The optical translucency and the genetic tractability of Drosophila embryos have established Drosophila as an invaluable model to live-image and dissect fundamental aspects of inflammatory cell behavior, including mechanisms of developmental dispersal, clearance of apoptotic corpses and/or microbial pathogens, and recruitment to wounds. However, more recent work has now demonstrated that employing a much later stage in the Drosophila lifecycle – the Drosophila pupa – offers a number of distinct advantages, including improved RNAi efficiency, longer imaging periods, and significantly greater immune cell numbers. Here we describe a protocol for imaging wound repair and the associated inflammatory response at the high spatio-temporal resolution in live Drosophila pupae. To follow the dynamics of both re-epithelialization and inflammation, we use a number of specific in vivo fluorescent markers for both the epithelium and innate immune cells. We also demonstrate the effectiveness of photo-convertible fluorophores, such as Kaede, for following the specific immune cell subsets, to track their behavior as they migrate to, and resolve from, the injury site.During the rapid inflammatory response to tissue damage, cells of the innate immune system are quickly recruited to the injury site. Once at the wound, innate immune cells perform a number of essential functions, such as fighting infection, clearing necrotic debris, and stimulating matrix deposition. In order to fully understand the diverse signaling events that regulate this immune response, it is crucial to observe the complex behaviors of (and interactions that occur between) multiple cell lineages  An efficient and effective inflammatory response is pivotal for any organism to fight infection, clear debris, and orchestrate the repair of injured tissues12Drosophila has become a well-established and valuable model system to dissect fundamental features of the inflammatory response conserved from insects to human4Drosophila offers far greater genetic tractability than is currently possible in other experimental models (such as mice or zebrafish), permitting precise spatio-temporal genetic manipulation in vivo  and ease of genome-wide screens6Drosophila have been performed at embryonic stages, as embryos are immobile (unlike Drosophila larvae or adults) and optically translucent which enables unparalleled high resolution in vivo imagingDrosophila innate immune cells (hemocytes) to the wound site in response to the mechanical or laser-induced injury to the embryonic epithelium910111213Drosophila embryos have uncovered many important immune cell proteins that control inflammatory cell behavior in vivo. For example, the CED-1 homolog Draper (an ITAM domain-containing protein) has been identified as an important 'damage receptor' that mediates the recruitment Drosophila immune cells in an H2O2-dependent manner to sites of damageIn recent years, Drosophila is a holometabolous insect that goes through the additional larval and pupal stages following embryogenesis, prior to reaching adulthoodDrosophila pupa has been developed as an additional model for non-invasive live-imaging of a variety of dynamic cellular events, including developmental cell migrationin vivo22Drosophila pupae are immobile and optically translucent, after careful dissection from their opaque pupal casesin vivo behavior of innate immune cells (hemocytes) in response to the tissue damage within Drosophila pupal tissues, such as the pupal wingJust as in embryonic stages, Drosophila hemocytes). A number of different markers  are available to label these two different cell populations - the choice of marker depends on the particular process to be studied. To mark the pupal epithelium, Drosophila lines containing either a ubiquitously expressed GFP-tagged E-cadherin (that labels adherens junctions) are routinely utilized to indicate the positions of the cell margins, or alternatively, a GFP-tagged Actin-binding domain of Moesin (that labels the actin cytoskeleton) to visualize the wound-edge contractile actin ring and leading-edge protrusions. To label the Drosophila hemocytes, a hemocyte-specific srp-Gal4Drosophila pupae, only combinations of genetic markers that are viable until mid-pupal stages can be utilized. Also, embryonic lethal stocks will not be suitable. This is unlikely to be a problem when imaging control (or wild-type) pupae but is important to consider when genes are to be knocked down or overexpressed, to assess their effect on the wound closure or inflammation. In the case of early lethality caused by gene knockdown (or overexpression), a Gal80ts construct can be used to induce the Gal4-driven knockdown later in development (see Discussion).In order to follow the dynamics of wound re-epithelialization and the accompanying inflammatory response within this new pupal model, two different cell populations must be labeled: the pupal epithelium and the innate immune cells  in response to subsequent insults, using the photoconvertible fluorophoreIn our recent studies, moving into the pupal stage has enabled us to gather sufficient immune cell trajectory data to analyze inflammatory behavior using sophisticated mathematical modeling, which in turn has allowed us to deduce novel details of the wound inflammatory attractant signalsDrosophila pupae. We provide a detailed methodology to cover the steps required for the initial pupae preparation (dissection and mounting) and the subsequent laser-mediated wounding and the time-lapse imaging. We also describe the use of photo-convertible fluorophores to permit the labeling of specific immune cell subsets in vivo. In the long-term, we envision that this new Drosophila pupal model will open up exciting possibilities for dissecting the complex signaling dynamics underlying the inflammatory response to tissue damage. By applying more sophisticated statistical analyses one might uncover features of the response that would otherwise remain experimentally inaccessible, whilst the improved RNAi efficiency could lend itself to the application of genome-wide screening within immune cells in vivo to identify novel players regulating immune cell behavior.Here we describe a protocol to visualize the dynamics of wound repair and the associated inflammatory response at high spatio-temporal resolution using living Drosophila stocks and staging of Drosophila pupae, (2) Pupal dissection and mounting, (3) Pupal wounding, (4) in vivo time-lapse confocal imaging.This protocol consists of four main sequential steps: (1) Preparation of Drosophila stocks .Obtain appropriate Select adult flies by using carbon dioxide gas pads to briefly anesthetize the flies and a fine paintbrush to transfer flies of the appropriate genotype or gender to a collection vial.Table of Materials) supplemented with yeast.Add 20 virgin females and 20 males to each vial containing standard fly food media  using forceps or a fine paintbrush to dislodge pupae from the interior vial surface and transfer pupae carefully to the side of a clean empty plastic vial. Note: Wandering 3rd instar larvae crawl upwards out of the food medium to undergo pupation; newly formed white prepupae are easily identified as they possess everted anterior spiracles and are stationary (unlike 3rd instar larvae). The cuticle transforms into the ‘puparium’  which is initially soft and white18 h before the scheduled imaging session, select at least 10 newly formed white pre-pupae  from theAge the selected pupae to the appropriate developmental stage  in the vial at 25 °C. Note: As the pupae develop, the pupal case will become progressively darker and more brittle.Prepare other reagents for the next step ahead of time. To make the heptane glue, combine a 20 cm length of rolled up double-sided tape with 20 mL heptane in a 50 mL centrifuge tube, seal with the paraffin film and rock at the room temperature overnight on the bench.Drosophila pupae to a piece of double-sided sticky tape mounted on a glass slide. Position the pupae so that the ventral side is firmly stuck to the tape and the dorsal side is facing upwards (Transfer the staged  upwards . Note: T-D). Initially, make an incision in the anterior-most region of the puparium using the forceps . Ensure After this initial incision, carefully tear or cut the pupal case open in an anterior to posterior direction using forceps or microscissors  until thCarefully remove pupae from their protective puparium casing under a brightfield dissection microscope using forceps and micro-scissors -D. InitiUse a 20 mL pipette tip to place a 10 mL drop of pre-prepared heptane glue (see section 1.6 above) in a line on the glass-bottomed dish.Allow the glue to dry for 5 s before transferring the dissected pupae carefully onto the heptane glue using forceps .For ease of wounding and imaging, line the pupae up in a row; approximately 5 pupae are suggested but more will be manageable with experience. Note: Use of heptane glue is recommended when using upright imaging systems but is not necessary when using an inverted system. If the glue creates optical aberrations during imaging, pupae can be placed directly on the coverglass instead – the natural adhesion between the pupal tissue and glass will be sufficient in most cases for stable imaging, as long as care is taken when moving the imaging dish between microscopes.Mount the pupae in a glass-bottomed dish using heptane glue. For best results, mount the pupae so that the wing is flat on the coverglass with the majority of the wing surface in direct contact with the coverglass . Roll thTo prevent sample dehydration during the imaging period, add a piece of absorbent filter paper soaked in distilled water to the side of the glass-bottomed dish at the end of mounting, being careful not to disturb the pupae . Cover tTable of Materials for detailsUse a pulsed-UV air-cooled nitrogen-pumped ablation laser tuned to 435 nm – see Transfer the glass-bottomed dish containing the mounted pupae to a wide-field microscope equipped with a tunable laser ablation system. Using brightfield optics, adjust the microscope stage controls to locate the pupal wing of the first pupa to be wounded .i.e. focus on the region of the epithelium to be wounded) using the fine focus control knob.For optimal results, use an oil immersion 40X or 63X objective lens for both the imaging and laser ablation; ensure that the immersion liquid used (oil or glycerol) is consistent between ablation and imaging systems. Adjust the microscope to focus on the plane of the pupal wing epithelium nearest the glass coverslip  and repeat the single click of the ablation trigger. Alternatively, gradually increase the laser power using the attenuator slide until the desired wound size is achieved.Repetition rate knob on the rear control panel (which changes the rate from less than 1 pulse/s up to 60 Hz). For optimal wounding, set the pulse repetition rate to 40 Hz.To vary the ablation laser pulse repetition rate, use the To generate different sized wounds, use the energy density attenuator slide to manually adjust the power level of the ablation light.Refrain from wounding all of the mounted pupae and use these non-ablated pupae as unwounded controls.For consistent results, regularly realign the ablation system . Also, clean and refill the dye resonator cell that controls the laser output wavelength.Quickly transfer the glass-bottomed dish to an appropriate microscope for time-lapse imaging. Note: For optimal results, use a high specification confocal or spinning disc microscope equipped with sensitive detectors that can detect both GFP and mCherry fluorophores.e.g. 20X) objective lens (-D).To image the entire pupal wing, use a low magnification  and adjust the laser power and gain/offset settings to give sufficient fluorescent signal whilst avoiding pixel saturation; use the lowest possible laser power (in the range 5 - 20%) to minimize photobleaching and phototoxicity.Using the image capture software, turn on the appropriate lasers To capture both the repairing epithelium and inflammatory cell recruitment, set the microscope to record a z-stack using the fine focus adjustment knobs on the control panel; for optimal results, set the software  to record z-slices through the pupal wing (minimum every 3 mm), from the top of the wounded epithelium through to the extracellular space beneath (containing migrating hemocytes) to achieve a large z-stack (in the range of 50 - 100 mm).For time-lapse imaging, record z-stacks at regular time intervals (minimum every 30 s) for at least 1 h post-wounding. Note: The exact time interval between z-stacks chosen represents a trade-off between capturing the rapidly-changing cell dynamics and avoiding photo-bleaching of the samples.To simultaneously image multiple pupae (including non-ablated unwounded controls), use a motorized stage (attached to the microscope) and the multi-position acquisition feature available within the imaging software. Manually set the position of each individual pupa within the software using the stage position control knobs and then manually set the appropriate z-stack limits (top and bottom) for each individual pupa.’ and D’), track hemocyte nuclei using the open-access ImageJ plug-ins “TrackMate” or “Manual Tracking”  and activate the 405nm laser (by clicking in the relevant software box)Bleaching) to a single iteration/frame and set the 405 nm laser at 20% laser power. Manually click Start the experiment to perform photoconversion.Select cells to be photoconverted within the FRAP software using the square, circular or freehand selection tool. Within the FRAP software, set the time-course for photoconversion (Close) and return to the original imaging screen within the software; use the 488 nm and 561 nm lasers to image the behavior of photoconverted and non-photoconverted cells by setting up a z-stack and time-lapse recording as above. Note: Photoconverted probes remain stable for many hours after the initial photoconversion, enabling the behavior of the photoconverted cells to be followed over time (for at least 5 h). For example, inflammatory cells in the wound can be selectively photoconverted ( and H).Exit the FRAP module  post-wounding without significant photobleaching.This protocol describes the preparation of Drosophila pupae for in vivo imaging.  