Although these genomic imprinting errors are undetected in the somatic tissues after birth, further research is warranted to examine potential germ cell transmission of epimutations and the potential risks of reproducing cattle using artificial reproductive technologies.Animal breeders have made widespread use of assisted reproductive technologies to accelerate genetic improvement programs aimed at obtaining more, better and cheaper food products. Selection approaches have traditionally focused on Mendel’s laws of inheritance using parental phenotypic characteristics and quantitative genetics approaches to choose the best parents for the next generation, regardless of their gender. However, apart from contributing DNA sequence variants, male and female gametes carry parental-specific epigenetic marks that play key roles during pre- and post-natal development and growth of the offspring. We herein review the epigenetic anomalies that are associated with artificial reproductive technologies in current use in animal breeding programs. For instance, we demonstrate that bovine embryos and fetuses derived by  Artificial reproductive technologies (ART) have been widely applied to improve the fertility of domestic species, particularly in bovine livestock production systems. From the less invasive ART of artificial insemination using frozen semen to the most recent advances in animal cloning by somatic cell nuclear transfer (SCNT), few studies have focused on the potential long term consequences, both positive and negative, of reproductive technologies to domestic animal health and welfare . Moreoven = 19; sheep, n = 17; pig, n = 22) compared to the much larger number already identified in humans (n = 95) and mice (n = 123). Nonetheless, imprinted genes have been found in livestock to affect traits such as milk yield, growth and carcass quality, fat and meat deposition and fetal development. For instance, the paternally expressed imprinted gene insulin-like growth factor 2 (IGF2) has been associated with meat traits and body weight in beef cattle  and the more recent use of DNA polymorphisms (genomic selection) will be useful to improve animal selection schemes, as indicated by timely recent review articles on this topic , which provides a listing of genes by species, only a few imprinted genes have been identified in domestic species  during gametogenesis and then in the zygote immediately after fertilization. The widespread epigenetic reprogramming in PGCs is associated with a global demethylation and is thought to be important for preventing the transmission of inappropriate epigenetic information to the next generation. Although zygotic demethylation seems to occur globally, some genomic sequences, including imprinted genes, maintain methylation during preimplantation and are essential for proper development. Moreover, some histones are retained at non-random genomic locations in the sperm  and can H19 (non-protein coding) is silenced on the paternal allele, thus enabling IGF2 paternal expression. On the other hand, H19 is expressed from the non-silenced maternal allele where it blocks IGF2 maternal expression. In contrast, the small nuclear ribonucleaoprotein polypeptide (SNRPN) gene is silenced on the maternal allele and, thus, is monoallelically expressed from the paternal allele. Moreover, the receptor for IGF2 (IGF2R) is transcribed exclusively from the maternal allele due to the repression of paternal transcription by the non-coding AIR transcript. The epigenetic processes of DNA methylation and histone modulation are both involved in achieving monoallelic expression of imprinted genes. The numerous human genetic diseases associated with imprinted genes, including Beckwith–Wiedemann syndrome , LOS commonly presents placental perturbations, leading to high birth weights and reduced survival rates. The incidence of such placental failures is especially important in cloning by nuclear transfer and IVF, representing the major cause of pregnancy failure in these animals , we were able to identify SNPs in proximity to the DMR and exonic polymorphisms that enabled analysis of the imprinting status of several genes, including the maternally expressed H19 and IGF2R genes, and the paternally expressed SNRPN gene. Analysis was performed on day-17 pre-implantation embryos, in post-implantation embryonic and extra-embryonic (placenta) tissues at around day 40 of gestation and in full term offspring. In general, we observe a de-methylation of the DMR at early embryonic stages (day 17) of development followed by a partial or complete re-methylation of the affected DMR of all three imprinted genes at the fetal stages (day 40–50) of development  and extra-embryonic (placenta) tissues , suggesting that the hypomethylation patterns observed in these tissues are insufficient to induce maternal expression. Nonetheless, placental tissues remained bi-allelic beyond implantation, indicating that the extraembryonic tissue may sustain higher levels of hypomethylation. In contrast, SCNT-derived embryonic and extra-embryonic tissues showed substantial bi-allelic expression and DMR hypomethylation, indicating that even embryos with severe epigenetic anomalies to SNRPN can survive beyond implantation.Methylation patterns of the  embryos , suggest tissues . SurprisH19 gene in cattle  and extra-embryonic (placenta) post-implantation tissues, indicating that the hypomethylation levels were insufficient to enable expression from the paternal allele. Interestingly, overall transcript abundance levels of IGF2, but not H19, were slightly increased in the placenta of SCNT-derived gestations. Since SCNT embryos are usually smaller, it is possible that increased IGF2 expression adversely affects the growth rate of the embryo itself.To extend our finding to other bovine imprinted loci, we identified SNPs in the DMR and the transcript (cDNA) of the n cattle . AnalysiIGF2R gene is between 2 to 2.7 kb in length and is localized in the second intron, approximately 4.4 kb upstream from exon 2 and 2.2 kb downstream from exon 3  fetal fibroblasts using transduction with a polycistronic excisable lentivirus containing mouse Oct4, Sox2 c-Myc, and Klf-4 transcription factors have indicated the H19 and SNRPN DMRs are hypomethylated in some iPS lines  cells. Recent preliminary studies with bovine iPS cell lines developed from F1 hybrid (s Figure . MoreoveSNRPN, H10/IGF2, and IGF2R imprinted genes are extensively hypomethylated in the early stage embryos derived by SCNT and to a lesser extent also in IVP embryos, indicating that the reprogramming of the chromatin and the culture in vitro of oocytes and or embryos causes epigenetic erasure of imprinted loci. Moreover, fewer epigenetic anomalies are observed at later stages of development, suggesting that the imprinted DMRs are either re-methylated during development or that only the less affected embryos survive to later stages of gestation and to term.In general, DMRs of in vitro, particularly with cloning by SCNT, further care must be taken when utilizing ART to improve the reproductive performance or accelerate the dissemination of valuable livestock genetic material. However, animals that develop to term seem to retain normal methylation patterns of regulatory regions that control the expression of imprinted genes regardless of their health status, suggesting that embryos carrying harmful epimutations may be selectively eliminated before birth. On the other hand, epigenetic variants that improve survival could be useful for generating animals with increased efficiency. Finally, epigenetic modifications to animals derived by ART could bring transgenerational advantages and risks to animal breeding programs.Epigenetic errors are likely to have significant effects on the prenatal and postnatal phenotype of domestic animals. Strategies aiming to modify the epigenome by promoting or inhibiting methylation/acetylation drugs prior or during SCNT have been used, however, results remain inconsistent . Since eThe authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Acinus (Acn) is a nuclear protein that participates in the regulation of autophagy. Loss of Acn function prevents autophagy in starving cells. Conversely, Acn activation induces basal autophagy. This enhances the quality control functions of autophagy such as the removal of misfolded proteins, thereby reducing neurodegeneration and prolonging lifespan. Acn activity is enhanced by Akt1-mediated phosphorylation, which counteracts the cleavage of Acn by a caspase-3 homolog.  