integration of histone modification maps with expression profiles and sequence-based genome annotations, iHMS enables the discovery of cell-type specific functional histone modification states, and the gaining of insights into the epigenetic basis of cellular phenotypes across different developmental stages and tissues. This extensive catalog of histone modification states thus provides wealth information of chromatin structure and function, which may help researchers understand the epigenetic mechanisms of the differentiation and development processes.In the foreseeable future, more histone modification data will become available with the rapid advancement of high-throughput sequencing technologies. Further development for iHMS will integrate whole-genome histone modification data from more developmental stages and tissues of human. Meanwhile, iHMS will continually incorporate the gene expression data and interconnect them with the histone modification data. As the amount of histone modification data increases, it is also important to develop efficient web tools to support quick incorporation and analysis of these newly produced data.http://www.tongjidmb.com/human/index.html.The iHMS is freely available online at


Human dengue virus infection without mosquito vector has been reported to occur as a result of mucocutaneous transmission, needlestick in patient care and laboratory accident, blood transfusion, bone marrow transplant, organ transplant, intrapartum and perinatal transmission, and breastfeeding. The emergence of Zika virus, another mosquito-borne flavivirus, has illustrated additional potential routes of non-vector transmission in humans. A recent study in another flavivirus, Japanese encephalitis virus, in pigs has also demonstrated non-vector transmission. We highlight some reports on dengue virus that have documented non-vector transmission and that are relevant to the transmission of Zika virus and other flaviviruses. Aedes mosquitoes, usually Aedes aegypti and Aedes albopictus. Rare cases of non-vector DENV transmission have been reported in the literature involving many routes including mucocutaneous exposure, needlestick in patient care and laboratory accident, blood transfusion, bone marrow transplant, organ transplant, intrapartum and perinatal transmission, and breastfeeding [Dengue virus (DENV) is a flavivirus transmitted via the bite of the female tfeeding –3. UntilAmong the flaviviruses, DENV and yellow fever (YF) are known to cause hemorrhagic manifestations. Because of the higher incidence and much broader distribution of DENV, and its associated thrombocytopenia and hemorrhagic manifestations, DENV potentially has the greatest associated risk for direct or nosocomial transmission. Human DENV infection without mosquito vector has been documented primarily in case reports Table . SeveralDENV transmission has also occurred via blood transfusion –11, boneThe effect of vertical transmission of DENV on infants is highly relevant given the concern resulting from the recognition of ZIKV to cause adverse fetal outcomes including microcephaly. Many cases of intrapartum and perinatal DENV transmission have been described but none have reported congenital abnormalities –17. SystBecause vertical transmission of DENV usually occurred in endemic countries, confirmation faced challenges in areas where testing may not be readily available. For example, a case series from Sri Lanka of women with DENV infection during pregnancy did not document infection in most of the newborns . In contMost previous cases of intrapartum and perinatal transmission were presumed to be via placental transfer of virus. In 2012, a case in New Caledonia of vertical transmission occurred possibly via breastfeeding . The motLastly, some investigators have proposed the possibility of DENV transmission via aerosol route. This mechanism was suggested in 21 healthcare workers who were serologically confirmed to have nosocomial DENV and where there was no known needlestick or mucocutaneous exposure to DENV-infected blood . To dateThe rapid spread of ZIKV infection has brought awareness about its transmission via non-vector routes and suggest areas of study needed for DENV. The most important non-vector route appears to be sexual contact. Such transmission associated with returning travelers has been documented in several countries –32. In 2A notable report raised the possibility of transmission through oral  or other body fluids besides semen in a woman living in Paris who had not traveled to any area with ZIKV circulation. She had sexual contact, both vaginal and oral, several times with a man who had been in Brazil and who had symptoms of ZIKV that resolved a day before their first contact . In the Other studies have also reported positive tests for ZIKV in saliva and urine with ZIKV typically persisting longer in semen, saliva, and urine than in blood , 38, 40.Persons infected with ZIKV but who are asymptomatic are potential sources for transfusion transmission of the virus. During the French Polynesia ZIKV outbreak, nearly 3 % of blood donations tested positive for ZIKV by PCR. Perinatal transmission of ZIKV has been identified . Many stOther flaviviruses related to DENV and ZIKV include Japanese encephalitis virus (JEV), Murray Valley encephalitis, St. Louis encephalitis, West Nile virus (WNV), and yellow fever (YF). Transmission of these viruses occurs nearly always via mosquito bites, although rare human cases of non-vector transmission have occurred for JEV, WNV, and YF . StudiesCulex mosquitoes and a cycle involving pigs as amplifying hosts. However, investigation of some JE outbreaks failed to detect virus in local mosquitoes [A recent article described vector-free transmission and persistence of JEV in pigs . JEV is squitoes , which rIn summary, pigs shed JEV in oronasal secretions and can be infected via the oronasal route. Whether