Drosophila white 'prepupae' are collected at '0 h' after puparium formation (APF), as the crawling larvae cease motility and adopt the stereotypical pupal shape with everted breathing appendages (spiracles) visible at their anterior-most end (-D). At this stage, other pupal body parts are also easily discernable, including the eyes, legs, and abdomen  may also contact the coverslip and are available for wounding and subsequent imaging (F). For experiments studying single wounds, laser-induced damages are generally best inflicted centrally in the wing . At this pupal stage, the wing epithelia are simple flat sheets of cells , large numbers of migratory innate immune cells  are found within the hemolymph (insect blood) occupying the intervening extracellular space ( 2A'). Laser-induced injury to the pupal wing epithelium  stimulates a rapid migration of hemocytes to the wound site . Labeling the hemocytes with both a nuclear marker (e.g. the nuclear RFP 'red-stinger') in combination with a cytoplasmic or cytoskeletal marker (e.g. cytoplasmic GFP or GFP-tagged Moesin) is particularly advantageous as it allows the simultaneous tracking of hemocyte nuclei  and the visualization of hemocyte morphology. The latter is important as it allows us to determine whether hemocytes are phagocytosing necrotic debris  demonstrates the complex spatio-temporal dynamics of the inflammatory response, similar to that reported previously for wounded embryos9D'). Within just 30 min of wounding, hemocytes located closest to the injury site begin directed migration towards the wound Simple tracking of hemocyte nuclear trajectories using appropriate Image Analysis softwarehe wound '. Howevehe wound '. In thihe wound . By calisrp-Gal4  as they resolve away from the wound site  and compare how their behavior is different from those non-photoconverted cells that don't reach the injury site. We have used this in vivo labeling technique to demonstrate that hemocytes recruited to an initial wound are temporarily desensitized to a second wound generated 90 minutes laterMoreover, by driving expression of the photoconvertible fluorophore Kaede within the immune cell lineage using 4 green,  we have 4 green, -H as the arrows,  and H an-D). Here ubiquitously expressed GFP-tagged E-cadherin labels the cellular adherens junctions throughout the wing epithelium and allows the shapes of individual epithelial cells to be followed over time. The wound edge is easily identified as the junction between intact GFP-labeled epithelial cells and unlabeled debris . For the majority of wounds, the wound begins to re-epithelialize within 1 h of injury and the wound edge advances inwards  or GFP-tagged actin-binding Moesinin vivo imaging. Interestingly, the inflammatory response associated with these non-healing wounds is markedly different from that associated with normal acute woundsin vivo analysis of chronic wounds using long-term imaging (over 24 h) in the pupal model might provide important mechanistic insight into this debilitating condition.Using this approach, we can also simultaneously follow the spatio-temporal dynamics of wound repair or 're-epithelialisation' -D. Here  inwards ; wounds Drosophila pupa preparation for wounding and live-imaging. Figure 1: (A) Drosophila white prepupae collected at 0 h APF, with anterior end indicated by everted breathing appendages (spiracles). (B) After raising white 0h APF prepupae for 18 h at 25 °C, the puparium appears brown. Dissection of the pupal case should begin at the anterior-most region (arrow), indicated by the everted spiracles as the pupa proper is absent from this region, and fine forceps and/or microscissors used to remove the protective pupal case (C). The pupal wings will be visible on the lateral sides of the pupal thorax (blue outlines). (D) Pupal case completely removed from 18h APF pupa, here the pupa has been rolled 90° to show lateral side, with the wing to be imaged outlined in blue. (E-F) Five 18h APF pupae mounted on glass coverslip within imaging dish using heptane glue, with water-soaked filter paper to minimize dehydration (E). Pupa located third in the sequence (arrow) should be discarded as damage occurred during preparation. Pupae are mounted with the flattest portion of the wing (outlined blue) in contact with the coverslip (F) and laser-induced wounds are generated centrally in the wing , although other locations may be used if multiple wounds are to be studied. The image in (D) adapted with permission from Weavers et al., 2016Please click here to view a larger version of this figure.in vivo analysis of the inflammatory response to tissue damage.Figure 2: Dynamic  Pupae dissected from protective pupal cases and mounted on glass coverslip (A) are wounded and subsequently imaged using confocal time-lapse microscopy (B-H). Low magnification view of the unwounded pupal wing  that contains large numbers of migratory hemocytes (A'). Laser-induced injury to the pupal wing epithelium  activates a rapid inflammatory response with the migration of multiple hemocytes  towards the wound site . Manual tracking of hemocyte trajectories  indicate the complex spatio-temporal dynamics of the inflammatory response, similar to that reported for wounded embryos. Hemocytes also phagocytose necrotic cellular debris at the wound site . Expression of the photoconvertible fluorophore Kaede in the immune cell lineage  enables wound-recruited hemocytes  to be differentially labeled  and followed over time as they resolve from the injury site . The following pupal genotypes were utilized: (A-D) 1118w;ubi-DE-cad-GFP, srp-Gal4>UAS-GFP(II); UAS-nRFP(III) and (E-H) 1118;srp-Gal4(II); UAS-Kaede(III). wImages adapted with permission from Weavers et al., 2016Please click here to view a larger version of this figure.in vivo on 3-dimensional living samples in order for the precise behavior and interactions of the various cell lineages involved to be followed accurately over time. Real-time analysis of these cell dynamics allows a more detailed characterization of mutant phenotypes than static single time-points from fixed samples using classic immunohistochemistry techniques. Traditionally, most live-imaging studies using the genetically tractable Drosophila model have used the embryonic stage of fruitfly development due to its optical translucency and immobility compared to the later developmental stages4Drosophila pupa as a novel model to perform high resolution and long-term imaging of wound repair and inflammation simultaneously in vivo822Drosophila adipocytesThe acute inflammatory response to tissue damage is a complex and highly dynamic process that is essential to orchestrate the repair of injured tissues, including the clearance of necrotic debris and the fight against infection. To fully understand and unravel fundamental aspects of this response, it is crucial that studies are performed Drosophila pupae that will determine the quality of the imaging outcomes described above. Arguably the most difficult step of the described protocol is the careful dissection and precise positioning of the pupae prior to wounding and imaging. Pupae at this developmental stage are extremely fragile and even minor accidental damage to the pupae during preparation stages will significantly impair the experiment; any pupae that may have sustained unintentional damage must be discarded from the experiment since this damage could activate its own inflammatory response, which might lead to more wide-spread (or even systemic) effects on inflammatory cell behavior elsewhere in the pupa. Due to the ongoing development of the pupae utilized in these experiments (which are undergoing significant tissue rearrangements to prepare tissues for adulthood), occasionally pupae will move during the course of imaging. Pupal rolling is, however, more likely to occur if pupae have not been mounted correctly with the flattest surface of the wing (or other tissue to be imaged) in the direct contact with the coverglass; use of heptane glue to stabilize the pupae on the cover glass should minimize this undesirable movement. For this reason, great care must also be taken to avoid dislodging the pupae from their carefully aligned positions when moving the samples between microscopes; ideally, the wounding laser will be attached to the same microscope to be used for subsequent time-lapse imaging and photo-conversion.There are a number of critical factors during the preparation and imaging of wounded Drosophila pupae used will have a significant effect on the quality of the imaging data generated. For example, the number of copies of the Gal4 driver and UAS constructs (e.g. UAS-GFP or UAS-Kaede) within an individual pupal genotype will determine the signal-to-noise ratio during subsequent imaging. As a general rule, the more copies of a Gal4 or UAS construct present, the greater the total level of fluorescent protein (e.g. GFP or Kaede) within the tissue. The optimal level of fluorescent protein will, however, be a careful balance between elevating tissue fluorescence sufficiently to allow high quality imaging  but without causing fluorophore-induced cellular toxicity; the optimal number of Gal4 and UAS constructs in each experiment will vary according to the particular drivers and fluorophores being used. Care should be taken to raise the pupae at 25 °C  because the Gal4-UAS system is temperature sensitive and will be ineffective at lower temperaturesGal4-driven expression, the Gal4-UAS system repressor Gal80 can also be included within the pupal genotypelexAop and QF-QUAS systems) to generate Drosophila which has multiple constructs  expressed simultaneously in a range of different tissuesIn addition to the proficiency of the pupal dissection and mounting steps, the exact genotype of the Drosophila pupal model offers a number of advantages over the more traditional embryo approach. Compared to the short-term imaging (up to 3 h) available in stage 15 embryos (the stage at which most embryonic wounding studies are performed), pupae can be imaged over significantly longer periods of time . Moreover, far greater numbers of hemocytes (Drosophila innate immune cells) are present within pupal tissues (and available for imaging) compared to the more limited number present within the embryo and this has allowed us to gather significantly more imaging data on hemocyte behavior using the same total number of specimens. Crucially, this, in turn, has enabled us to apply more sophisticated mathematical modeling to analyze hemocytes behavior and extract novel features of the wound attractants and inflammatory response that would have otherwise remained experimentally inaccessibleUse of this new Drosophila pupae clearly cannot be used to study the phenotypes resulting from genetic mutations which are embryonic lethal; functional and live-imaging studies of genes that are essential for embryonic development must therefore still be performed in embryos, unless RNAi-mediated gene knockdown in a time or tissue-specific manner permits development to occur through to pupal stages. The embryo also remains the model of choice to study and live-image certain features of immune cell behavior, including the developmental dispersal of immune cells from their origin, contact-inhibition of locomotion and phagocytosis of apoptotic corpses generated during developmental tissue sculpting5Drosophila larvae and adults have provided an important insight into the mechanisms underlying wound repair and inflammation40414243Drosophila stages - from embryos through larval and pupal periods to adulthood (each with their own unique advantages and limitations) - will provide complementary insights into the molecular and cellular mechanism driving wound repair and inflammation.However, Drosophila pupae can be easily adapted to study a range of inflammation-related phenomena and has far-reaching potential for uncovering novel features of the inflammatory wound response. The combination of long-term imaging, together with the application of photoconvertible fluorophores (such as Kaede), are of great value for understanding the dynamics of innate immune cell behavior and in particular, the far less understood resolution phase of the wound inflammatory response. By specifically labeling either individual or subpopulations of immune cells (such as those recruited to a wound) it will be possible to analyze how exposure to one environmental cue (such as a corpse or injury) affects the immune cell's subsequent response to a later cue. The inflammatory behavior of Drosophila hemocytes can be altered by previous experiences - for example, they are primed to respond to tissue injury by prior phagocytosis of apoptotic corpses during developmentDrosophila together with the ease of long-term pupal imaging, novel epithelial repair or inflammatory regulators could be uncovered through the application of unbiased genome-wide knock-down approaches.In future, this protocol for wounding and long-term imaging of The authors declare they have no competing conflicts of interests.