In a second role, autophagy operating at basal levels contributes to quality control in cells and aids in the removal of aberrant proteins or organelles that can accumulate in response to a variety of cellular stresses. It is important to understand how the basal level of autophagy is adjusted to varying degrees of stress in the absence of starvation as failures in quality control have been linked to neurodegenerative diseases, inflammation, and cancer.2 indicates that Acinus (Acn) protein may play a role in that regulation. Acn is a conserved nuclear protein that interacts with the exon junction complex and spliceosomes and thereby modulates specific RNA splicing events3, 4. The first indication of a role in autophagy came from acn loss-of-function mutations, which interfere with autophagosome maturation.5 In well-fed Drosophila autophagy is inhibited by target of rapamycin (TOR) signaling,6 but this inhibition can be bypassed by Acn overexpression. Even more strikingly, high-level Acn expression is lethal, but viability is restored when autophagy is blocked.5 These observations emphasize the importance of the control of Acn activity for adjusting the levels of autophagy. In our recent study2 we explored how multiple intracellular signals can modulate Acn levels, which might serve as a focal point for adjusting the basal level of autophagy.Our recent work5 To our surprise, a GFP reporter transgene detected little regulation at the transcriptional level; instead, Acn is primarily regulated at the level of protein stability.2 Two conserved elements that contribute to its regulation are a caspase cleavage site7 and a pair of Akt1 consensus target sites.8 To test their importance in vivo we generated transgenic flies in which endogenous Acn was replaced by mutant proteins designed to prevent cleavage by caspases (AcnD527A) or mimic phosphorylation at the Akt1 target sites . Both of these mutations stabilized Acn and yielded interesting physiological consequences.The dynamic regulation of Acn is exemplified in the developing eye where its expression in photoreceptor cells changes rapidly depending on cell type and developmental stage.In these mutant animals, all stages of autophagy were enhanced, whether evaluated by live imaging of GFP-Atg8a fluorescence in early autophagosomes, antibody staining for endogenous Autophagy-related 8a (Atg8a) protein, or lysotracker accumulation in autolysosomes. Electron microscopy revealed a remarkable increase in size and abundance of autolysosomes compared to control animals. The relative increase in autophagy was most pronounced in fed animals, indicating that elevated Acn levels enhanced basal, starvation-independent levels of autophagy. The resulting improved cellular quality control was evident from an enhanced ability to clear aggregation-prone poly-Q Huntingtin protein from photoreceptors and, maybe most strikingly, a significantly prolonged longevity (Drosophila caspases tested in this screen only knockdown of death caspase-1 (Dcp-1), a homolog of mammalian caspase-3, enhanced Acn function. Elevated levels of Acn in dcp-1 mutant cells and the resulting upregulation of autophagy substantiated the physiological relevance of the genetic interactions in the eye.To identify the protease responsible for Acn cleavage we used a targeted RNAi screen. Acn overexpression in the eye causes mild eye roughness that served as readout. Among the 9 7 first detected cleavage of mammalian Acn proteins by caspase-3 activity that was upregulated in the context of apoptotic cells. Our observations extend their original finding to cells in different developing tissues, including precursors of photoreceptors and fat body cells. These healthy, non-apoptotic cells use their low background levels of caspases to inactivate Acn as they balance the beneficial effects of quality control autophagy with the deleterious effects resulting from its overactivation. Acn may not be the only target in such contexts, as cleavage of Beclin-1 and autophagy-related 4 (Atg4) by caspases can also reduce autophagy and suppress its cytoprotective function.1Sahara and colleaguesin vitro phosphorylation of mammalian Acn by Akt1,8 we found that Akt1 knockdown in Drosophila reduced Acn phosphorylation in vivo and prevented its protective function against Acn cleavage.Regulated cleavage of Acn by Dcp-1 may also be the key to understanding the genetic interactions between Akt1 and Acn. Their co-expression worsened eye roughness induced by wild-type Acn, but not by Acn mutants lacking the Akt1 target sites. Consistent with the effect of 1 One possible explanation for this contradiction could be the existence of distinct pools of Akt1.9 A pool of cytoplasmic Akt1 may inhibit autophagy by phosphorylating the tuberous sclerosis complex 2 (TSC2) protein and Beclin.1,6 In contrast, we speculate that a nuclear pool of Akt1 may phosphorylate Acn, and possibly other nuclear targets yet to be identified, leading to increased basal autophagy.Surprisingly, Akt1-mediated stabilization of Acn and the resulting upregulation of basal autophagy appear to be opposite to the well-documented role of Akt1 as a negative regulator of autophagy in the context of the canonical PtdIns3K–Akt–TOR pathway.5 Deciphering the mechanisms by which Acn regulates basal autophagy will be an important goal of our future research.How Acn induces basal autophagy remains unclear. As Acn is primarily nuclear and part of the apoptosis-and splicing-associated protein (ASAP) complex, one possible mechanism may relate to the regulated splicing of genes involved in autophagy. Alternatively, we detected cytosolic Acn in a subset of cells in developing eyes, raising the possibility that Acn functions outside the nucleus.


Chronic diseases such as diabetes require high levels of medication adherence and patient self-management for optimal health outcomes. A novel sensing platform, Digital Health Feedback System , can for the first time detect medication ingestion events and physiological measures simultaneously, using an edible sensor, personal monitor patch, and paired mobile device. The Digital Health Feedback System (DHFS) generates a large amount of data. Visual analytics of this rich dataset may provide insights into longitudinal patterns of medication adherence in the natural setting and potential relationships between medication adherence and physiological measures that were previously unknown.Our aim was to use modern methods of visual analytics to represent continuous and discrete data from the DHFS, plotting multiple different data types simultaneously to evaluate the potential of the DHFS to capture longitudinal patterns of medication-taking behavior and self-management in individual patients with type II diabetes.Visualizations were generated using time domain methods of oral metformin medication adherence and physiological data obtained by the DHFS use in 5 patients with type II diabetes over 37-42 days. The DHFS captured at-home metformin adherence, heart rate, activity, and sleep/rest. A mobile glucose monitor captured glucose testing and level (mg/dl). Algorithms were developed to analyze data over varying time periods: across the entire study, daily, and weekly. Following visualization analysis, correlations between sleep/rest and medication ingestion were calculated across all subjects.r=.47, P<.02; Subject 4: r=.35, P<.05). With Subject 2, sleep/rest disruptions during the night were highly correlated  with missing doses the following day.A total of 197 subject days, encompassing 141,840 data events were analyzed. Individual continuous patch use varied between 87-98%. On average, the cohort took 78% (SD 12) of prescribed medication and took 77% (SD 26) within the prescribed ±2-hour time window. Average activity levels per subjects ranged from 4000-12,000 steps per day. The combination of activity level and heart rate indicated different levels of cardiovascular fitness between subjects. Visualizations over the entire study captured the longitudinal pattern of missed doses (the majority of which took place in the evening), the timing of ingestions in individual subjects, and the range of medication ingestion timing, which varied from 1.5-2.4 hours (Subject 3) to 11 hours (Subject 2). Individual morning self-management patterns over the study period were obtained by combining the times of waking, metformin ingestion, and glucose measurement. Visualizations combining multiple data streams over a 24-hour period captured patterns of broad daily events: when subjects rose in the morning, tested their blood glucose, took their medications, went to bed, hours of sleep/rest, and level of activity during the day. Visualizations identified highly consistent daily patterns in Subject 3, the most adherent participant. Erratic daily patterns including sleep/rest were demonstrated in Subject 2, the least adherent subject. Correlation between sleep /rest and medication ingestion in each individual subject was evaluated. Subjects 2 and 4 showed correlation between amount of sleep/rest over a 24-hour period and medication-taking the following day (Subject 2: Visualizations integrating medication ingestion and physiological data from the DHFS over varying time intervals captured detailed individual longitudinal patterns of medication adherence and self-management in the natural setting. Visualizing multiple data streams simultaneously, providing a data-rich representation, revealed information that would not have been shown by plotting data streams individually. Such analyses provided data far beyond traditional adherence summary statistics and may form the foundation of future personalized predictive interventions to drive longitudinal adherence and support optimal self-management in chronic diseases such as diabetes. Medication adherence is defined