infected by injection, close contact, or oronasal inoculation, clinical symptoms, virus tropism, and CNS histological lesions were similar. The tonsils were prominent sites of virus replication and JEV persisted there for ≥25 days despite high levels of neutralizing antibodies.Studies in animals on the transfer of DENV via aerosol or intranasal or oral route have not been done. One challenge has been the lack of adequate animal models for DENV. Non-human primates can be infected with DENV but do not become symptomatic . A recenClearly non-vector transmission of DENV has occurred, and many possible routes have been described. The overall burden of DENV infection from known non-vector transmission appears to be low. Primarily the non-vector routes involve percutaneous or mucocutaneous exposure to infectious blood, vertical transmission, and receipt of infected products for treatment. Many of these have also been reported with ZIKV in current outbreaks, and some have also been described with other flaviviruses such as WNV and YFV . For insUnlike the ZIKV reports that document sexual transmission and the JEV study in pigs that confirmed oronasal transmission, DENV infection has not been attributed specifically to these routes of transmission. One case report of the blood splash to face that led to confirmed DENV infection was considered mucocutaneous transmission, but oronasal transmission might have been plausible. Possibly, oronasal and sexual routes of exposure can lead to DENV transmission, but are difficult to distinguish from mosquito-borne transmission in endemic countries where mosquito vectors are widely present.It is also possible that routes of non-vector transmission of flaviviruses differ from each other. For DENV and ZIKV, infections in pregnant women clearly lead to different birth outcomes. While DENV in pregnant women has been associated with low birth weight infants and preterm birth, no congenital abnormality has been found, but detailed prospective studies are lacking. On the other hand, ZIKV acquired in utero has the much more severe consequence of microcephaly and multiple other abnormalities.Are there additional routes of DENV transmission, including oral, intragastric, intranasal/aerosol, and sexual routes?Is DENV present in body fluids other than blood and breast milk , and what are the virus kinetics in these body fluids?If DENV is present in other body fluids, how long does it persist?What is the potential of DENV transmission via sexual contact?Is there any possible association of vertical transmission of DENV with congenital abnormalities?Is it possible for DENV transmission via breastfeeding to cause significant harm in infants?In dengue-endemic countries where mosquitos are ubiquitous, how will it be possible to determine whether a case of DENV is acquired via a mosquito bite or a non-mosquito route?Many knowledge gaps in DENV non-vector transmission remain. Key questions that need exploration in view of discoveries from ZIKV include:Aedes mosquitoes, the vectors of disease, are ubiquitous in most countries endemic for DENV and bites occur despite preventive measures; therefore vector-borne transmission is implicated foremost as the exposure. Non-vector transmission is more likely to be suspected in non-endemic countries that detect unusual infections with some link to returning traveler or unusual exposures. Studies on DENV transmission in animal models, like the study on JEV in pigs, would be helpful in our understanding of non-vector transmission of DENV. Similar studies will also be relevant in gaining deeper understanding of the pathogenesis and transmission of ZIKV.In conclusion, documenting and confirming non-vector routes of transmission of DENV faces challenges.


A vast array of tumor-derived genetic, proteomic and cellular components are constantly released into the circulation of cancer patients. These molecules including circulating tumor DNA and RNA, proteins, tumor and immune cells are emerging as convenient and accurate liquid biomarkers of cancer. Circulating cancer biomarkers provide invaluable information on cancer detection and diagnosis, prognosticate patient outcomes, and predict treatment response. In this era of effective molecular targeted treatments and immunotherapies, there is now an urgent need to implement use of these circulating biomarkers in the clinic to facilitate personalized therapy. In this review, we present recent findings in circulating melanoma biomarkers, examine the challenges and promise of evolving technologies used for liquid biomarker discovery, and discuss future directions and perspectives in melanoma biomarker research. The overall survival of patients with Stage III and IV melanoma has improved dramatically in the last ten years with the introduction of immunotherapies and mitogen activated protein kinase (MAPK) targeted treatments –3. TheseIn this era of multiple effective therapies, designing the optimal treatment strategy for each cancer patient requires the development of sophisticated diagnostic, prognostic and predictive biomarkers that are sensitive and specific for cancer detection, patient outcomes and treatment response. The ideal biomarker in metastatic melanoma would guide sequencing and identify the optimal timing to introduce the next line of therapy, and differentiate patients who would benefit from treatment beyond progression. The latter is particularly important in the case of pseudo-progression, which can occur both early and late into the treatment. With recent publications outlining the effectiveness of adjuvant targeted and immunotherapies in stage III melanoma , 12, a nCancer biomarkers can be classified as diagnostic, prognostic or predictive Fig. . DiagnosCirculating biomarkers identified in biological liquid samples, termed liquid biopsies, are particularly valuable as they can be sampled repeatedly in real time and