Plasmodium parasites that infect the red blood cells (RBCs). Manual identification and counting of parasitized cells in microscopic thick/thin-film blood examination remains the common, but burdensome method for disease diagnosis. Its diagnostic accuracy is adversely impacted by inter/intra-observer variability, particularly in large-scale screening under resource-constrained settings.Malaria is a life-threatening disease caused by State-of-the-art computer-aided diagnostic tools based on data-driven deep learning algorithms like convolutional neural network (CNN) has become the architecture of choice for image recognition tasks. However, CNNs suffer from high variance and may overfit due to their sensitivity to training data fluctuations.The primary aim of this study is to reduce model variance, improve robustness and generalization through constructing model ensembles toward detecting parasitized cells in thin-blood smear images.We evaluate the performance of custom and pretrained CNNs and construct an optimal model ensemble toward the challenge of classifying parasitized and normal cells in thin-blood smear images. Cross-validation studies are performed at the patient level to ensure preventing data leakage into the validation and reduce generalization errors. The models are evaluated in terms of the following performance metrics: (a) Accuracy; (b) Area under the receiver operating characteristic (ROC) curve (AUC); (c) Mean squared error (MSE); (d) Precision; (e) F-score; and (f) Matthews Correlation Coefficient (MCC).It is observed that the ensemble model constructed with VGG-19 and SqueezeNet outperformed the state-of-the-art in several performance metrics toward classifying the parasitized and uninfected cells to aid in improved disease screening.Ensemble learning reduces the model variance by optimally combining the predictions of multiple models and decreases the sensitivity to the specifics of training data and selection of training algorithms. The performance of the model ensemble simulates real-world conditions with reduced variance, overfitting and leads to improved generalization. Plasmodium parasitic infection transmitted through the bite of female Anopheles mosquitoes. The parasites mature in the liver, are released into the human bloodstream and infect the red blood cells (RBCs) to result in fatal symptoms. Several species of the parasites exist including Plasmodium falciparum, P. vivax, P. ovale, P. Knowlesi, and P. malariae; however, P. falciparum can be lethal and infects the majority of global population. According to the 2018 World Health Organization (WHO) report, an estimated 435,000 malaria-related deaths are reported globally. Children under 5 years of age are reported to be the most vulnerable, accounting for 61% of the estimated death counts. The disease transmitted through Plasmodium falciparum has a high prevalence in Africa followed by South-East Asia and Eastern Mediterranean regions. An estimated US $3.1 billion has been reported to be invested worldwide in malaria control and elimination strategies by disease-endemic countries  tools using machine learning (ML) algorithms applied to microscopic blood smear images have the potential to reduce clinical burden by assisting with triage and disease interpretation. The promising performance of CNNs is attributed to the availability of huge amounts of annotated data. Under circumstances of limited data availability as in the case of medical images, transfer learning strategies are adopted. The CNN models are pretrained on large-scale datasets like ImageNet  to transLiterature studies reveal the application of conventional ML and data-driven DL methods toward the challenge of malaria parasite detection in thin-blood smear images. Ensemble learning strategies are often applied to obtain stable and promising model predictions. In this study, we evaluate the performance of custom and pretrained CNNs and construct an optimal ensemble model to deliver predictions with reduced bias and improved generalization toward the challenge of classifying parasitized and normal RBCs in thin-blood smear images. Compared to our previous study , we aim P. falciparum-infected patients and healthy controls and photographed using a smartphone camera. The slide images were manually annotated by an expert, de-identified, and archived. The Institutional Review Board (IRB) at the National Library of Medicine (NLM), National Institutes of Health (NIH) granted approval to carry out the study within its facilities (IRB#12972). A level-set based algorithm was applied to detect and segment the RBCs  custom CNN; (b) VGG-19 ; (c) Squ® 1080Ti graphical processing unit (GPU). The models are configured in Python using Keras API with Tensorflow backend and CUDA/CuDNN dependencies for GPU acceleration.We trained the models on an Ubuntu system with Xeon E5-2640v3 processor, 64GB Random Access Memory (RAM), and NVIDIAThe custom CNN model has three blocks of batch normalization, convolution, pooling, and convolutional dropout layers. The convolutional layers use 5 ×5 filters throughout the depth and same values for padding to maintain identical feature map dimensions. The first convolutional layer has 64 filters, the number of filters is doubled after every max-pooling layer. Usage of batch normalization layers reduces overfitting and improves generalization by normalizing the output of the previous activation layers. Non-linear activation layers add non-linearity into the decision-making process and speed up training and convergence . Usage ohttps://github.com/autonomio/talos). The process flow diagram of the optimization procedure is shown in We optimized the parameters and hyperparameters of the custom CNN model using the Talos optimization tool  with the Adam optimizer to minimize the categorical cross-entropic loss as not to rapidly modify the pretrained weights.The predictions of the custom and pretrained CNN models are averaged to construct the model ensemble. p < 0.05), the null hypothesis is rejected and the alternate hypothesis is accepted. This demonstrates the fact a statistically significant difference in the mean values of the performance metrics exists between at least two models under study. One-way ANOVA is an omnibus test that further needs post-hoc analyses to identify the specific models that demonstrate statistically significant differences  to determine the existence of a statistically significant difference . Howeverferences . We perfThe performance of the optimized custom CNN and pretrained models are evaluated toward the challenge of classifying parasitized and uninfected cells. The optimal values for the parameters and hyperparameters of the custom CNN, obtained with the Talos optimization tool are shown in p > 0.05  for both tests that signified that the assumptions of data normality and homogeneity of variances are not violated. The independence of observation existed and no significant outliers are observed. Hence, we performed one-way ANOVA to explore the presence/absence of a statistically significant difference in the mean values of the performance metrics for the models. p < 0.05) and the All-Ensemble model  is statistically significantly lower compared to the Ensemble-D model (0.995 ± 0.0005). A similar trend is observed for AUC where the AUC for Ensemble-D model and VGG-19 is 0.9993 ± 0.0004) and 0.993 ± 0.0006, p > 0.05) respectively. Considering the harmonic mean of precision and recall as demonstrated by the F-score, the Ensemble-D model (0.995 ± 0.001) outperformed the All-Ensemble  and VGG-19  models. Similar trends are observed for the performance metrics including MCC, precision, and MSE. The Ensemble-D model statistically significantly outperformed the VGG-19 and All-Ensemble model in all performance metrics.We performed the Shapiro–Wilk test to investigate for data normality and Levene’s test, for homogeneity of variances. We observed that Malaria Cell Analyzer App to which the user submits an image of the parasitized/uninfected cell and the model embedded into the browser gives the predictions.We deployed the trained model into a web browser to enable running the model at reduced computational cost and alleviate issues due to the complex backend, architecture pipelines, and communication protocols. A snapshot of the web application is shown in We ensured that the custom CNN converges to an optimal solution through (a) architecture and hyper-parameter optimization, (b) implicit regularization imposed by batch normalization, and (c) improved generalization through aggressive dropouts in the convolutional and dense layers. We performed cross-validation at the patient-level to present a realistic performance measure of the predictive models so that the test data represents truly unseen images with no leakage of information pertaining to the staining variations or other artifacts from the training data.CNNs suffer from the limitation of high variance as they are highly dependent on the specifics of the training data and prone to overfitting leading to increased bias and reduced generalization. We addressed this issue by training multiple models to obtain a diverse set of predictions that can be combined to deliver optimal solutions. However, it is imperative to select diversified base-learners that are accurate in diverse regions in the feature space. For this reason, we evaluated a selection of model combinations and empirically determined the best model combination to construct the ensemble for the current task. Experimental results are statistically significant for a given statistical significance level if they are not attributed to chance and a relationship actually exists. We performed statistical analyses to determine the existence of a statistically significant difference in the performance metrics of the individual and ensemble models under study. We also performed post-hoc analyses to identify the specific models demonstrating these statistically significant performance differences.It is observed that the ensemble model constructed with VGG-19 and SqueezeNet outperformed the other models and the state-of-the-art toward classifying the parasitized and uninfected cells to aid in improved disease screening.It is observed that model ensemble using multiple DL models obtained promising predictive performance that could not be accomplished by any of the individual, constituent models. Ensemble learning reduces the model variance by optimally combining the predictions of multiple models and decreases the sensitivity to the specifics of training data and training algorithms. We also developed a web application by deploying the ensemble model into a web browser to avoid the issues of privacy, low-latency, and provide cross-platform benefits. The performance of the model ensemble simulates real-world conditions with reduced variance, overfitting and leads to improved generalization. We believe that the results proposed are beneficial toward developing clinically valuable solutions to detect and differentiate parasitized and uninfected cells in thin-blood smear images.