as “the extent to which patients take medications as prescribed by their health care providers” . An estiAny attempt to address this problem is complicated by the absence of reliable measurement of medication adherence, a difficulty that has plagued medicine since the days of Hippocrates . The curA novel technology, Digital Health Feedback System (DHFS), is now available that allows for the date- and time-stamping of actual ingestions of oral medications rather than surrogate measures of ingestion. The system has been shown to be safe, reliable, and highly accurate, with a positive detection accuracy of sensor-detected ingestions of approximately 99.1%  . In the 3 edible sensor (1 x 1 x.45 mm microchip), coated with very thin layers of commonly ingested excipients , and a small detector patch worn on the torso. When ingested with medication, the sensor readily separates from the carrier, is energized, and communicates with the adhesive-backed detector patch worn on the torso. The detector patch interprets the information as unique to the ingested sensor and records it along with physiological metrics including heart rate, step activity, and sleep/rest. All of the recorded data are sent wirelessly to a paired device, such as a mobile phone or a personal computer, and are subsequently uploaded to a secured, centralized data storage location  the entire study period, (2) 24-hour periods, and (3) weekly time periods. Visualizations generated attempted to explore relationships that would be of value in supporting patient medication adherence and self-management in this chronic disease state.Data analyzed were from a user experience study, which was a prospective, single-arm, observational cohort study  that aimed to characterize the at-home adherence patterns of 5 patients with type II diabetes to oral metformin . The stuWe analyzed Microsoft Excel and Matlab files exported from the DHFS database and wireless glucose monitor, containing individual subject’s DHFS outputs of pulse measured every 10 minutes, activity recorded every 5 minutes, sleep/rest, and glucose.Standard summary statistics in percentages were calculated across all subjects for (1) taking adherence, defined as the number of ingestible sensor tablet detections by the personal monitor divided by the number of metformin doses prescribed, and (2) scheduling or timing adherence, defined as the number of ingestible sensor tablets detected within a±2-hour time window around the pre-determined dosing time divided by the number of sensors detected. Descriptive statistics of daily glucose measurement, with mean, maximum, and minimum range, along with 95% confidence intervals across the study period were calculated.Patch function was checked using number of individual activity events reported over a 24-hour time period, with sampling every 5 minutes, that is, 288 measurements daily. The amount of continuous patch wearing per subject was recorded. In correlation calculations, days without full patch function were removed. The total number of events per subject per day recorded by the monitoring patch including heart rate, activity, and posture were approximately 720. Thus, over the 197 days of the study, data events recorded ranged from approximately 26,640-30,240 per subject, with a total number of data events recorded of greater than 141,840 for the entire study.Algorithms were developed using Matlab and applied to analyze data for medication-taking behavior, sleep/rest, activity, heart rate, and then integrated with glucose measurements over (1) the entire study period, (2) daily, and (3) weekly. The sleep/rest state signal is derived from an algorithm based on activity, position, and pulse. The temporal structure of this sleep/rest state signal was used to derive the waking time. Waking time derivation was based on the following assumptions: (1) there is a single daily waking event, (2) short interruptions in long rest periods are transient state changes that should be ignored, and (3) similarly short rests in long waking periods do not suggest the main daily transitions. Visualizations were plotted using Matlab.r correlation between sleep/rest metrics and medication-taking behavior was calculated using a single daily measure, derived from physiological features tracked by the personal monitor patch, and a daily adherence measure of either number of doses taken or timing of dose ingestion. A delay in medication ingestion of greater than 12 hours was considered to be a missed dose. The daily sleep/rest measure used were total hours of rest, and number of sleep disturbances between 10 p.m. and 8 a.m.Pearson’s Subjects were 5 patients with type II diabetes , age 43-61, prescribed twice-daily metformin. Subjects 1, 2, and 5 used insulin in addition to metformin during the study. Days of participation per subject ranged from 37-42, with a total number of subject days of 197. On average, the cohort took 78% (SD 12) of prescribed medication and took 77% (SD 26) within the prescribed ±2-hour time window. Patch use across 197 subject days of participation in the study showed subjects wore the patch continuously between 87-98% of the time. One isolated event of greater than 288 events was observed due to patch dysfunction. Data from days of no recording were removed as described above.The DHFS system allows precise time-stamping of ingestions. The initial visualizations sort to provide a means to quickly evaluate how closely patients executed the twice daily dosing regimen prescribed and what the fraction of missed doses looked like in terms of the time of their occurrence. In The DHFS is capable of identifying sleep/rest behavior in addition to the precise timing of medication ingestion. The ability to execute consistent timing of drug ingestion twice daily may be connected to individual daily waking and bedtimes. Using DHFS data, we derived each subject’s waking time and bedtime . We then visualized wake time with medication ingestion time for each subject, but also incorporated time of glucose measurement over the course of the study to explore if it was possible to visualize morning self-management patterns in individual subjects. Subjects in this study were instructed to take at least 1 daily glucose measurement, preferably first thing in the morning to provide a daily fasting glucose measure.r=.6113, P>.001). Subject 4 took metformin within minutes of waking but missed multiple metformin doses. The proximity of waking time and medication ingestion for Subject 4 may partly account for the consistency in timing adherence of this subject, thus when the subject remembered to take the medicine, he did so on waking usually between 6-8 a.m. Subject 4 did not take blood sugar measures every morning and those taken were frequently made hours after waking and thus unlikely to represent fasting glucose values. Subjects 1 and 5 took their metformin dose within 4 hours of waking and their graphs are shown in Graphs 1 and 2 in The DHFS also monitors heart rate and activity. An important aspect of patient self-management in chronic diseases like diabetes is maintaining healthy levels of physical activity. Subjects 3 and 4 had the most frequent and vigorous exercise levels, averaging between 8000 and 12,000 steps on most days. Subjects 1 and 2 had the lowest step counts averaging 4000-5000 steps per day. Subject 5 showed the widest range of daily step count with an average of 6000 steps per day. Step count distribution and daily average, maximum, and minimum heart rates for each patient are shown in Graphs 3 and 4 in We then combined data on heart rate and step activity to gain potential insight into the fitness levels of the subjects. We looked at the sustained maximum heart rate in terms of the elevation of the heart rate from resting  and its relationship to daily step count in each subject . In FiguWe then explored whether data analysis using visualization over a 24-hour time frame would offer different information than visualization over the entire study period. We generated graphs for each day of study participation, incorporating medication ingestion, sleep/rest, activity, and glucose measurement  for each subject. We found that with this combination of ingestion and physiological data, it was possible to generate visualizations that reconstructed the broad pattern of the patient’s day in relation to their medication-taking. Thus we could see when patients rose, tested their blood glucose, took their medication, became physically active, and later went to bed. Samples of these daily graphs for each subject are provided; Subjects 2, 3, and 4 are shown in This interval of analysis enabled highly individualized insight into each participant’s daily behavior patterns over the period of study in relationship to medication ingestion. The data potentially provide information to support individually tailored interventions to improve adherence outcomes.While daily graphs demonstrated the ability of the DHFS to provide detailed insights into individual daily patterns of behavior, we wanted to capture both the detail of the daily analysis with longitudinal patterns of behavior, so we generated visualizations using the data input