are non-invasive . Here, wThere are many prognostic and predictive biomarkers used clinically in melanoma, and these form the updated version of the 8th edition American Joint Committee on Cancer (AJCC) melanoma staging system . This stTumor cells, tumor-derived metabolites, proteins, nucleic acids and vesicles are constantly shed into the circulation and these circulating components can provide valuable diagnostic, prognostic and predictive information Fig. . Liquid Although many circulating cancer biomarkers have been identified in pre-clinical models and clinical samples, few have been validated or FDA-approved for clinical use. A critical review in 2005 showed a general decline in FDA-approved plasma protein biomarkers, despite an increase in biomarker-related publications during this period. For instance, of the 2000 publications on cancer biomarkers in 1994, two plasma protein biomarkers received FDA approval and only one biomarker was approved by the FDA in 2000, despite over 3000 biomarker publications . The incIn the following sections, we discuss commonly used proteomic, molecular and cellular profiling approaches, the progress and limitations of these emerging technologies, and their contributions to melanoma biomarker discovery Table .Table 3AProteins are easily recovered from blood plasma and serum, but the high abundance of a few proteins, including albumin , the brMass spectrometry (MS) is based on the fractionation of proteolytic peptides by liquid chromatography and subsequent quantitation and characterization of each fraction. MS-based technologies require significant optimization, expertise and are time consuming Table . They ofThere have been many refinements in MS-based technologies to improve throughput and quantitation, including multiple reaction monitoring (MRM) and sequential window acquisition of all theoretical mass spectra (SWATH-MS). Highly multiplexed MRM platforms are capable of quantitating proteins and have been used to identify potential biomarkers in bladder cancer . SWATH-MAffinity-based proteomic assays capture target proteins and utilize a secondary detection method to generate a quantifiable signal proportional to the quantity of protein present in samples. Traditional singleplex assays such as the enzyme-linked immunosorbent assay (ELISA) detect a specific protein, but more contemporary multiplex methods simultaneously measure many target proteins over a wide dynamic range without the need for the depletion of abundant proteins. These assays are dependent on highly specific antibodies or modified aptamers. For instance, the Mesoscale Discovery Technology Platform (MSD) and the Q-Plex array (Quansys Biosciences) have capture antibodies immobilized on a solid phase support, while the Luminex (ThermoFisher), Cytometric Bead Arrays (BD Biosciences) and Bio-PlexPro (BioRad) assays utilize antibodies conjugated to fluorescently-activated microbeads to allow identification and detection using a flow cytometry-based method , 42. TheAffinity-based protein profiling assays depend on antibodies or aptamers that recognize specific epitopes, without cross-reactivity to other proteins. Although capture antibodies or aptamers are analyzed for cross reactivity, they are often tested against a restricted panel of antigens. Method testing and validation of these multiplex immunoassays are critical but few studies have examined performance of these assays in detail . Indeed,Genetic and signaling changes that drive melanoma development and progression can be identified through molecular profiling. These changes can be detected in the circulation in the form of circulating free DNA (cfDNA), including circulating tumor DNA (ctDNA), microRNA (miRNA) and long non-coding RNA (lncRNA) that are shed into the blood stream by cancer cells. Detection sensitivity of cfDNA is a persistent problem, however, and a number of studies have sought to optimize the yield and stability of cfDNA by comparing a range of tubes during blood collection , 49, andCommercial cfDNA purification kits typically employ a spin column-based or magnetic bead-based approach. Spin columns are more time consuming and costly, but appear to be the more consistent with higher yields than the magnetic-based systems , 49. BotctDNA is highly fragmented single or double stranded DNA shed by tumor cells into the circulation . ctDNA hThe utility of ctDNA in identifying heterogeneous resistance mechanisms to EGFR targeted therapy has been well outlined in non-small cell lung cancer , with thLevels of ctDNA in cancer patients are associated with disease volume and can be influenced by tumor location, vascularity and cellular turnover , 61, andIn addition to ctDNA quantitation, epigenetic changes in ctDNA such as methylation can also be detected and analyzed. Epigenetic modifications of ctDNA, especially the evaluation of methylation signatures , is a prMany different platforms have been used to detect ctDNA including quantitative PCR (qPCR), digital droplet PCR (ddPCR) and next generation sequencing  reviewe. SeveralThere are a number of challenges in ctDNA detection and analysis. The proportion of ctDNA is low compared to total background cfDNA, and it is imperative that white blood cell lysis, which increases the cfDNA fraction, is avoided during pre-analytical steps such as blood collection, processing and storage. Plasma is the preferred source for ctDNA compared to serum due to greater cell lysis that occurs during the clotting process . HoweverCurrently, detection of BRAF and NRAS mutations in ctDNA has shown significant value in predicting treatment response and outcome in melanoma , 65, 77 MicroRNAs are short (20–200 nucleotides) noncoding RNA molecules that regulate gene transcription processes to affect cell proliferation, apoptosis, differentiation and survival. Long noncoding RNAs (lncRNAs), spanning more than 200 nucleotides, also have