Dramatic success in cancer immunotherapy has been achieved over the last decade with the introduction of checkpoint inhibitors, leading to response rates higher than with chemotherapy in certain cancer types. These responses are often restricted to cancers that have a high mutational burden and show pre-existing T-cell infiltrates. Despite extensive efforts, therapeutic vaccines have been mostly unsuccessful in the clinic. With the introduction of next generation sequencing, the identification of individual mutations is possible, enabling the production of personalized cancer vaccines. Combining immune check point inhibitors to overcome the immunosuppressive microenvironment and personalized cancer vaccines for directing the host immune system against the chosen antigens might be a promising treatment strategy. They express the checkpoint cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) which binds to B7 molecules on antigen presenting cells (APCs) and thereby hinders the interaction of CD28 molecules on T cells and the B7 molecules on APCs [An effective host immune response against cancer depends on an intact chain of carefully regulated steps known as the cancer-immunity cycle. The first event is the release of cancer antigens, followed by antigen presentation to T cells on dendritic cells via major histocompatibility complex (MHC) class I and II molecules. This leads to priming and activation of T cells, followed by trafficking and infiltration of T cells into the cancer. Recognition of target cancer cells by T cells and destruction of the cancer are the final steps of the chain which leads to release of additional cancer antigens and subsequently restart of the cancer immunity cycle . Cancer  on APCs .The avoidance of immune destruction is now recognised as one of the hallmarks of cancer . MonocloIn this review, we aim to provide an overview of the current understanding of the dynamic interaction between tumour and host immune system, focusing on the key steps required for efficient T cell priming and how these can be subverted by cancer. We then discuss strategies to amplify tumour-specific T cell responses through therapeutic active immunization with vaccines, and in combination with checkpoint inhibitors. Much work has gone into identifying tumour antigens able to drive effective T-cell responses against cancer . In geneTumour associated antigens are a group of non-mutant molecules that are “shared” by normal tissue and the cancer like overexpressed antigens or differentiation antigens. Amplification of genes like in Her2/Neu positive breast cancer can lead to overexpression of a normal protein. Differentiation antigens are molecules expressed on the cancer and on non-malignant cells of the same cell lineage, for example tyrosinase in melanoma cells which is also expressed in normal melanocytes. Since tumour associated antigens are self-proteins, they are more likely to have induced some form of centrally or peripherally mediated immunological tolerance often resulting in a reduced repertoire of immune effectors specific for the tumour associated antigen ,17,18. ATumour specific antigens are exclusively expressed by the cancer, and as such not subject to central tolerance, and are ideally suited as therapeutic targets. Oncogenic viral antigens can be used as targets in virus-associated cancers such as human papillomavirus (HPV) in cervical, anogenital and oropharyngeal cancers, hepatitis B virus in hepatocellular carcinoma and human herpesvirus 8 in Kaposi sarcoma ,21. CytoTumour neoantigens arise from a somatic mutation in the cancer and can be common recurrent mutations such as the BRAF V600E mutation or Kirsten rat sarcoma (KRAS) G12D [AS) G12D . HoweverAS) G12D  and withAS) G12D ,26. HighAS) G12D ,28,29. IAS) G12D ,31. The + T-cells on MHC class I molecules. In order to induce a potent immune response, the antigen released must be accompanied by the emission of damage-associated molecular patterns (DAMPs) [+ T-helper cells is necessary to generate effective CTL-mediated anti-tumour responses as well as long-lasting memory CTLs [The concept that the body can differentiate between self and non-self tissue earned Macfarlane Burnett the Nobel Prize in 1960  but a fu (DAMPs) ,44. Surf (DAMPs) . Present (DAMPs) . Binding (DAMPs) . The comory CTLs ,49,50.invisible’ to the immune system. Several mechanisms contribute to the defect of antigen presentation by tumour cells including firstly a lack of tumour antigens; a downregulation or loss of MHC expression, alterations of the machinery responsible for the loading of tumour antigens onto MHC or the loss of co-stimulatory molecules  which is essential for long lasting immune responses. The ability of DCs to cross present made them an ideal instrument for therapeutic use in the field of cancer immunotherapy. DC vaccines are generated ex vivo with the collection of monocytes from patients via leukapheresis which are then activated and differentiated in a laboratory, and subsequently loaded with whole tumour cells, DNA or mRNA encoding tumour antigens, or recombinant virus expressing tumour antigens as well as antigenic peptides or proteins [Dendritic cells (DCs) are the professional antigen-presenting cells of the immune system, capable of capturing exogenous antigens and not only presenting them in the MHC class II pathway but also presenting them in the class I antigen presentation pathway to CD8proteins ,63,64,65proteins . The IMPproteins . Secondlproteins ,67. Numerous trials utilising autologous DCs pulsed with autologous tumour RNA , synthetic mRNA encoding tumour antigens  and synthetic peptides are ongoing across multiple tumour indications ,68,69. HThis strategy involves the direct delivery of the antigen (either nucleic acid-based or peptide based) into the patient, usually with the aid of an adjuvant where they are internalised and processed by antigen presenting cells. In contrast to ex vivo approaches, these can be produced fairly easily and induce minimal if any toxic effects. Short epitope peptides are typically eight to ten amino-acids in length and directly bind to class I MHC molecules on the surface of immature DCs. However, as short peptides can also bind to class I MHC molecules on nonprofessional antigen-presenting cells  which lack co-stimulatory molecules and thereby do not induce immune responses, this may induce immune tolerance [Long peptides usually consist of 20–30 amino acids and require internalization by antigen presenting cells such as DCs.One of the key elements in creating peptide based vaccines is the length of the used peptides. olerance ,76. LongAntigens alone are often poor inducers of immunity which can result in immune tolerance instead of immunity. Therefore, adjuvants are needed as vaccine components to enhance immune response ,77. The tumour associated antigens with peptide-based cancer vaccines has been a long time focus of industry as they are shared by several cancer types. However, their use in clinical practice has been hindered so far by disappointing phase 3 clinical trials [Targeting l trials ,87,88,89l trials ,90,91. OWith the establishment of next generation sequencing (NGS) for detection of tumour mutations the idea of generating vaccines that target personal tumour neoantigens was born.Non-synonymous somatic mutations are identified by whole exome sequencing of tumours and normal-cell DNA from individual patients. The listed mutations are then ranked according to their likelihood of expression and affinity binding of the neoantigen to autologous MHC class I and II molecules which can be predicted by bioinformatic tools like NetMHCpan or IEDB ,59.+ and CD8+ T cells in pre and post-vaccination leukapheresis samples. Responses against one-fifth of the mutations were detectable in blood without in-vitro stimulation. Two of the five patients with metastatic disease experienced vaccine-related objective responses. Removal of lymph node metastasis in one patient confirmed vaccine-induced neo-epitope specific T cells in the tumour [The advantage of neo-antigens that arise from tumour specific mutation is that they are highly immunogenic since the cytotoxic T lymphocyte clones with high affinity for these antigens are unlikely to have been deleted by central tolerance. This concept has been investigated in a phase 1 study with six stage III and IV melanoma patients after surgical resection with curative intent. These patients received subcutaneous vaccinations of synthesized long peptides targeting up to 20 personal neo-antigens per patient, combined with the TLR 3 and melanoma differentiation associated protein 5 agonist poly-ICLC as immunostimulant. After a median follow-up of 25 months four patients remained without disease-recurrence . The IVAe tumour . A currently ongoing phase 1 study is investigating an intravenous formulation of a RNA based personalized vaccine in combination with the PD-L1 targeting agent atezolizumab in patients with solid tumours (NCT03289962).+ responses against predicted high-affinity binders were low as 29%, indicating the need for improvement of the used algorithms [With the possibility of parallel sequencing, a new era for antigen selection began. More challenging is identifying which of the listed mutations will induce the strongest immunogenicity in vivo . Bioinfogorithms . As cancer cells have evolved various mechanisms for immune escape, combination therapies are needed to restore antitumour-immunity. Conventional therapies like chemotherapy and radiotherapy can be used to support antigen release by cancer cell death. Checkpoint inhibitors release the break on endogenous T cells by blocking the negative regulatory pathway used by tumours. They have shown efficacy on their own in various cancer types, however, less success was achieved in tumours devoid of infiltrating lymphocytes . The lacTumour immunosuppression often correlates with tumour burden, making immunotherapy less effective in patients with advanced disease. In clinical trials immunologic response rates to vaccines are often higher during adjuvant treatment than in the palliative setting which provides a rationale for the use of vaccines in earlier stage of disease ,97,98. FWith tumour progression new mutations emerge which can lead to ineffectiveness of neo-epitope vaccines because of mutation and loss of the antigenicity of the neoepitope itself ,59. For The acceleration of NGS–omics technologies together with rapid progresses in bioinformatics heralds a very exciting era for research in oncology. There is abundant data detailing how a tumour is different from normal self tissue on a DNA, RNA and protein level. This does not only help the search for targeted therapies but also provides possibilities for personalized treatment approaches. Further development of techniques for collecting cell free DNA or circulating tumour cells are also likely to provide a more ‘up to date’ picture of the cancer, enabling approaches to overcome the problem of tumour heterogeneity and cancer evolution. Analysis of the tumour microenvironment and understanding strategies used by cancer to overcome immune evasion will also open the possibilities of successful combinatorial therapies.