over weekly periods. The daily and weekly visualizations suggested there may be some association with variation in sleep pattern and medication ingestion in some subjects, particularly Subject 2. To evaluate whether there was a relationship between sleep/rest and medication-taking behavior in the individual patients, we looked at the correlation between (1) total hours of sleep/rest the previous night and pill taking the next day, and (2) sleep/rest disruptions (breaks in sleep between 10 p.m. and 8 a.m.) and medication-taking behavior the following day for each subject over the entire study period. The DHFS is the only system to date that can detect actual medication ingestion events. It also captures dense physiological data simultaneously. This study aimed to use modern methods of visual analytics to represent continuous and discrete data from this novel sensor system, plotting multiple different data types simultaneously to evaluate the potential of the DHFS to capture longitudinal patterns of medication adherence. The DHFS was able to provide remote monitoring of ingestion events and physiological metrics in the natural setting over the entire period of the study. High levels of continuous patch wearing with an early prototype were demonstrated in this study (current monitor patch versions are four generations from the version used).Our study demonstrated a number of findings. Visualization of the data with simultaneous variable plotting, integrating physiologic and medication ingestion data, provided useful detailed information on longitudinal medication-taking and timing adherence patterns beyond traditional summary statistics. Varying the time interval over which the variables were visualized provides complementary data, with visualizations over a 24-hour period demonstrating the ability to reconstruct basic daily behavior patterns in relation to medication ingestion. While there was some overlap of behavior in this small sample, essentially each subject emerged as having their own distinct longitudinal pattern. Even if that pattern was one of variability, such as Subject 2, who showed widely variable patterns of medication ingestion and timing with highly variable morning and daily routines, including sleep/rest patterns. In contrast, our analyses also enabled us to look at the behavior patterns of Subject 3, a patient with type II diabetes, who was highly adherent to the prescribed regimen and whose glucose measures remained under 150 mg/dl over the period of the study. The regularity of this subject’s daily routine, including sleep/rest cycles and level of exercise, was striking in comparison to some of the other subjects. As the number of these types of analyses using the DHFS over wide populations grows, it will be also be important to increase our understanding of how highly adherent and optimally self-managed patients behave. This will enable us to identify “success habits” and share those with other patients. The focus of adherence consultations can then include not just “how you are failing,” but also generalized examples of “how to succeed.”One of the most significant strengths of the visualizations presented is that they encompass idiographic data analysis techniques that can focus on individual variability over time. These methods are uniquely suited to the analysis of individually tailored interventions evolving over time to promote medication adherence. The initial graphs on timing of ingestions and missed doses may allow the health care provider and patient to discuss patterns of medication-taking across a monitored time period and to focus on the time of day patients may need the most support. Addition of the 24-hour graphs provide detailed information on patterns of activity and sleep/rest on days when doses were missed and may allow a more in-depth interaction with the patient on the types of support needed. To illustrate how this information could be used in practice, in discussion with Subject 2, the health care provider could extend the interview on factors affecting this patient’s medication adherence to include sleep/rest patterns and other disorders associated with significant sleep disturbance, such as depression, hyperthyroidism, chronic pain, gastroesophageal reflux disease, to try to understand whether the patients’ daily patterns are the result of untreated concurrent conditions or a reaction to stressors, or both. The visualizations provide the opportunity to extend the health care patient interview allowing broader personalized intervention to support treatment success beyond the use of medication reminders alone, which would be unlikely to successfully support medication adherence in Subject 2. However, Subject 4, who most frequently took his medication after waking, may well respond to reminders alone, particularly missed dose reminders, timed around his waking. Similarly dose reminders may work well in the evening time for Subjects 1, 4, and 5, particularly missed medication reminders around dinner time, to reduce the number of missed medications in the evening. The fully developed DHFS is capable of delivering near real-time feedback, which can be incorporated into individually tailored patient missed-dose reminder interventions. Thus the visualizations tell individual stories for each subject that can inform intervention and future management to support medication adherence and patient self-management.A major stated aim of this paper is to provide and explore modes of data visualization that are accessible to both health care worker and patient consumer. This requires visualizations to preserve the accuracy of the data, while maintaining accessibility to the maximum number of individuals without prior training. Despite the density of the multiple different data types summarized by some of the visualizations, it was possible to develop graphs that could be easily understood and potentially suitable for use by patients and health care workers with minimal training. Health care workers in particular have very little time, and continuous data streaming of individual variables can easily overwhelm providers with data that may be largely unusable. As stated in the introduction, visual analytics is an emerging discipline that has shown significant promise in addressing many of these information overload challenges . In dataBased on visualizations showing variability in sleep/rest and medication-taking behavior in some subjects, we evaluated potential correlations between medication-taking behavior sleep/rest patterns. This analysis suggested medication-taking behavior in 2 individual subjects was significantly influenced by sleep/ rest patterns over the period monitored. Other researchers have found sleep disturbance, especially when reported with depression, is associated with poor medication adherence ,23. LargAs these visualizations could prove useful and relevant in clinical practice, investigation of their ease of use and utility to health care workers and patients is currently in progress. While our analyses across varying time intervals provided complementary data, using a weekly interval of analysis we were able to provide much of the detail of daily structure in combination with longitudinal patterns over a 1-week period. Thus, we estimate that the weekly visualizations will prove the most useful interval of evaluation in future studies incorporating tailored individual interventions to support medication adherence and optimal self-management. The addition of subject input such as personal event logs would further increase the impact of these visual analyses of DHFS data and enrich feedback that could be given to individuals to guide self-management.In future, as the number of these analyses and use of the DHFS system grows, reference databases on patterns of longitudinal medication adherence and self-management patterns will accumulate and measurable estimates of comparability of longitudinal patterns to large sample populations will be available. Ultimately, we anticipate that machine-learning techniques will make predictive interventions possible to support longitudinal medication adherence and patient self-management.The major limitation of this work is the study size. Work is currently underway to further refine analytic algorithms within larger studies. Co-ingestion of an edible sensor whenever taking metformin, as occurred in this user experience study, is now being replaced with combined formulations of edible sensor and medication . The focVisualizations integrating medication ingestion and physiological data from the DHFS over varying time intervals captured detailed individual longitudinal patterns of medication adherence and self-management in the natural setting. Visualizing multiple data streams simultaneously, providing a data-rich representation, revealed information that would not have been appreciated by plotting data streams individually. Such analyses provided data far beyond traditional adherence summary statistics and may form the foundation of future personalized predictive interventions to drive longitudinal adherence and support optimal self-management in chronic diseases such as diabetes.