direct roles in transcriptional, post-transcriptional and epigenetic gene expression modulation . Both miDetection of miRNAs requires selective and sensitive amplification methods including isothermal exponential amplification and rolling cycle amplification, capillary electrophoresis-based assays, and use of quantum dots, Raman spectroscopy, gold nanoparticle probes and duplex specific nucleases . CurrentExpression of miRNAs and lncRNAs have shown diagnostic, prognostic and predictive value in melanoma . HoweverExosomes are small  membrane bound vesicles, produced by all cells and capable of transporting DNA, RNA and proteins between cells. Tumor cells actively secrete exosomes, and these can deliver tumor-specific cargo  to other body sites to modify tumor survival, proliferation and treatment response , 93. SecExosome levels can be monitored directly in the circulation via cell surface markers such as the tetraspanin proteins, CD63, CD81 and CD9. For example, ExoScreen can detect and quantitate exosome surface proteins with streptavidin-coated donor beads that capture analyte-specific biotinylated antibodies, and acceptor beads conjugated to secondary antibodies that recognize an epitope of the analyte . ExoScreWhole blood contains different inflammatory and immune cell subsets such as peripheral blood mononuclear cells (PBMCs), and can also contain circulating tumor cells (CTCs), derived from malignant cells that have detached from primary or metastatic tumor sites and shed into the circulation. The phenotypic and functional analysis of whole blood may identify potential cell-based biomarkers .CTCs represent a small proportion of cells in the circulation, and are detected at a rate of approximately one CTC per million leukocytes . The detCurrently, there are more than 400 clinical trials incorporating CTCs as diagnostic biomarkers for patients with advanced late stage cancers. However, CTC detection in early stage disease remains challenging  despite Circulating melanoma cells (CMCs) have been detected in blood by qPCR of melanocyte specific genes or by enrichment using melanocyte surface markers; CMCs have shown prognostic value in identifying disease stage , progresThe presence of tumor-infiltrating immune cells predicts melanoma response to immunotherapy –119 and The capacity to profile different immune populations has vastly improved due to refinements in multiparameter flow cytometry and mass cytometry techniques. These technologies allow phenotypic and functional characterization of individual cells using multiple parallel tags. Flow cytometry uses antibodies conjugated to fluorochromes that bind to cell surface or intracellular markers to allow cellular characterization; these fluorochromes have now expanded to allow for routine analysis of up to 15 different parameters , 121. Mahi and Tbetlo) expressing the proliferative marker Ki67. Numbers of circulating Ki67+ CD8+ T cells correlated with tumor burden before and after therapy, and more importantly, a ratio of T cell reinvigoration to tumor burden greater than 1.94 significantly associated with better objective response, progression free survival and overall survival [Several recent studies have demonstrated the utility of immune profiling to discover predictive melanoma biomarkers. In a study with 209 melanoma patients treated with ipilimumab, low absolute monocyte counts, and high absolute eosinophil count, T regulatory cells and relative lymphocyte counts were associated with a favorable outcome . Similarsurvival . WhetherThe identification and validation of diagnostic, prognostic and predictive biomarkers are essential for directing and optimizing personalized therapy. For instance, in melanoma, biomarkers that predict and monitor responses to immunotherapies  will enable the selection of patients most likely to respond to each therapy, identify patients who may require more toxic, combination therapies and ensure efficient use of health care resources; in Australia, pembrolizumab costs over $130,000 per patient per year. These therapies can continue for years, can be given intermittently, or can be used as second-line therapies to prolong patient survival. The management of these long-term cancer survivors requires ongoing review and monitoring, and this can be ideally achieved with inexpensive, accurate and non-invasive liquid biomarkers. Unfortunately, the identification of biomarkers in liquid biopsies has been slow and challenging despite recent advances in molecular and proteomic technologies. Many candidate biomarkers have been identified and proposed but few have reached clinical application. Major factors hindering the approval of new biomarkers include lack of reproducibility, absence of technical standardization, and inadequate validation studies. Given the heterogeneity of individual patients and individual tumors, robust validation of candidate biomarkers requires large-scale prospective multi-center clinical trials. The regulatory pathways involved in biomarker licensing and implementation are also complex and the FDA has published guidelines to support the pre-market development of companion diagnostics.Liquid biopsy biomarkers could pave the way to better personalized treatment strategies for melanoma patients. Using circulating biomarkers, we may be able to offer patients minimally-invasive, inexpensive and accurate means of selecting the best treatment option and monitoring response during the course of treatment. The identification of potential biomarkers will increase with more sophisticated profiling technologies and more studies focused on the expanding repertoire of targeted and immunotherapies, used alone or in conjunction, in clinical trials. However, biomarker discovery alone is not sufficient, and more emphasis needs to be directed at validation of newly emerging biomarker candidates to realize their implementation into clinic.