RPGR) gene is one of the more severe forms, and female carriers of RPGR mutations have a variable presentation. A retrospective review of twenty-three female RPGR carriers aged between 8 and 76 years old was carried out using fundoscopy, autofluorescence imaging (AF), blue reflectance (BR) imaging and optical coherence tomography (OCT). Confirmation of the genetic mutation was obtained from male relatives or Sanger genetic sequencing. Fundus examination and AF demonstrate phenotypic variability in RPGR carriers. The genetic mutation appears indeterminate of the degree of change. We found four distinct classifications based on AF images to describe RPGR carriers; normal (N) representing normal or near-normal AF appearance ; radial (R) pattern reflex without pigmentary retinopathy ; focal (F) pigmentary retinopathy  and; male (M) phenotype . The phenotypes were precisely correlated in both eyes . Skewed X-inactivation can result in severely affected carrier females—in some cases indistinguishable from the male pattern and these patients should be considered for RPGR gene therapy. In the cases of the male (M) phenotype where the X-inactivation was skewed, the pattern was similar in both eyes, suggesting that the mechanism is not truly random but may have an underlying genetic basis.Inherited retinal degenerations are the leading cause of blindness in the working population. X-linked retinitis pigmentosa (XLRP), caused by mutations in the Retinitis pigmentosa GTPase regulator ( RPGR) gene [Retinitis pigmentosa is the most-common inherited retinal dystrophy with a worldwide prevalence of 1 in 4000. It is a heterogeneous group of disorders that can be inherited as autosomal dominant (30%–40% of cases), autosomal recessive (50%–60% of cases) or X-linked (5%–15%) [GR) gene .RPGR-related RP is one of the most severe forms of retinitis pigmentosa in males, with symptoms of nyctalopia within the first 10 years of life and progression to blindness within the third or fourth decade . TypicalRPGR, the severe phenotype can also be seen in female carriers [Despite the X-linked inheritance of carriers  and is ccarriers . X-linkecarriers .RPGR gene therapy currently undergoing clinical trials for males, there must be the consideration for therapeutic intervention in females who also suffer from the severe phenotype of retinitis pigmentosa.In this study, we categorise the female RPGR phenotypes using fundus autofluorescence (FAF) imaging and blue reflectance imaging to define the different levels of disease. With RPGR retinitis pigmentosa (NCT03116113) and via specialist genetic eye clinics. All females were confirmed as carriers either through male relatives screened and/or enrolled in the RPGR gene therapy trial (with genetic sequencing performed as per protocol) or through analysis of familial RPGR mutations.We reviewed 23 female carriers of X-linked Retinitis Pigmentosa who had been examined and imaged at the Oxford Eye Hospital. Patients were identified through ongoing gene therapy clinical trials for All patients underwent a complete ophthalmic examination, including logMAR best-corrected visual acuity (BCVA), standardized anterior and posterior segment examination and imaging. Imaging included fundus photography , spectral domain optical coherence tomography (SD-OCT), Spectralis HRA + OCT, , blue autofluorescence (B-AF) and, in some patients where AF categorization was not obvious, blue reflectance (BR) . B-AF images were obtained using a blue light excitation wavelength of 488 nm and recorded emission wavelengths were limited by a barrier filter to wavelengths between 500 and 700 nm.A total of 46 eyes of 23 consecutive RPGR patients  were included in this study. Differences in the fundus appearance on B-AF and BR imaging allowed us to identify four different patterns of presentation: N-pattern—normal or near-normal fundus appearance, the R-pattern—radial-spoke shaped reflexes extending from the central macular area in a radial pattern; the F-pattern—focal pigmentary retinopathy patchy pigmentation with a radial reflex pattern and the M-pattern—male pattern retinitis pigmentosa. In all cases, the pattern observed in one eye matched the other in the same patient. It is possible, however, that eyes of the same patient may be functionally discordant ,10.n = 1) was identified in one female with an X-linked family history and confirmed RPGR mutation but no retinal signs or symptoms of RP, see RPGR mutation observed in affected males of the same family. It is possible that with the progression of the disease, a radial reflex pattern may become more obvious.The normal (N) pattern (n = 14) shows a radial reflex without pigmentary retinopathy, see The radial (R) pattern (n = 5), the radial pattern is still present, but with areas of focal pigmentary retinopathy, as shown in In the focal (F) pattern (n = 3) represents females with the same male RP phenotype and a clinically significant visual impairment within the third or fourth decade of life, see RPGR carrier who had sufficiently severe vision loss to be enrolled in a clinical trial for an electronic retinal implant [RPGR gene therapy as part of another trial. Pedigrees for patients 21, 22, and 23 are shown in Lastly, male (M) pattern . There was no specific correlation between the location of the mutation and phenotype category; however, other studies such as Commander et al. have noted functional differences between mutations in the ORF15 region and exon 1–14 in RPGR . The resRPGR mutations are the third most common cause of dominant RP. In our cases, the family history of the three male pattern patients would be indistinguishable from the classic dominant inheritance [RPGR gene therapy.Here, we describe the spectrum of retinal degeneration in 23 female carriers of X-linked RP. In three patients (13%), we found a pattern indistinguishable to the male phenotype, verifying the previous finding that eritance . GeneticRPGR gene is located on the short arm of the X chromosome. It is ubiquitously expressed, playing a role in cilia-related body functions including the ears and respiratory tract. RPGRORF15 is the retinal-specific isoform located in the connecting cilium of photoreceptors and is thought to aid in the trafficking of molecules between the inner and outer segments [The segments . The repsegments .RPGR gene are associated with a cone-rod or rod-cone phenotype. The male phenotype of XLRP is well documented, but it has long been recognised that female carriers of X-linked retinitis pigmentosa can also suffer from visual dysfunction and display a retinal phenotype even without symptoms [RPGR female carriers that are thought to occur due to X-inactivation in early embryological development.Mutations in the symptoms . The disXist, located on the long arm of chromosome X, is a non-translated region of RNA in the X-inactivation centre (XIC). It aids in the counting, choosing and silencing process when deciding which X chromosome should be translated [Xist RNA is crucially translated in the inactive chromosome that is maintained throughout the cell line [X-inactivation is a chromosomal process in females. Either the maternal or paternal X chromosome is chosen at random and is passed down to daughter cells. A 50:50 ratio of the maternal and paternal X chromosome is expected . Xist, lanslated ,16. The ell line .RPGR or adjacent genes affect the translation or selection ability of the Xist RNA. Peripheral blood samples in this cohort and in other studies [Mutations may skew the inactivation process with the mutant allele being preferentially selected or inactivated, altering the ratio of mutant to wildtype X chromosomes selected. This may occur at any stage of X-inactivation and independently in the inner and outer retina due to their differing embryological origins. It is also possible that mutations in  studies  have not studies .RPGR. Additionally, patients two and three are twins and display similar phenotypes; however, twin 1 has a worse symptomatology. A long-term follow-up of patients is required to look at the progression of XLRP carrier phenotypes in more detail.Furthermore, RPGR-related retinitis pigmentosa  is currently in clinical trials for males. Additional interventional trials for severely affected females should, therefore, also be considered. Those female carriers categorised into the M-pattern are the most likely candidates for treatment; however, further formal assessments, such as visual field, scotopic microperimetry, electroretinography and assessment of stability and/or progression over time should be investigated to identify potential female candidates.At the other end of the spectrum, carriers with the M-pattern have the most severe phenotype with similar patterns described in men and visual acuities affected early in life. Gene therapy for


Epstein-Barr virus (EBV) is associated with a number of diseases, including malignancies. Currently, it is not known whether patients with different EBV-associated diseases have different methylation profiles of circulating EBV DNA. Through whole-genome methylation analysis of plasma samples from patients with nasopharyngeal carcinoma (NPC), EBV-associated lymphoma and infectious mononucleosis, we demonstrate that EBV DNA methylation profiles exhibit a disease-associated pattern. This observation implies a significant potential for the development of methylation analysis of plasma EBV DNA for NPC diagnostics. We further analyse the plasma EBV DNA methylome of NPC and non-NPC subjects from a prospective screening cohort. Plasma EBV DNA fragments demonstrate differential methylation patterns between NPC and non-NPC subjects. Combining such differential methylation patterns with the fractional concentration (count) and size of plasma EBV DNA, population screening of NPC is performed with an improved positive predictive value of 35.1%, compared to a count- and size-based only protocol. Epstein-Barr virus (EBV) is associated with different malignant diseases and circulating EBV DNA is a biomarker for nasopharyngeal carcinoma (NPC). Here, the authors report that plasma EBV DNA methylation profiles show disease-associated patterns and can help to distinguish NPC and non-NPC subjects. Because of such associations, circulating EBV DNA has been explored for its diagnostic role in different EBV-associated malignancies9. For NPC, plasma EBV DNA is a well-established biomarker for prognostication and monitoring for recurrence12. Its additional clinical utility for NPC screening of asymptomatic individuals was confirmed in a recent large-scale prospective study14. For other EBV-associated malignancies, plasma EBV DNA was also shown to have prognostic significance16. Recently, our group has identified different fragmentation patterns and size profiles of plasma EBV DNA between NPC and non-NPC subjects17. Based on this differentiating