Carcinoma ex pleomorphic adenoma (CXPA) is an unusual epithelial malignancy that develops from a primary or recurrent pleomorphic adenoma (PA), the most common tumor of salivary glands, and constitutes about 11.5% of all carcinomas that affect these glands. Intraoral minor salivary glands and seromucous glands of the oropharynx are uncommon locations of CXPA. On histopathological examination, the tumor comprises a wide morphological spectrum with a variable proportion between the benign and malignant components with the latter often predominating and overlapping the PA, which may cause misdiagnosis. Here, we report a case of palatal minor salivary gland CXPA composed of invasive micropapillary salivary duct carcinoma and adenoid cystic carcinoma components with multiple nodal metastases in a 74-year-old woman. Neoplastic cells showed heterogeneous immunohistochemical profile with both luminal and myoepithelial differentiation. The invasive micropapillary salivary duct carcinoma component demonstrated overexpression of the oncoprotein human epidermal growth factor receptor-2. This feature should be considered and evaluated as a possible target for adjuvant therapy in case of metastatic disease. A malignant salivary gland tumor was suspected and the patient underwent resection of the mass with right radical neck dissection. Tumor-free margins were confirmed by microscopic examination of intraoperative frozen sections.The resected specimen and 79 cervical lymph nodes were fixed in 4% buffered formalin and paraffin-embedded. Microscopic examination revealed an invasive neoplastic process with 3 distinct and well-demarcated recognized elements. The first element, the scarcest area, was typical of PA, represented by occasional bilayered duct-like structures in association with a myxochondroid stroma, which showed areas of discrete hyalinization Figure A. The seImmunohistochemical stains showed that in residual PA area, cytokeratin (CK)7 protein was positive in pseudoluminal-forming cells Figure A; the IM1 Although most CXPA occur in major salivary glands, cases involving the oral and oropharyngeal minor glands account for about 17.5% of the Armed Forces Institute of Pathology series. Of all these cases, 63% were in the palate and 10.5% were in the upper lip. Other sites included the tongue, buccal mucosa, tonsil, and oropharynx. Signs and symptoms most commonly reported were a painless mass of long duration.10CXPA is an infrequent malignant tumor of the salivary glands historically named as malignant mixed tumor, carcinoma ex mixed tumor, carcinoma ex adenoma, and carcinoma ex benign pleomorphic adenoma.12 The double differentiation of the carcinomatous component of CXPA described in this case is a very exceptional event and has been previously reported by 2 groups: Freeman et al13 described a fatal nasal CXPA with adenoid cystic and squamous carcinomatous differentiation and Nakamori et al14 an intracapsular salivary duct and squamous cell CXPA of the buccal mucosa , and frankly invasive (>1.5 mm of invasion from the tumor capsule into the adjacent tissue) with prognostic implications.19 The negative stain found should be partially explained by the fact that the ACC arising in a previous PA probably displays a different immunoprofile and genetic abnormalities than ACC without PA association, perhaps owing to different mechanisms of carcinomatous initiation and progression, despite the similar histopathological aspects. However, the p53 oncoprotein showed diffuse positive staining in carcinomatous areas, but not in residual PA. The p53 oncoprotein has been implicated in the pathogenesis of CXPA, and our findings corroborate this hypothesis. Furthermore, p53 overexpression is considered a helpful tool in identifying areas of carcinomatous transformation in PA.20As would be expected, modified myoepithelial cells of the ACC component showed diffuse immunoreactivity to the myoepithelial markers p63 and α-SMA, whereas CK7 was positive in those cells with a luminal distribution and c-kit was negative. The c-kit protein has been considered as a helpful marker in distinction between ACC and other salivary gland tumors, which share morphological similarities, such as polymorphous low-grade adenocarcinoma.21 Nevertheless, it is considered to play an important role in targeting adjuvant therapy,22 as well as has been employed as an immunohistochemical marker to identify areas of malignant transformation in PA, particularly if the carcinoma is of the salivary duct type.23 Furthermore, HER-2 overexpression by immunohistochemistry or amplification by fluorescent in situ hybridization test in salivary gland CXPA and other salivary gland malignancies may elect patients for Trastuzumab therapy, especially in case of metastatic disease.23 Recently, Di Palma et al24 reported a case of plurimetastatic CXPA successfully treated by Trastuzumab and radiotherapy. In the presented case, HER-2 overexpression was identified only in the IMSDC component by immunohistochemistry and curiously the 39 nodal metastatic foci were composed exclusively by this tumor. If the patient experience recurrence, visceral metastasis, or both by the IMSDC, the status of HER-2 observed in this case could call attention to the possibility of adjuvant therapy with Trastuzumab to cure.The HER-2 oncoprotein is extensively studied in mammary ductal invasive carcinoma and its overexpression is often associated with a poor prognosis and high frequency of nodal metastasis.In summary, we report an unusual case of palatal minor salivary gland CXPA composed of IMSDC and ACC with extensive nodal involvement based on histopathological and immunohistochemical findings. Improved understanding of the pathobiology of this tumor and other salivary gland tumors may lead to rationally designed targeted therapies that could improve the outcome of patients with CXPA.


Acute respiratory distress syndrome represents a complex syndrome with considerable morbidity and mortality, for which there exist no targeted treatment strategies. However, recent advances in clinical care have improved outcomes, and we will review a number of these approaches here, as well as explore the mechanisms underlying the benefit of intervention that might point us in the direction toward future treatment and preventive strategies for this devastating syndrome. It is unlikely, as is the case for many serious ailments, that there is a “one size fits all” treatment for ARDS, and thus improved understanding of the disease process and appropriately characterizing severity of illness will be critical for making advances in treatment strategy. Furthermore, the National Institutes of Health (NIH) has recognized the importance of addressing strategies to prevent ARDS development, thus forming the new version of the ARDS Network under the heading of “PETAL”: Prevention and Early Treatment of Acute Lung Injury. Therefore, in this brief review, we set out to discuss some of the recent advances in understanding and treating ARDS, as well as to address the possible biological mechanisms underlying these mechanisms, to attempt to shed light on potential areas for future scientific investigation. We focus our discussion on significant articles that have modified mortality from ARDS, and we summarize a proposed overall approach to ARDS.The acute respiratory distress syndrome (ARDS), first described in 1967, remains difficult to treat and has significant morbidity and mortality. Risk factors for ARDS include factors resulting from direct injury to the lung  or indirect injury . These conditions result in inflammatory lung injury and hypoxemia that arise from disruption of the alveolar-capillary membrane and influx of protein-rich edema fluid, producing physiologic lung dysfunction. Remarkably, despite intense investigation and numerous large-scale clinical trials, no targeted medical therapies have yet been developed nor proven effective, and there exist no universally agreed-upon biomarkers that might predict severity of illness, or clinical outcomes, or both. These challenges in characterization and treatment likely result from the heterogeneity of ARDS as well as the difficulty of treating a “syndrome” rather than a molecularly confirmed disease; however, a number of management strategies have proven beneficial and have resulted in reductions in mortalityaO2/FiO2, or P/F) ratio of >200 with (b) new bilateral infiltrates (c) not attributable to heart failure as defined by pulmonary capillary wedge pressure (PCWP) (as measured by a Swan-Ganz catheter) of not more than 18 mmHg 2. These criteria were adopted with the goal of more uniformly defining the syndrome and identifying appropriate patients for ARDS therapies and enrollment in clinical trials. Although these criteria facilitated these goals, it was felt that certain improvements in the definition might improve the clinical phenotyping and risk stratification of ARDS subjects, including a more explicit definition of “acute” onset of hypoxemia, further definition of the dependence of the P/F ratio on ventilator settings  setting), improved criteria for chest radiograph interpretation of “bilateral infiltrates”, and more explicit guidance with defining the contribution of cardiogenic pulmonary edema to the clinical picture.From 1994 to 2012, ARDS was defined on the basis of the American-European Consensus Conference (AECC) criteria: (a) acute onset of hypoxemia defined by partial pressure of arterial oxygen/fraction of inspired oxygen  defining three categories of ARDS severity on the basis of P/F ratio: P/F ratio ≤300 and >200 , P/F ratio of between 100 and 200 (“moderate” ARDS), and P/F ratio of <100 (“severe” ARDS); (b) defining “acute” onset of bilateral infiltrates as within 7 days of exposure to an ARDS risk factor or worsening respiratory symptoms; (c) more definitive chest radiograph