Chronic kidney disease-mineral and bone disorder (CKD-MBD), a complication of chronic kidney disease, has been linked to reduced quality and length of life. High serum phosphate levels that result from CKD-MBD require phosphate-lowering agents, also known as phosphate binders. The objective of this systematic review is to compare the effects of available phosphate binders on laboratory outcomes in patients with CKD-MBD.Data sources included MEDLINE and EMBASE from January 1996 to April 2016, and the Cochrane Register of Controlled Trials up to April 2016. Teams of two reviewers, independently and in duplicate, screened titles and abstracts and potentially eligible full text reports to determine eligibility, and subsequently abstracted data and assessed risk of bias in eligible randomized controlled trials (RCTs). Eligible trials enrolled patients with CKD-MBD and randomized them to receive calcium-based phosphate binders , non-calcium-based phosphate binders (NCBPB) , phosphorus restricted diet (diet), placebo or no treatment and reported effects on serum levels of phosphate, calcium and parathyroid hormone.We performed Bayesian network meta-analyses (NMA) to calculate the effect estimates (mean differences) and 95% credible intervals for serum levels of phosphate, calcium and parathyroid hormone. We calculated direct, indirect and network meta-analysis estimates using random-effects models. We applied the GRADE  approach to rate the quality of evidence for each pairwise comparison.Our search yielded 1108 citations; 71 RCTs were retrieved for full review and 16 proved eligible. Including an additional 13 studies from a previous review, 29 studies that enrolled 8335 participants proved eligible; 26 trials provided data for quantitative synthesis. Sevelamer, lanthanum, calcium, iron, diet and combinations of active treatments  resulted in significantly lower serum phosphate as compared to placebo . We found no statistically significant differences between active treatment categories in lowering serum phosphate. Sevelamer, lanthanum and diet resulted in lower serum calcium compared to calcium . Iron, sevelamer and calcium yielded lower parathyroid hormone levels as compared to lanthanum. Meta-regression analyses did not yield a statistically significant association between treatment effect and trial duration.We found few differences between treatments in impact on phosphate and differences in parathyroid hormone. Relative to calcium, sevelamer, lanthanum and diet showed significant reduction in serum calcium from baseline. Treatment recommendations should be based on impact on patient-important outcomes rather than on surrogate outcomes.Systematic review registration: PROSPERO CRD-42016032945 Chronic kidney disease (CKD) has been linked to negative patient outcomes, including mortality, often due to cardiovascular diseases –7. CKD aIn patients suffering from CKD-MBD, clinical practice guidelines suggest maintaining targets for serum phosphate, calcium and parathyroid hormone –10. DietPrevious systematic reviews have addressed the impact of alternative interventions for CKD-MBD on outcomes of important to patients, including all-cause mortality , 21. JamConsistent with Jamal’s review, our systematic review and network meta-analysis (NMA) found that calcium versus sevelamer resulted in higher mortality among CKD-MBD patients . Our NMAThe association between drug effects on laboratory outcomes and patient survival has been explored with mixed results , 24. NevKnowledge of the impact of interventions on these surrogate outcomes may provide insight into understanding of the results of randomized controlled trials (RCTs) that address patient-important outcomes, and might provide clues regarding the comparative effectiveness of NCBPB agents on patient-important outcomes, currently unestablished. The objective of this study was therefore to systematically review and synthesize evidence from RCTs addressing the effectiveness of phosphorus restricted diet (diet) and different phosphate binders on serum levels of phosphate, calcium and parathyroid hormone by combining direct and indirect estimates in a NMA. We updated the Jamal systematic review  and applIn our previous review, we included patient-important outcomes using the frequentist framework. In this study, we only assessed surrogate outcomes . When conducting meta-regression, the Bayesian framework provides a common coefficient for all treatment comparisons. It is not possible to produce a common coefficient in the frequentist framework. In this study, we were able to perform meta-regression, since we used the Bayesian framework.CRD42016032945) and adhered to the Preferred Reporting Items for Systematic Review and Meta-analysis for Network Meta-analysis (PRISMA NMA) guidelines in drafting our manuscript  randomized patients to a diet or phosphate binder versus a control; (3) reported at least one of the following outcomes: serum phosphate, calcium or parathyroid hormone; and (4) had a minimum follow-up of 4 weeks. Phosphate binders included calcium  or NCBPBs . A control included placebo or no intervention. We excluded non-randomized controlled trials, observational studies and conference abstracts.We included studies that: (1) enrolled patients with CKD, defined as an estimated glomerular filtration rate <60 ml/min/1.73 mWe used the search of MEDLINE and EMBASE that we performed in our recently published review  which waTeams of two reviewers independently screened each title and abstract. If either reviewer identified a citation as potentially relevant, we obtained the full text of the article. Two reviewers independently determined the eligibility of all studies that underwent full text evaluation and resolved discrepancies by discussion.We extracted study data using a customized data collection form accompanied by a detailed instruction manual. Two independent reviewers abstracted the following information from each study: (1) author, (2) year of publication, (3) summary of baseline characteristics of the participants, (4) trial duration, and (5) serum levels of phosphate, parathyroid hormone or calcium. We recorded the last measurement if multiple measurements were provided during the follow-up period.Two reviewers used a modified version of the Cochrane risk for bias tool in order to assess the risk of bias on the basis of randomization, allocation concealment, blinding, incomplete outcome data, selective reporting (by comparing the methods and results sections of the manuscript) as well as stopping early for benefit . RevieweWe assessed the quality of evidence in effect estimates for each outcome as high, moderate, low or very low using the GRADE rating system  in whichAfter considering these reasons for rating down, we judged the overall confidence in estimates of effect for change in serum phosphate, calcium and parathyroid hormone from baseline for each pairwise comparison as follows: ‘high’ quality of evidence (we are very confident that the true effect lies close to that of the estimate of the effect); ‘moderate’ quality of evidence ; ‘low’ quality of evidence ; and ‘very low’ quality of evidence  .We also applied the GRADE methodology to rate the confidence of indirect effect estimates. In relation to the treatment comparisons, we visually examined the network graphs and identified first order  and higher order loops (more than one interventions connecting to the two interventions). The quality of evidence rating for the indirect comparisons informing each pairwise comparison was the lower of the ratings of quality for the two direct estimates contributing to the first order loop. For instance, if one contributing direct comparison was rated as low and other rated as moderate evidence, we rated the quality of indirect evidence as low . In the In the GRADE system for NMA, indirect effect estimates may be further rated down for intransitivity. The transitivity assumption implies similarity of trials in terms of population, intervention (type and dosing frequency), settings and trial methodology across the treatment comparisons included in the network. If the transitivity assumption was deemed to be violated, we planned to rate down the indirect comparison by one further level (if possible), as well as to explore this meta-regression analysis. Trial duration was the only effect modifier that we assessed for this assumption. All other potential effect modifiers, indeed, were not assessed using meta-regression due to unavailability of the data, such as mean age.If both direct and indirect evidence were available, the NMA quality rating came from the higher of the two. If there was direct evidence, but no indirect evidence because of no closed loop or if there was a closed loop formed by a multi-arm trial, the NMA was graded according to the direct evidence. If there was no direct evidence, the NMA received the GRADE assessment of the indirect estimate.We also considered coherence (degree of consistency between direct and indirect effect estimates) in our final quality rating of network estimates. We visually examined the magnitude of the difference between direct and indirect effect estimates and the extent to which their confidence intervals overlapped. We planned to rate down the quality of the NMA effect if we found meaningfully large incoherence. We calculated indirect effect estimates using the node-splitting approach . We haveIf the NMA evidence was substantially more precise than the higher quality of the direct or indirect estimates, we rated that estimate up due to improved precision.We used a funnel plot to explore publication bias for comparisons with more than 10 studies in the direct comparisons. Asymmetrical funnel plots indicate reporting biases due to publication bias or small-study effect , 39. HowIn summary, the quality of evidence for each pairwise network comparison included assessment of transitivity ; coherence (similarity between direct and indirect effect estimates); and homogeneity .We used aggregate data  to perform pairwise and network meta-analyses. In our conventional meta-analysis, we calculated pooled mean differences (MD) and the associated 95% credible intervals (CrIs) for each outcome using random-effects models in a Bayesian framework.For Bayesian analyses, we used non-informative normal priors for means and a half-normal prior distribution for the between-study standard deviation , τ>0). Posterior distributions were produced using Markov chain Monte Carlo methods. Two sets of initial values were produced for each chain with 100,000 iterations. We planned to increase the number of iterations if the data did not converge. The first 10,000 iterations were discarded as burn-in and a thinning of 10 was also applied .We employed fixed-effect and random-effects models and compared model fit and parsimony using the deviance information criterion (DIC). We reported our final results based on random-effect models because they indicated lower DIC values.For each outcome, we reported the pooled MD and associated 95% CrIs based on the posterior distributions of Bayesian NMAs. We also calculated predictive intervals (PrIs) to capture the magnitude of the between-study variance for each outcome per phosphate binder. PrIs present the intervals within which we would expect the treatment effect of a future study to lie . For eacMRC Biostatistics unit, Cambridge, UK), which generated inferences using the Gibbs sampler. We performed analysis for indirect estimates in R studio using the gemtc package [network command in Stata  [Modified Gelman-Rubin statistics and graphical assessment of trace plots were used to examine model convergence. The analysis was performed using OpenBUGS 3.2.3 ( package . We asseCorp LP) .We employed a network meta-regression in order to examine an association between treatment effect using trial duration as a continuous variable measured in months. We also conducted a subgroup analysis for dialysis versus non-dialysis patients.Our updated search yielded 1108 citations, of which 71 were retrieved for full review; 16 RCTs including 3576 patients proved eligible . We inclTable A in the The omnibus test of consistency between direct and indirect estimates did not approach significance for any of the three outcomes .Our assessment indicated low risk of bias for missing data and selective reporting in about 95% of the trials; blinding was adequate in only about 25% of the trials . Of the Lanthanum was associated with significant reductions in serum phosphate level as compared to placebo  as was iron   showed significant reduction in serum phosphate level . No otheSUCRA ranking suggested diet as the optimal treatment for reducing serum phosphate  . HoweverOf the 25 comparisons that failed to reach statistical significance in the network estimate, we classified eight as high quality, eight as moderate quality and nine as very low quality evidence .Patients treated with diet had a higher likelihood of reduction in serum calcium as compared to those treated with other treatment categories  . HoweverIn individual interventions tested, iron, diet, sevelamer and calcium yielded lower parathyroid hormone levels as compared to lanthanum. Iron was more effective in reducing parathyroid hormone than sevelamer, calcium, lanthanum and placebo  .Combination treatment with magnesium yielded significantly higher parathyroid hormone levels than iron and calcium-and-sevelamer combination. Combination treatment with sevelamer and calcium showed lower parathyroid hormone levels as compared to single treatment with sevelamer, calcium, lanthanum and iron.Of the 28 comparisons, 11 failed to reach statistical significance in the network estimate. We classified eight as high quality, eight as moderate quality, three as low quality evidence and nine as very low quality .Patients treated with sevelamer and calcium combination had a higher likelihood of reduction in serum parathyroid hormone as compared to those treated with other treatment categories   Table N. The betIn meta-regression analysis, trial duration is not associated with a significant change in phosphate, calcium and parathyroid hormone levels  .No evidence of inconsistency between direct and indirect estimates were found for all three outcomes  . Our NMA results find no statistically