feature, we have developed a second-generation NPC screening test which could achieve a higher positive predictive value with only one testing. With better understanding of the molecular characteristics of plasma EBV DNA, it is possible that the diagnostic performance of plasma EBV DNA testing can be further enhanced.Epstein–Barr virus (EBV) is known as an oncogenic virus through its association with a number of malignancies of epithelial and haematological origins22 in different EBV-associated diseases. These studies on EBV DNA methylation have focused on the analysis of methylation status of specific gene regions 23. In one study, Fernandez et al.19 analysed the methylation status of 77 amplicons bearing transcription start sites in the EBV genome in the tumour tissues or cell line samples of different EBV-associated diseases. They showed that most gene promoters were methylated in tumour tissues or cell line samples of both NPC and EBV-associated lymphoma, whereas these promoters were unmethylated in cell lines in which the virus was in the lytic replicative state.EBV DNA methylation, as a key epigenetic characteristic, has been studied to understand EBV biology13. It is particularly challenging to analyse the methylation profiles of plasma EBV DNA when its concentration is expected to be low in early-stage cancers. We demonstrate the differential methylation patterns between NPC and non-NPC subjects, which could be potentially used to differentiate the two groups in the context of screening.Currently, it is not known whether patients with different EBV-associated diseases would have distinct methylation profiles of circulating EBV DNA. Hence, in the current study, we perform genome-wide methylation profiling of circulating EBV DNA in the plasma of patients with different EBV-associated diseases. We report that the viral genome-wide EBV DNA methylation profiles exhibit a disease-associated pattern among the different diseases under investigation. To illustrate the potential clinical utility of this observation, we perform methylation profiling of plasma EBV DNA of NPC and non-NPC subjects from a previous screening cohortWe performed genome-wide methylation profiling of plasma DNA from 15 patients with NPC, 9 patients with EBV-associated lymphoma  and 5 patients with infectious mononucleosis. The subject characteristics are shown in Supplementary Table Unsupervised hierarchical clustering analysis of the genome-wide methylation patterns of plasma EBV DNA was performed for all the 29 samples of EBV-associated diseases Fig. . The clu13. In such a screening context, approximately 5% of the general population harbours detectable levels of EBV DNA in their plasma by polymerase chain reaction (PCR)-based testing on one occasion24. These individuals would contribute to the false-positive group. It would be ideal if the test method could differentiate NPC patients from the false-positive group of non-NPC subjects with detectable levels of plasma EBV DNA. Here, we explored if we could differentiate the NPC from the non-NPC group by methylation analysis of their plasma EBV DNA.After identifying that distinctive plasma EBV DNA methylation patterns did exist amongst different EBV-associated diseases, we explored the potential clinical utility of such analyses in the context of cancer screening. Specifically, plasma EBV DNA analysis was recently validated for screening NPC13 were used to explore the clinical utility of methylation analysis of plasma EBV DNA. In the screening cohort of 20,174 asymptomatic male subjects, we identified 34 NPC patients and 1078 non-NPC subjects with detectable plasma EBV DNA at baseline by PCR-based testing. Since a two time-point testing protocol was adopted, these 1078 non-NPC subjects could be further classified into either a transiently positive group (positive at baseline and negative at the follow-up test) (n = 803) or a persistently positive group (positive at both the baseline and follow-up tests) (n = 275) based on their plasma EBV DNA test results.Archived plasma samples of NPC patients and non-NPC subjects with detectable plasma EBV DNA from the prospective screening trialIn the current study, we first explored the differences in the methylation profiles of plasma EBV DNA between NPC and non-NPC subjects in an exploratory sample set. The exploratory set consisted of 10 NPC patients and 40 non-NPC subjects (20 with transiently positive and 20 with persistently positive plasma EBV DNA results) randomly selected from the previous screening cohort. We subsequently validated our findings in the validation sample set which consisted of the remaining 23 NPC patients and another 120 randomly selected non-NPC subjects (90 with transiently positive and 30 with persistently positive plasma EBV DNA results) from the screening cohort. One NPC patient was not analysed because the sample had been exhausted. The number of non-NPC subjects to be included in the validation set was based on a power analysis, which would be described in the Methods section. The baseline plasma samples collected at enrolment into the screening study would be analysed. We have also included another 14 NPC patients from an unscreened cohort in the validation sample set. These 14 NPC patients in the validation set did not overlap with those NPC patients used for mining the NPC-associated differentially methylated regions (DMRs), which would be described in the next section. The subject characteristics are shown in Table We first identified the NPC-associated DMRs in the EBV genome. We pooled the sequencing data of all the 15 cases of NPC and 5 cases of infectious mononucleosis which we had analysed their plasma samples as described in Fig. To allow quantitative comparison of the methylation profiles of plasma EBV DNA between samples, we developed a metric, the EBV DNA methylation score, to represent the aggregated methylation levels for EBV DNA reads within the pre-defined NPC-associated DMRs. The methylation score was calculated by the following equation:The calculation of EBV DNA methylation score would be detailed in Methods and Supplementary Fig. p < 0.0001)  than non-NPC subjects with transiently positive  and persistently positive  EBV DNA results  Fig. . These rA cutoff value in the EBV DNA methylation score was defined at 3 standard deviations below the mean of the methylation scores of these 10 NPC patients in the exploratory dataset. The cutoff value of 73.7 was obtained Fig. . Using t17. In the current study, we evaluated if similar observations could still be obtained after bisulfite treatment of plasma DNA. For the count-based analysis, we analysed the proportion of all EBV DNA reads among the total number of human and viral sequenced reads after removal of PCR duplicates. In the exploratory sample set, NPC patients  had a statistically higher proportion of EBV DNA reads than non-NPC subjects with transiently positive  and persistently positive results    Fig. .The size-based analysis was based on the observation of a characteristic nucleosomal size profile of plasma EBV DNA from NPC patients. Plasma EBV DNA from non-NPC subjects, on the contrary, exhibited a different size profile. As a result, NPC patients had a lower proportion of short EBV DNA molecules (less than 110 bp) when compared to the non-NPC subjects. From our current bisulfite sequencing data, the size profiles of plasma EBV DNA from an NPC patient and a non-NPC subject are shown in Supplementary Fig. p < 0.0001)  was significantly lower than the median size ratios of samples from non-NPC subjects with transiently positive  and persistently positive results   Fig. .The proportions of EBV DNA reads and the EBV DNA size ratios for all the samples in the exploratory set were stated in Supplementary Data 17.The count- and size-based analysis results of NPC patients from our current exploratory dataset confirmed similar findings of the molecular profiles of plasma EBV DNA reported previously in the non-bisulfite sequencing dataset−5 was obtained  subjects with transiently positive and 5 (out of 20) subjects with persistently positive results who passed both all the three cutoffs. The calculated sensitivity and specificity were therefore 100% and 87.5%, respectively at these cutoffs   and the external cohort  had significantly higher EBV DNA methylation scores than non-NPC subjects with transiently positive  and persistently positive  results  Fig. . These r01) Fig. . The calWe performed a DMR down-sampling analysis and observed a decline in the area under the receiver operating characteristic (AUROC) values of the methylation-based analysis in NPC detection with serial down-sampling of DMRs  than the non-NPC cases with transiently (10.1 ng/mL) or persistently positive plasma EBV DNA (8.2 ng/mL)  . Noting the different amounts of plasma DNA input for different cases, we performed a down-sampling analysis of the sequencing data for the NPC and non-NPC cases in the validation cohort to evaluate the potential impact of sequencing depth on the performance of the methylation-based analysis. The down-sampling analysis showed comparable performances of the methylation-based analysis based on equal number of down-sampled reads and that based on all fragments  and external  cohorts had significantly higher proportions of plasma EBV DNA reads than non-NPC subjects with transiently  and persistently positive  results   non-NPC subjects with transiently positive and 10 (out of 30) subjects with persistently positive results who passed the cutoff in the count-based analysis  Fig. . All thesis Fig. . The cal.1 × 1001p < 0.0001)  and external  cohorts had significantly lower EBV DNA size ratios than non-NPC subjects with transiently  and persistently positive  results  Fig. . With th01) Fig. . The calUsing the cutoffs defined in the exploratory dataset, in the combined methylation-, count- and size-based analysis, all the samples of NPC patients in the validation set could be captured. There were 4 (out of 90) subjects with transiently positive and 3 (out of 30) subjects with persistently positive results who passed all the three cutoffs. The sensitivity and specificity of the combined analysis in the validation set were calculated to be 100% and 94.2%, respectively  non-NPC subjects with transiently positive, 3 out of 30 (10%) subjects with persistently positive and all 23 (100%) NPC patients passed the three cutoffs in the combined analysis. When taken into account that one subject with undetectable plasma EBV DNA by PCR-based testing developed NPC within 1 year, the sensitivity of the current protocol would be 97.1%. The estimated number of subjects with false-positive test results from the combined analysis was 63 (4.4% × 803 (transiently positive group) + 10% × 275 (persistently positive group)). The estimated specificity would be 99.7%. The