criteria were provided , and use of chest computed tomography was allowed for fulfilling the radiographic definition as well; (d) use of the PCWP for defining cardiogenic pulmonary edema was removed (given the declining use of Swan-Ganz catheters), and it was acknowledged that cardiogenic and non-cardiogenic pulmonary edema can coexist. However, determination of whether the bilateral infiltrates are attributable to a cardiogenic cause cannot be based solely upon clinical decision making. If a risk factor for ARDS is not identified, then some objective criteria of cardiac function, such as echocardiography, are required to exclude a sole cardiogenic cause for pulmonary edema; and (e) minimum use of PEEP of at least 5 cm H2O on the mechanical ventilator (or delivered by non-invasive ventilation only in the mild ARDS category) in assessing the severity of oxygenation impairment using the P/F ratio.In 2012, the European Society of Intensive Care Medicine convened an expert panel to improve the reliability and validity of the ARDS definition, termed the Berlin Criteria4. Ideally, the use of additional biologic predictors might have the capacity to improve prediction of outcome and risk stratification. Although the hunt for predictive biomarkers for ARDS development and outcome is still under way, existing studies suggest the promise of using plasma biomarkers—e.g., interleukin-8 (IL-8), tumor necrosis factor alpha (TNFα), surfactant protein-D (SPD), and mitochondrial DNA—to improve prediction of outcomes beyond clinical classification algorithms 6. Recent studies suggest that ARDS might be better predicted by specific biomarkers, such as plasma levels of the soluble form of the receptor for advanced glycation end products (sRAGE) as a marker of lung epithelial injury8 and plasma levels of tumor necrosis factor receptor-1 (TNFR1), IL-6, IL-8, and plasminogen activator inhibitor-1 (PAI1) as markers of a hyperinflammatory ARDS subphenotype9. Although the Berlin Criteria have enhanced our clinical phenotyping systems, ongoing work in clinical/biological phenotyping of critically ill subjects will ideally facilitate additional prevention trials, allowing investigators to target specific risk groups with modifiable risk factors for ARDS development.The Berlin Criteria were derived and validated, and additional variables that were considered in the definition  did not improve severity prediction and therefore were not incorporated into the final criteria . Of note, defining the “severe ARDS” category called attention to the most afflicted group (with a P/F ratio of <100), which has the highest mortality irrespective of ventilator strategy and therefore might benefit from applications of more advanced ARDS rescue strategies (see discussions below). Specifically, mortality rates in the mild, moderate, and severe groups were 27%, 32%, and 45%, respectively, and the Berlin Criteria improved mortality prediction beyond that of AECC; however, as acknowledged by the authors, there are clearly limitations to clinical criteria in defining a syndrome10. This study prompted the widespread use of low tidal volume ventilation in supporting patients with ARDS and has led to ongoing studies to investigate the mechanisms underlying this profound benefit (see below). In addition, this important trial has prompted additional recent trials investigating whether low tidal volume ventilation might also benefit other populations of patients, such as those undergoing mechanical ventilation for an operative procedure .This question remains a point of clinical debate in setting mechanical ventilation parameters for critically ill patients without the presence of ARDS. Although it is known that normal laboratory mice exposed to high tidal volume ventilation develop lung injury11, it is not clear whether this is the case for humans without pre-existing lung injury. Interestingly, a recent article reported that the use of a “prophylactic” protective ventilation strategy improved clinical outcomes  in intermediate- and high-risk patients undergoing abdominal surgery12.In a seminal study performed by the ARDS Network in 2000, mechanical ventilatory support of ARDS patients with 12 ml/kg  tidal volume was compared with low tidal volume ventilation at 6 ml/kg, and there was a significant reduction in mortality with low tidal volume ventilation (38% to 31%)14, supporting the complexity of ARDS pathophysiology and management. Mechanical ventilation without maintenance of open lung units has the potential to exacerbate lung injury as a result of opening and closing of lung units, termed “atelectrauma”16, which has led to widespread studies of optimal application of PEEP to maintain open lung units, and a recent meta-analysis suggested that higher levels of applied PEEP might be beneficial in patients with moderate ARDS17. Beyond physiologic benefits of low tidal volume ventilation, numerous studies have called attention to the concept of “biotrauma” as a result of injurious mechanical ventilation, in which stretching of lung units might activate cellular signaling cascades resulting in lung inflammation, increased release of pro-inflammatory mediators , and effects on non-pulmonary tissues resulting in multi-system organ failure. Potential physiologic benefits of low tidal volume ventilation have recently been reviewed in detail19.The findings of improved mortality with low tidal volume ventilation prompted widespread investigation into the mechanisms underlying this protection, resulting in a vast expansion in our understanding of factors driving mechanotransduction-related lung injury. Physiologic lung improvements as a result of low tidal volume ventilation have been attributed to a number of factors, including most grossly, reduced incidence of barotrauma (application of high pressures to the lung resulting in injury), volutrauma , and perhaps improved hemodynamics (blood pressure and organ perfusion) as a result of less overdistention of the lung and improved venous return to the heart; however, ventilation at low tidal volumes can result in collapse of the lung parenchyma, and trials of high-frequency oscillatory ventilation that allowed for very small tidal volumes did not prove beneficialet al. examined 340 intubated patients in a multi-center trial with severe ARDS (P/F ratio of <150), who were randomly assigned to receive NMB (cisatracurium besylate) versus placebo for 48 hours. All patients received low tidal volume ventilation and were on at least 5 cm H2O PEEP. The adjusted 90-day in-hospital mortality rate was lower with NMB versus placebo, and no increased neuromuscular weakness was observed in the NMB group20. Additionally, an increased number of ventilator-free days was observed in the NMB group. Of note, both groups received deep sedation. This study has raised important questions about the utility of NMB in ARDS, and there is sufficient uncertainty about its widespread use that the NIH PETAL Network is addressing this issue in one of its first network trials. Thus, further data will be available in the future to help guide clinical practice. Residual questions that remain include whether patients solely with severe ARDS might benefit from NMB, what the optimal NMB infusion duration might be, whether similar benefits might be observed with NMB agents other than cisatracurium besylate, and what the independent effects of heavy sedation apart from NMB might be22.Neuromuscular blockers (NMBs) have been used for a long period of time in the intensive care unit, largely to facilitate mechanical ventilation of ARDS subjects when sedation alone was insufficient, usually in the setting of severe gas exchange impairment, or to facilitate other advanced therapies for ARDS, such as prone positioning (see below), or to do both; however, protocolized care for use of NMBs in ARDS has not been uniformly applied, and concerns regarding adverse effects of NMBs  without clear data showing benefit of NMBs limited widespread use until recently. Papazian20; (b) NMBs might result in less biotrauma as evidenced by less end-organ failure associated with their use20, as well as reduction in lung  and serum (IL-1β and IL-8) cytokines in patients on NMB23; (c) NMBs limit expiratory muscle function and therefore reduced respiratory system collapse and derecruitment that might result in improved respiratory system compliance and improved ventilation-perfusion matching22. Interestingly, a recent preclinical study suggests that the mechanism of protection of NMBs might relate to direct anti-inflammatory effects of blocking the nicotinic acetylcholine receptor-α1, independent of effects on improving ventilator dyssynchrony24.Although much of the mechanism remains to be learned regarding protective effects underlying NMB , there exist data to support a number of possible pathways of benefit: (a) NMBs counteract patients bucking the ventilator, thereby limiting lung injury arising from ventilator dyssynchrony—of note, an increased rate of pneumothoraces (consistent with barotrauma) was observed in the placebo group25. In 2013, Guérinet al. examined prone positioning (at least 16 hours per day) versus standard positioning in 466 subjects with severe ARDS , FiO2 of at least 0.6, low tidal volume ventilation, and PEEP of at least 5 cm H2O and found a striking 28-day mortality benefit of prone positioning (32.8% supine versus 16% prone), and a mortality benefit persisted until day 9026. Of note, there was no significant difference in complications between the prone and supine groups (except for an increased rate of cardiac arrests in the supine group); however, the authors acknowledge that this study was carried out in centers with substantial experience and expertise in prone positioning. This lack of expertise in prone positioning, the potential complications that might arise from proning, and the