significant difference between active treatment categories in lowering serum phosphate. Further, combination therapy provides no benefits relative to monotherapy in lowering serum phosphate.In terms of reducing serum calcium levels, we find no statistically significant difference between those who receive placebo or active treatment. Calcium binders likely increase serum calcium levels relative to other interventions .The use of lanthanum increases parathyroid hormone as compared to sevelamer, calcium, iron, diet and placebo . Our results show combination therapy with sevelamer and calcium will likely reduce parathyroid hormone as compared to single drug regimen which includes sevelamer, calcium, lanthanum or iron. Combination therapy with magnesium relative to iron and calcium-and-sevelamer combination yields an increase in parathyroid hormone levels with very low quality of evidence .We found no statistically significant association between trial duration and treatment effect in our meta-regression. However, this negative finding may be due to low power to detect an important effect. Hence, we cannot conclude that trial duration was not related to the effect size.This is the first network meta-analysis within a Bayesian framework that examined effectiveness of phosphate binders on laboratory outcomes in patients with CKD. The most recent systematic review addressing phosphate binders in patients with CKD did not report the effectiveness of calcium and NCBPBs on laboratory outcomes .Strengths of our systematic review and meta-analysis include explicit eligibility criteria, a comprehensive search, independent duplicate assessment of eligibility, and use of the GRADE approach to assess quality of evidence an outcome-by-outcome basis for direct, indirect and network evidence. Limitations of our review included low and very low quality evidence for some treatment comparisons.Previous evidence had demonstrated that phosphate binders lower serum phosphate levels by diminishing phosphate reabsorption from the gastrointestinal system. Clinical practice guidelines recommend calcium as first line treatment for stages 4 and 5 CKD patients , 10 and The association between laboratory outcomes and patient-important outcomes has been an area of interest for many researchers. A recent systematic review failed to show a significant association between drug effects on the laboratory outcomes and survival in CKD-MBD . The triin vivo and in vitro studies. An association between calcium phosphate binders and cardiovascular calcifications, positive calcium balance and hypercalcemia have been previously reported [Comparative effectiveness of phosphate binders on markers of bone and mineral metabolism including phosphate, calcium and parathyroid hormone have been investigated reported , 17, 76.In animal models, iron has been associated with a significant decline in serum parathyroid levels . In contMagnesium has been inversely correlated with parathyroid hormone and plays a role in the causation of adynamic bone disorder –81. TherSevelamer reduces mortality relative to calcium , but resAccording to our previous systematic review, the effects of various types of NCBPs have not been linked to mortality, although the sevelamer and calcium comparison yielded significant results supporting the mortality benefit of sevelamer . FurtherSome RCTs are designed and executed to assess the impacts of treatments on laboratory outcomes rather than mortality or quality of life. They often report events during the trial period, but study durations are not long enough to capture the effects on patient important outcomes. Since it is not always possible and practical to design and conduct an RCT to capture information about patient important outcomes, laboratory outcomes are used instead. The main problem with this approach is that it is difficult to relate laboratory outcomes to patient-important outcomes.This NMA showed only small and unconvincing differences between phosphate binding agents with low to very low quality of evidence. The treatment of hyperphosphatemia with calcium will likely induce hypercalcemia. The combination therapy with sevelamer and calcium will likely cause a decrease in serum parathyroid hormone.The only result possibly explaining the previously demonstrated reduction in mortality with sevelamer versus calcium binders was a lower serum calcium with sevelamer. Our findings emphasize the necessity for trials focusing on patient-important outcomes to establish the relative benefit and harm of alternative management strategies for CKD-MBD.In order to fully explore the return on investment and risk of investment, cost and effectiveness data should be incorporated in a network meta-analyses. This will guide policy-makers in drug coverage making decisions, especially in countries with taxed-based health care financing systems, such as Canada.S1 Supporting Information FileFile A. The PRISMA NMA checklist. The PRISMA NMA checklist. File B. Search strategies. Search strategies for MEDLINE OVID, EMBASE OVID and EBM Reviews—Cochrane Central Register of Controlled Trials databases. Fig A. Assessment of publication bias by funnel plots for phosphate outcome. Funnel plot of effectiveness outcome for mean phosphate reduction at the end of the study period. Table A. Study Characteristics. Table B. Treatment codes, treatment categories and abbreviations used in the analysis. Table C. Treatment comparisons, number of studies and number of patients for phosphate outcome. Table D. GRADE quality assessment of direct evidence from each pairwise treatment comparison for phosphate. Table E. GRADE confidence assessments of indirect estimates per pairwise treatment comparison for phosphate in cases when direct comparisons are available. Table F. GRADE confidence assessments of indirect estimates per pairwise treatment comparison for phosphate in cases when direct comparisons are unavailable. Table G. GRADE quality assessment of direct evidence from each pairwise treatment comparison for calcium. Table H. GRADE confidence assessments of indirect estimates per pairwise treatment comparison for calcium when direct comparisons are available. Table I. GRADE confidence assessments of indirect estimates per pairwise treatment comparison for calcium when direct comparisons are unavailable. Table K. GRADE quality assessment of direct evidence from each pairwise treatment comparison for parathyroid hormone. Table L. GRADE confidence assessments of indirect estimates per pairwise treatment comparison for parathyroid hormone when direct comparisons are available. Table M. GRADE confidence assessments of indirect estimates per pairwise treatment comparison for parathyroid hormone when direct comparisons are unavailable. Table N. SUCRA rankings of phosphate binders. Table O. Effectiveness outcome for mean phosphate, calcium and parathyroid hormone reductions at the end of the study period using adjusted analysis for trial duration. Table P. Exploring the global inconsistency in networks for each laboratory outcome using the design-by-treatment interaction model.(DOCX)Click here for additional data file.