corresponding PPV and false-positive rate would be 35.1% and 0.31%. The modelled performance of the methylation-, count-, size-based and combined analysis is shown in Table The above data indicated that the best screening performance for NPC could be obtained from the simultaneous analysis of the methylation, quantitative and size profiles of plasma EBV DNA. While the real-time PCR-based detection of plasma EBV DNA achieved a high negative predictive value, this combined methylation-, count- and size-based analysis would best serve as a confirmatory test to differentiate NPC from non-NPC subjects with detectable EBV DNA by PCR-based analysis. A plasma sample was considered as test-positive in the combined analysis if it simultaneously passed the methylation-, count- and size-based cutoffs. We modelled the diagnostic performance of incorporation of this combined analysis in the entire set of our previously reported screening cohortOur current study reports the genome-wide methylation profiles of plasma EBV DNA in NPC, EBV-associated lymphoma and infectious mononucleosis. In our clustering analysis of plasma EBV DNA methylomes, we observed that samples from different patients within the same group of EBV-associated disease were clustered together and yet they were more distant from samples of different classes of diseases. These results implied that distinctive plasma EBV DNA methylation profiles existed among the different diseases that we have investigated. We then explored the clinical potential of such an observation and developed the methylation-based analysis of plasma EBV DNA and showed that it improved the specificity of EBV DNA-based NPC screening test.SEPT9 as a blood-based marker for detection of colorectal cancer, with a reported sensitivity of 44.7% for stage I–II diseases in a prospective evaluation28. Assay sensitivity is particularly important in the screening setting when low concentrations of circulating tumour DNA and therefore relatively weak cancer signals would be expected for early stage cancers. In the present work, the NPC-associated DMRs were mined from the NPC and the infectious mononucleosis cases described in Fig. Using the archived plasma samples from the previous screening cohort, the methylation-based analysis of plasma EBV DNA was shown to achieve a high specificity of NPC identification at an observed sensitivity of 100%. The high diagnostic performance of the methylation-based analysis was contributed by the use of sequencing-based analysis and the selection of NPC-associated DMRs. Bisulfite sequencing allowed simultaneous analysis of a multitude of methylation markers across the whole viral genome. This is in contrast to the analysis based on a single methylation marker which might theoretically result in lower sensitivity for detection of cancer. This is supported by the result of our DMR down-sampling analysis, in which we have observed a decline in the AUROC values of the methylation-based analysis in NPC detection with serial down-sampling of DMRs. It might be worthwhile to explore the development of multiplex methylation-specific PCR targeting multiple DMRs as an alternative to a sequencing-based approach. An example outside of the EBV field is the use of methylated 17. The combined analysis of the quantitative and size profiles through non-bisulfite sequencing was shown to allow identification of NPC patients in the screening cohort at an improved specificity of 99.3% and PPV of 19.6%17. From the bisulfite sequencing dataset in our current study, the differences in the quantitative and size profiles of plasma EBV DNA between NPC patients and non-NPC subjects could still be observed. Indeed, by just analysing the quantitative and size profiles in the current bisulfite sequencing dataset, we obtained a modelled specificity of 99.1% and PPV of 16.6% in NPC identification. These values were very similar to those reported from the non-bisulfite sequencing analysis. Importantly, this bisulfite sequencing-based technology allowed the combined methylation-, count-, and size-based analysis of bisulfite-treated plasma DNA samples, which offered synergistic effect in the diagnostic performance and boosted the PPV. The prospectively collected plasma samples from our previous screening cohort provided a valuable and unique sample set to test the combined approach. This combined approach was shown to achieve a PPV of 35.1% without compromising the detection sensitivity. These results represent a significant improvement when compared to the reported PPV of 11.0% from the published two time-point PCR-based testing protocol13. The substantial improvement in PPV would be translated into a reduction in medical costs on confirmatory investigations. The impact would be pronounced if a mass screening programme based on this combined analysis of plasma EBV DNA is to be launched in endemic regions.We have previously identified the differentiating quantitative and size profiles of plasma EBV DNA between NPC and non-NPC subjects through non-bisulfite sequencing29. In our previous screening cohort, we observed that there was a correlation between the proportion of screened subjects with plasma EBV DNA positivity, but who did not have NPC, with increasing age29. Interestingly, there was also a negative correlation between the proportion of screened subjects with plasma EBV DNA positivity, but who did not have NPC, with the ambient temperature on the day of blood sampling29. These results29 suggested a possible correlation with weakened immunity which might lead to viral reactivation and replication. Our current study provides another piece of evidence by predicting the origin of viral fragments based on the methylation signatures. We have shown that the plasma EBV DNA molecules from non-NPC subjects were more hypomethylated than those from NPC patients. This molecular feature is in accordance with our understanding that EBV DNA from lytic replication by the viral DNA polymerase is unmethylated19. Our current study hence provides epigenetic evidence that the source of EBV DNA in plasma of non-NPC subjects is from viral reactivation.We hypothesised that non-NPC subjects harbour EBV DNA in plasma as a result of viral replication from transient immune suppression30. It would also be exciting to extend the concept beyond EBV for studying the methylation profiles of circulating nucleic acids of other oncogenic viruses, for example, hepatitis B virus and human papilloma virus31.This work has provided a framework for studying the methylation profiles of circulating viral nucleic acids. We illustrated the potential clinical utility of analysing the plasma EBV DNA methylome in the context of NPC screening. It would be worthwhile to develop EBV DNA methylation markers for other EBV-associated diseases. One potential application may include monitoring of the treatment response to the specific chemotherapy of demethylating agents, e.g., azacytidine, in EBV-associated malignanciesIn our current study, the total number of NPC patients analysed in both the exploratory and validation cohorts is relatively small, as limited by the number of NPC samples  from the prospective screening cohort. Therefore, we have included 14 additional NPC samples from an external cohort in the validation set. We thus believe that the robustness of the methylation-based analysis of plasma EBV DNA in differentiating NPC from non-NPC samples is well supported.32, this may be more typical for patients with advanced-stage cancers35. In contrast to this belief, we observed lower concentrations of total plasma DNA in the screening cohort of NPC cases. For this screening cohort, the majority of the NPC cases were early-stage diseases. We also note that the total plasma DNA concentrations were higher in the external cohort with advanced-stage NPC. In the published literature, there is a lack of information on the spectrum of total plasma DNA concentrations in NPC patients. In future studies we may explore the total plasma DNA concentration among NPC patients of different stages in particular those with early stage disease to see if similar findings will be observed. To address the pre-analytical difference in the total plasma DNA concentration as a potential confounder in our study, we have performed the down-sampling analysis of the sequencing data of all the NPC and non-NPC cases in the validation cohort  (seventh edition). The clinical staging of lymphoma patients was based on the Ann-Arbor staging system.36. The exploratory and validation cohorts consisted of samples of NPC and non-NPC subjects randomly selected from the prospective screening study (simple randomisation). The exploratory cohort consisted of 10 NPC patients and 40 non-NPC subjects (20 with transiently positive and 20 with persistently positive plasma EBV DNA results) randomly selected from the screening study. The validation cohort consisted of the remaining 23 NPC patients and 120 randomly selected non-NPC subjects (90 with transiently positive and 30 with persistently positive plasma EBV DNA results). There is no significant difference in the mean plasma EBV DNA concentrations measured by the real-time PCR analysis between the 120 non-NPC subjects in the validation set and all the 1078 non-NPC subjects from the screening cohort . There is no statistically significant difference in the stage distribution (stages I and II versus stages III and IV) of NPC patients from the screening cohort between the exploratory and validation sets . Samples in the two cohorts did not overlap. The validation analysis was performed in a blinded manner. In the training phase, we first performed isolated methylation-, count- and size-based analyses of the bisulfite sequencing data of NPC and non-NPC samples from the exploratory cohort. The definitions of the methylation-, count- and size-based parameters in the corresponding analyses were locked down before validation. Cutoff values of these three parameters were determined solely based on the exploratory dataset with reference to the means and standard deviations and were also locked down before validation. Then, we performed the combined methylation-, count- and size-based analysis in the exploratory dataset. In the combined analysis, a plasma sample was flagged as positive if its sequencing data concurrently passed the three corresponding cutoffs. The analytical definitions of the combined analysis and the cutoffs were locked down before validation. The diagnostic performances (sensitivity and specificity) of the isolated and combined analyses were subsequently evaluated in the validation cohort.The study design is described with reference to the REMARK guidelinesA power analysis was performed to determine the number of non-NPC subjects required in the validation sample set given that we analysed 23 NPC patients from the screening cohort. Based