potential difficulty in selecting optimal patients who might benefit from proning  have led to variability in uniform adoption of prone positioning in ARDS clinical centers.Although it was realized in the 1970s that prone positioning improved oxygenation in ARDS, numerous studies over ensuing decades demonstrated improvement in oxygenation but failed to show improved mortality from prone positioning. This lack of mortality benefit, coupled with concerns regarding possible adverse events from proning patients , led to limited/sporadic use across clinical ARDS centers27. Of note, differential use of neuromuscular blockade (increased NMB was used in the prone position group) has been cited as an important factor to consider in interpreting this trial (seeAdvances in adjunctive therapy for severe acute respiratory distress syndrome: neuromuscular blockade section above). Some earlier studies suggested that the most afflicted patients (i.e. those with the lowest P/F ratios) might benefit from proning, prompting the selection of the patient population in the most recent study26. In general, potential benefits of proning might include (a) improved lung ventilation perfusion matching, (b) improved right ventricular dysfunction29, and (c) recruitment of lower-lobe atelectatic lung units (perhaps related to reduced compression of lung units in the prone position) and decreased intrapulmonary shunting, as well as potentially improved maintenance of open lung units, thus limiting ventilator-induced lung injury (through mitigating repeated opening and closing of lung units that generates lung injury). It is believed that some patients also experience improved secretion clearance gravitationally in the prone position25.Although a number of studies over many years examined potential benefits of proning, a mortality benefit to the degree described above was only recently observed. Some of the earlier studies were small studies and in addition studied patients in later ARDS phases when prone positioning might be less likely to reverse the disease process. It is possible that more routine use of low tidal volume ventilation in this most recent study is a factor, as well as the more prolonged period of proning that was employed in this study compared with other trials31, although more recent data have called attention to the possibility that a more restrictive fluid management strategy is associated with cognitive dysfunction32. Fluid management in critical illness is currently under review33, and the information that is gleaned may help guide clinical practice in the future.Although ARDS represents a complex syndrome with considerable morbidity and mortality, recent advances in clinical care have improved outcomes, as described in this review. Support of ARDS patients with low tidal volume ventilation has become the standard of care, and this approach has revealed important underlying mechanisms that have led to new areas of investigation in lung injury. Use of the Berlin Criteria has aided in the identification of the most afflicted ARDS patients who might benefit from rescue therapies, and targeting of neuromuscular blockade and prone positioning in severe ARDS has recently proven beneficial in terms of improved ARDS mortality. Ongoing studies will be important for providing additional information for helping us target these modalities to the patients most likely to benefit from them as well as to gain further understanding of the mechanisms underlying benefit of these modalities. An additional area of clinical care and investigation not reviewed here in detail is the use of conservative fluid strategy to decrease ventilator time in patients with ARDS34, including those in an ongoing NIH-funded trial in mesenchymal stromal cells36, are under investigation; however, it is widely appreciated that the heterogeneity of the syndrome might require a more targeted/personalized approach toward ameliorating complex biologic pathways that might be differentially activated with different host responses and at different time points in each illness. Increasingly, it is appreciated that efforts targeted at prevention of ARDS represent a growing opportunity for investigation and treatment37, both in optimally identifying at-risk subjects and in selecting those most likely to benefit from early interventions. Of note, prevention studies will be a major focus of the NIH PETAL Network. In conclusion, although ARDS represents a challenging syndrome to characterize, manage, and treat, recent advances have improved clinical outcomes, and exciting approaches on the horizon hold promise for allowing us to gain insights into novel treatment strategies.Although targeted medical therapies have not yet proven beneficial in clinical trials, promising targets


Melanoma tumors are heterogeneous and involve different processes generating cells with variable metastatic capacity, which also results in distinct clinical outcome of patients and variations in therapy responses. This might be due to different strategies leading to evasion of T and or NK cell-mediated surveillance, which is accompanied by disease progression and a poor survival of melanoma patients. Therefore, the characterization of immune escape mechanisms might contribute to a better understanding of the development of the aggressive melanoma phenotype. This study analysed the underlying molecular mechanisms of HLA class I abnormalities and aberrant HLA-G expression in melanoma. A reduced mRNA and/or protein expression of various components of the MHC class I antigen processing machinery (APM) was identified in a large series of melanoma cell lines and lesions, which could be correlated with an increased tumor grading. In addition, adoptive T cell therapy also caused an escape from immune cell recognition by down-regulation components of the antigen processing machinery (APM). Recently, microRNAs (miRs) targeting HLA class I APM components were identified suggesting an important role for posttranscriptional control in this process. These miRs have functional activities on APM components, thereby also affecting HLA class I surface expression. Thus, these miRs might be used as novel targets for the treatment of melanoma or for selection of melanoma patients undergoing the most effective (immuno)therapy. In addition, a direct link of the IFN signalling pathway and the constitutive HLA class I APM component expression was found in melanoma. Down-regulation or loss of single components of the IFN-γ signal cascade was detected, which could be due to structural alterations, epigenetic mechanisms, such as methylation and/or histone deacetylation, or transcriptional/post-transcriptional deregulation. This was accompanied by a heterogeneous response of melanoma cells to IFN-γ treatment. Alterations in the IFN-γ signalling pathway were directly associated with a down-regulation of constitutive HLA class I components as demonstrated in melanoma lesions as well as in melanoma cell lines. Using shRNA-mediated silencing a direct effect of STAT1, JAK1 and JAK2 on MHC class I surface expression was confirmed. These data may provide novel insights into the complex regulation of HLA class I expression in melanoma and gives a rational for excluding patients for specific immunotherapies. Furthermore, strategies will be developed for restoration of the HLA class I positive phenotype.


Melanoma accounts for only 5% of all cancers but is the leading cause of skin cancer death due to its high metastatic potential. Patients with metastatic melanoma have a 10-year survival rate of less than 10%. While the clinical landscape for melanoma is evolving rapidly, lack of response to therapies, as well as resistance to therapy remain critical obstacles for treatment of this disease. In recent years, a myriad of therapy resistance mechanisms have been unravelled, one of which is autophagy, the focus of this review. In advanced stages of malignancy, melanoma cells hijack the autophagy machinery in order to alleviate drug-induced and metabolic stress in the tumor microenvironment, thereby promoting resistance to multiple therapies, tumor cell survival, and progression.  Autophagy is an essential cellular process that maintains cellular homeostasis through the recycling of intracellular constituents. Early studies on the role of autophagy in cancer generated controversy as to whether autophagy was pro- or anti-tumorigenic. Currently, there is a consensus that autophagy is tumor-suppressive in the early stages of cancer and tumor-promoting in established tumors.  