Testing for total antinuclear antibodies (ANA) is a critical tool for diagnosis and management of autoimmune diseases at both the primary care and subspecialty settings. Repurposing of ANA from a test for lupus to a test for any autoimmune condition has driven the increase in ANA requests. Changes in ANA referral patterns include early or subclinical autoimmune disease detection in patients with low pre-test probability and use of negative ANA results to rule out underlying autoimmune disease. A positive result can lead to further diagnostic considerations. Currently, ANA tests are performed in centralized laboratories; an alternative would be ANA testing at the clinical point-of-care (POC). By virtue of its near real-time data collection capability, low cost, and ease of use, we believe the POC ANA has the potential to enable a new paradigm shift in autoimmune serology testing. Autoantibodies are essential serological markers that define and classify most autoimmune diseases. Testing for total antinuclear antibodies (ANA of undefined specificity and which includes anti-cytoplasmic autoantibodies) has become an invaluable tool at both the primary care and subspecialty settings as a window into further clinical investigation. The presence of total ANA triggers follow-up diagnostic studies for specific autoimmune disorders that are part of the diverse clinical landscape seen in rheumatology, neurology, oncology, and in infectious, pulmonary, and renal diseases among others. In many of these conditions ANA constitutes part of classification and diagnostic criteria for those diseases. The total and ANA sub-serology tests also facilitate differential diagnosis and its refinement , predictThe present article attempts to summarize current trends in ANA serology testing by diverse physician groups and to provide ideas on how point-of-care delivery of ANA results may produce the framework, knowledge, and practices which may benefit patients, providers, and the health care industry as a whole. While methods for ANA detection have markedly evolved in recent years, newer methodologies generally require expensive instrumentation and/or central clinical laboratories. An inexpensive and reliable point-of-care device for ANA testing could be applicable not only in communities with modern health care infrastructures but also in more resource-poor settings that struggle with provision of medical care and high burden of disease.Intent to diagnose There are many factors, which determine a physician’s test ordering practices. These include diagnostic, prognostic, and therapeutic factors, as well as patient-related factors (reassurance), doctor-related factors , and organization-related factors  among others . Regardi2.Intent to refer ANA testing is routinely performed during initial evaluation of patients with increased pre-test probability for autoimmune disease , the con3.Intent to case find for early disease prevention (PCPs)According to the CDC and Prevention’s National Ambulatory Medical Care Survey , more th4.Intent to reassure patient In an insightful review and commentary on ANA testing  M. FritzTesting with the intent of “reassurance” is not infrequent, despite the fact that when done for symptoms with low risk of serious illness, it is doing little to decrease anxiety or resolve complaints, but may reduce further primary care visits .The total global autoimmune diagnostic tests’ market is predicted to reach $14.2 billion by 2020 . While mCurrent ANA testing is performed exclusively in centralized clinical laboratories. This is a protracted, labor-intensive, and expensive procedure that can slow the diagnostic process and restricts use in a large segment of the population. Also, the requirement for blood drawing, transport to the testing lab, blood processing, test execution, and communication of results is cumbersome, time consuming, error prone and costly, which detract from its diagnostic value. Primary care physicians recognize delays in test result review as a significant problem affecting quality of care and patient safety—“I wish I has seen this test result earlier”, even raising malpractice concerns .POC diagnostics is gaining momentum in different areas of patient care, as its short turnaround time and minimal manual requirements enable quick clinical management decisions . BiosensWe have described development and application of an electrochemical biosensor for rapid quantitation of total ANA having performance characteristics well correlated with ANA titer determination by indirect immunofluorescence in a clinical laboratory . The immIn 2012, the American Board of Internal Medicine Foundation  launched the “Choosing Wisely” campaign, aiming to advance a dialogue on avoiding wasteful and unnecessary medical tests, treatments, or procedures. Specialty society partners American College of Rheumatology  and Cana