on the means and standard deviations of the EBV DNA methylation scores of NPC patients and non-NPC subjects in the exploratory sample set, if we would reproduce the observed difference in the validation set at a significant level of 0.001 and a power of 0.999, at least 82 non-NPC subjects would be required.g for 10 min at 4 °C then re-centrifugation of the plasma portion at 16,000g for 10 min at 4 °C to remove the residual blood cells. All the plasma samples were stored at −80 °C. For all the samples analysed, plasma DNA was extracted from 4 mL of plasma. DNA from plasma was extracted using the QIAamp Circulating Nucleic Acid Kit (Qiagen).Peripheral blood samples were collected into EDTA tubes and immediately stored at 4 °C before further processing. The centrifugation protocol was as follow: centrifugation at 160041 was shown to achieve a high conversion rate with minimal intra- and inter-individual variabilities. After bisulfite treatment, the DNA was amplified with 13 cycles of PCR using the KAPA HiFi Uracil + ReadyMix PCR Kit (KAPA Biosystems).Plasma DNA libraries were constructed using the TruSeq Nano DNA Library Preparation Kit (Illumina) according to the manufacturer’s protocol. The adaptor-ligated DNA molecules were subjected to two rounds of bisulfite treatment using Epitect Plus Bisulfite Kit (Qiagen). The protocol of two-round bisulfite treatmentTarget enrichment of EBV DNA molecules from the plasma DNA samples was done via the capture-probe system. We designed the EBV capture probes to cover the entire EBV genome, which were then synthesised by Roche NimbleGen . The probes would be specifically designed to capture both converted (unmethylated) and unconverted (methylated) DNA fragments after bisulfite treatment. Multiplexing of DNA libraries from four plasma samples in one capture reaction were performed. Equal amounts of DNA libraries for each sample were used. We had also included probes to cover human autosomal regions from all, except the sex chromosomes, as a reference set. The BED file with the EBV and autosomal regions for the capture-probe design is included in the Supplementary Information (Supplementary Data Two plasma DNA samples (TBR1765 and TBR2003) from two male patients with advanced NPC were evaluated with serial 10-fold dilutions . The measured concentrations of EBV DNA by quantitative PCR for samples TBR1765 and TBR2003 were 24,625 and 26,750 copies/mL, respectively. The diluent for the serial dilution consisted of plasma DNA from a separate healthy male individual for each of the NPC sample. The concentrations of plasma DNA from the two healthy control plasma samples for dilutions of TBR1765 and TBR2003 were 955 and 1182 copies/mL, respectively. A linear relationship between the number of sequenced EBV DNA fragments and the dilution factor could be observed for the range of 500–1.5 million EBV DNA fragments . A 76 × 2 paired-end sequencing protocol was used.42 developed by our group to perform sequence alignment and methylation call. The sequence reads were aligned to the combined reference genomes including reference human genome (hg19) and EBV genome (AJ507799.2). The methylation densities of all the CpG sites across the viral genome were deduced. The DMRs were mined based on the criteria described in the main text. The quality control statistics for all the cases in Fig. The paired-end bisulfite sequencing data were analysed by the Methy-Pipegenome hg9 and EBVFor the identification of NPC-associated DMRs, we defined a CpG site as differentially methylated if the methylation density of the site was >80% in the pooled sequencing data of 15 NPC cases and <60% in the pooled data of 5 infectious mononucleosis cases shown in Fig. All the sequenced EBV DNA reads within DMRs would be used to determine the total depths at CpG dinucleotides within the DMRs. The fraction of unconverted cytosines (methylated) over the sum of unconverted cytosines (methylated) and converted thymine (unmethylated) present in its total depth at CpG dinucleotides within DMRs was used to define the methylation score as shown by Eq. . If one Cutoff values of the three parameters in the methylation-, count- and size-based analyses were determined solely based on the exploratory dataset with reference to the means and standard deviations. In the methylation-based analysis, a cutoff value in the EBV DNA methylation score was defined at 3 standard deviations below the mean of the methylation scores of these 10 NPC patients in the exploratory dataset. In the count-based analysis, a cutoff value was defined at 3 standard deviations below the mean of the logarithmic values of  the portion of EBV DNA fragments of the same 10 NPC patients, assuming EBV DNA quantity follows the Gaussian mixture distribution. In the size-based analysis, a cutoff value was defined at 3 standard deviations above the mean values of the EBV size ratios of all the 10 NPC patients.We performed a DMR down-sampling analysis with 100 simulations. In the analysis, with the serial down-sampling of the 158 DMRs, we evaluated the AUROC values of the methylation-based analysis at the corresponding number of DMRs in the validation cohort using the statistical R package pROC. As shown in the Supplementary Fig. p < 0.0001). The performance of the methylation-based analysis based on the down-sampled reads  is comparable to that based on all fragments .Noting the different amounts of plasma DNA input for different cases, we performed a down-sampling analysis of the sequencing data for the NPC and non-NPC cases in the validation cohort to evaluate the potential impact of sequencing depth on the performance of the methylation-based analysis. From the raw sequencing data, we first removed PCR duplicates of total mapped DNA fragments of all NPC and non-NPC samples in the validation cohort to obtain what would subsequently be termed deduped fragments. The total number of deduped fragments obtainable for 95% of the cases (NPC and non-NPC) in the validation cohort was 9,383,179. We then down-sampled the deduped fragments from all cases to 9,383,179 reads per case. Seven cases in the validation cohort had deduped fragment counts lower than this level and were excluded from the down-sampling analysis. Then we calculated the EBV DNA methylation score on the down-sampled reads for each included case. As shown in the Supplementary Fig. p < 0.001). These results suggested that the methylation-based analysis could provide additional differentiating power of NPC from non-NPC samples independent of count-based analysis.We have also performed down-sampling of EBV DNA fragments among NPC and non-NPC samples in the validation set. Plasma EBV DNA fragments were down-sampled to equal levels  to ensure similar viral genome coverage for different samples. The EBV DNA methylation scores were then calculated using the same down-sampled amount of EBV DNA fragments in each scenario (Supplementary Fig. p value of <0.05 was considered as statistically significant.The Kruskal–Wallis test was used to compare the EBV DNA methylation scores, proportion of EBV DNA reads and EBV DNA size ratios in the three groups. A Further information on research design is available in the Supplementary InformationSupplementary Data 1Supplementary Data 2Supplementary Data 3Reporting SummaryDescription of Additional Supplementary FilesSource Data


VHL) tumor suppressor gene in > 70% of sporadic cases. VHL inactivation is linked to constitutive expression of Hypoxia Inducible Factor 1 or 2 alpha (HIF- 1/2α) and therefore increased transcription of the Vascular Endothelial Growth Factor (VEGF) gene.Despite several improvements during the last decade, metastatic renal cell carcinoma (mRCC) remains incurable. However, mRCC represent a general paradigm of tumor vascularization. The molecular mechanism linked to the exacerbated angiogenesis in these tumors was considered as relatively simple: inactivation of the von Hippel Lindau  if no metastasis is detected by CT scan, treatment relies on partial or complete removal of the affected kidney then surveillance every six months; ii) in case of metastasis, two strategies are available; anti- VEGF monoclonal antibodies bevacizumab/Avastin in combination with interferon alpha induced a revolution in the field by increasing the time to progression of metastatic patients ; sunitinet al described an evolution of renal cancers treatment, from the dark-age in the 1990s to the modern-age during the 2000s 2010s and we currently experiencing the beginning of the golden-age [The development of these different strategies is a “scholar case” and highlights renal cancers as one of the most active field for the development of new therapeutic tools. Hence, Hsieh However, simple observations have to be emphasized according to patients’ specificity and treatments:Despite equivalent clinico-pathological characteristics, tumors present a different response to the same treatment. The survival of 4543 patients treated with sunitinib ranged from few months to few years without satisfactory explanations . This heCurrent treatments target tyrosine kinase receptors . More recently, targeting the c-MET pathway was considered relevant . Inhibitet al proposes an elegant strategy based on the following rationale: i) several tyrosine kinase receptors are involved in exacerbated angiogenesis and growth of kidney cancers; ii) all tyrosine kinase receptors activate the PI3 Kinase and Src kinase. Hence, targeting paramount signaling pathways down-stream of tyrosine kinase receptors should be highly efficient and less submitted to tumor cell adaptation. The authors have focused on two drugs used in clinical trial; the GDC-0941 (PI3 Kinase inhibitor) and Saracatinib (Src Kinase inhibitor). Independently, these two drugs have a modest activity on different in vitro parameters of tumors cells aggressiveness. However, the authors observed a synergistic anti-tumor effect by combining both drugs. As described above, VHL inactivation happens in > 70% of renal cancers. However, the VHL wild-type tumors are more aggressive [et al further showed that VHL negative cells re-expressing VHL are more sensitive to the GDC-0941/Saracatinib combination. Therefore their strategy might be relevant for highly aggressive tumors.In accordance with these considerations, new strategies must be developed to chronicize or even to cure metastatic kidney cancers. The paper of Roelants gressive . Roelantin vitro results were confirmed on ex vivo explant cultures from renal tumor Patient-Derived Xenografts (PDXs) and experimental tumors in mice.The et al represent a real breakthrough in the field of treatment of renal cancers. Since the two tested drugs are currently in clinical trials for other pathologies, new phase I/II trials based on this relevant rational would deserve to be launched.Together, the results of Roelants