This review aims to highlight current understandings on the role of autophagy in melanoma malignancy, and specifically therapy resistance; as well as to evaluate recent strategies for therapeutic autophagy modulation. BRAF is a serine/threonine kinase that is involved in various cellular processes such as proliferation, differentiation, and survival2. An important approach to treatment for melanoma is the use of inhibitors such as vemurafenib, dabrafenib, or cobimetinib, which specifically target the mutant BRAF. BRAF-directed therapy initially decreases tumor burden considerably; however, most patients ultimately develop resistance and tumors recur5. Melanoma cells can adopt various mechanisms of resistance such as the re-activation of the mitogen-activated protein kinase (MAPK) signaling pathway6 and aberrant activation of other signaling pathways such as the insulin-like growth factor receptor (IGFR) and Wnt signaling pathways8. Ultimately, reactivation of the MAPK pathway is a key feature of all of these different resistance mechanisms, and this has prompted the approval of combinatorial MAPK therapies that target multiple nodes in this signaling pathway9. In addition to these approaches to inhibit MAPK signaling for therapeutic gain, another important form of therapy for melanoma is immune checkpoint inhibition. This emerging form of therapy targets molecules such as CTLA-4 (cytotoxic T-lymphocyte-associated protein 4) or PD-1 (programmed cell death protein 1), which are found on immune cells and signal to inhibit the activity of T cells10. By disabling these checkpoints, most often by using antibodies against CTLA-4 or PD-1, the immune system is re-activated and can act to target and destroy the tumor cells. When these therapies are effective, their effects are durable, but many still do not initially respond to treatment, and resistance still appears in a subset of those who do respond, with the most recent data suggesting that while these rates are slightly increased with combination approaches to immunotherapy, they still remain under 50%. Understanding the mechanisms of resistance to targeted therapy and immunotherapy is therefore critical for effective eradication of melanoma.Malignant melanoma arises from melanocytes, cells that are responsible for pigment production. Approximately 50% of melanomas harbor a mutation in the BRAF gene, which leads to the dysregulated downstream activation of the MEK/ERK signaling pathway11. Recent studies in various types of cancers such as colorectal cancer, prostate cancer, lung cancer, and melanoma have demonstrated that in established tumors, cancer cells can also upregulate a related stress response process: autophagy. Current research is now focusing on manipulating autophagy in cancer cells in order to inhibit drug resistance and improve patient outcome. In this review, we will discuss the dual role of autophagy in melanoma and its implications in resistance to the therapies currently available for the treatment of melanoma. We will also discuss recent developments and strategies to inhibit autophagy activity in tumor cells in pre-clinical and clinical models and the importance of this as a means of re-sensitizing tumors to current therapies.The signaling pathways involved in resistance as well as the spectrum of therapy-acquired mutations that may arise have been well studied and discussed, while the cellular aspects of therapy resistance have not. For example, one way for melanoma cells to resist therapy is to undergo an adaptive stress response. We have previously shown that the initiation of a senescent-like phenotype is one way in which melanoma cells resist vemurafenib12. The main stages of the autophagy process are summarized inAutophagy can be activated by various stimuli such as nutrient depletion, hypoxia, infection, stress, and aberrant cell growth during cancer. The regulation and molecular circuitry of autophagy is quite complex and involves various conserved autophagy genes. The initial step of autophagy consists of the synthesis of the phagophore, which requires the ULK1 complex and the formation of the class III phosphoinositide 3-kinase (PI3-K) complex. This is followed by the elongation of the phagophore, which requires the ATG5-ATG12-ATG16 complex and lipidated microtubule-associated protein light chain 3 (LC3) − LC3II. The growing phagophore engulfs cytoplasmic material targeted for degradation as it progressively forms a complete autophagosome. The last step of autophagy involves the fusion of the autophagosome with the lysosome and the subsequent degradation of the vesicle’s content by lysosomal hydrolases13. Autophagy flux can be measured by the use of inhibitors that block the fusion of the autophagosome with the lysosome or by increasing lysosomal pH with a lysosomal proton pump inhibitor such as bafilomycin, thus allowing the measurement of accumulated LC3II14. Nascent LC3 is converted to LC3I by ATG4; LC3I in turn becomes conjugated with PE (phosphatidylethanolamine) to form LC3II. While LC3I remains in the cytoplasm, LC3II binds to both the outer and the inner membranes of the autophagosome; therefore, it is considered a marker of the autophagosome. It is important to note, however, that measurement of LC3II should be complemented with other methods such as transmission electron microscopy or fluorescence microscopy using the mCherry-enhanced green fluorescent protein (eGFP)-LC3 autophagy reporter system in order to have an accurate assessment of autophagy flux. The mCherry-eGFP-LC3B autophagy reporter system has been used in both fluorescence microscopy and the quantification of autophagy flux by flow cytometry15. This fluorescent reporter is based on the principle that the GFP tag is acid sensitive, while the mCherry tag is acid insensitive. In an unfused autophagosome, both tags are expressed, such that the cell glows yellow. When there is increased autophagy, such that the autophagosome fuses with the acidic autolysosome, or endosome, GFP is degraded, and mCherry is the stronger signal, such that the cell now glows red. This allows for a quantitative, dynamic assessment of autophagy in living cells. The ability to measure this complex process effectively using various methods has led to a greater understanding of autophagy in the spectrum of cancer.Autophagy is a dynamic process that involves numerous steps; therefore, measuring autophagy proteins and structures at any stage of the process might not be indicative of the overall changes in autophagy activity, so a measurement of flux through the entire autophagy pathway is recommended. Autophagy flux is described as the entire process of autophagy from the formation of the autophagosome to the formation of the autolysosome and subsequent degradation of the cargo and release of the degraded products into the cytosol18. In the context of cancer, affecting the genes involved in autophagy, such asATG5 orATG7 and the geneBeclin 1, has been shown to result in tumor promotion. For example, deletion ofATG5 orATG7 in the mouse induces spontaneous benign tumor formation in the liver and concomitant deletion ofp62 reduces tumor size, implying that accumulation of p62 due to deficient autophagy contributes to tumor progression17. Heterozygous disruption of theBeclin 1 gene has also been shown to cause spontaneous tumor formation and accelerate hepatitis B virus-induced neoplasia18.Beclin 1 is the mammalian orthologue of yeast autophagy-related geneATG6; it is an essential component of the class III PI3K, which is required for autophagy induction.Beclin 1 has also been found to be monoallelically deleted in human breast and ovarian cancer20. Mathew and colleagues investigated how the loss ofBeclin 1 contributes to tumorigenesis; they found that monoallelic loss ofBeclin 1 induces DNA damage and chromosome instability, which in turn can promote tumor initiation21. Taken together, these studies show that autophagy prevents tumor initiation by protecting cells from metabolic stress that can lead to an imbalance in cellular homeostasis. However, as tumors progress, autophagy takes on a different role. Studies in various types of cancers such as colorectal cancer, glioblastoma, and esophageal cancer have shown that established tumor cells use autophagy to meet the high metabolic demands of cancer cells that are rapidly proliferating24.Autophagy is essential for survival and development; aside from maintaining homeostasis, this catabolic process protects organisms from various types of conditions including neurodegenerative diseases, heart disease, liver disease, and aging25. Under stressful conditions, melanoma cells have been shown to upregulate autophagy activity as a protective mechanism; Marino and colleagues found that melanoma cells cultured under acidic conditions are able to survive through the upregulation of autophagy activity. Inhibition of autophagy by ATG5 knockdown decreased melanoma cell survival under acidic conditions26. This highlights the fact that melanoma cells can use autophagy as an adaptive mechanism to survive and progress under the stressful conditions of the tumor microenvironment.Liu and colleagues identified the BH3-only protein Noxa as a driver of melanoma development and progression; upregulation of Noxa by MEK/ERK oncogenic activation promotes an increase in autophagy through the transcription factor cAMP responsive element binding protein (CREB). In this study, Noxa was found to be necessary for MEK/ERK-driven autophagy; moreover, Noxa was shown to induce constitutive activation of autophagy that delayed the apoptosis of human melanoma cells under nutrient-deficient conditions24. In the particular case of melanoma, inhibitors designed to target mutant BRAF fail to produce long-term effects in the clinic owing to the emergence of resistance. One recent study investigated mechanisms of drug resistance in therapy-induced autophagy; Ma and colleagues investigated resistance pathways adopted by the autophagy machinery following treatment with PLX4720, a BRAFV600E inhibitor27. They found that BRAF inhibition upregulated autophagy in patients with BRAF-mutant melanoma; these patients were less sensitive to BRAF inhibition and had poorer clinical outcome. Further, in melanoma cells, both BRAF inhibition and combinatorial BRAF/MEK inhibition induced cytoprotective autophagy due to the activation of the endoplasmic reticulum (ER) stress response triggered by mutant BRAF binding to GRP78, a chaperone required for ER integrity27. Overall, the combination of BRAF and autophagy inhibition was found to be efficient in inducing tumor regression in the PLX4720-resistant tumor xenografts. As mentioned earlier, another mechanism of resistance is the reactivation of the MAPK pathway through MEK; a recent study explored the effects of MEK and autophagy inhibition in BRAF-inhibitor-resistant melanomas. The authors found that inhibiting autophagy in vemurafenib-resistant melanomas either by ATG5 knockdown or pharmaceutically was not sufficient in restoring sensitivity to vemurafenib treatment; however, combination of autophagy inhibition and MEK inhibition increased melanoma cell death28. Based on the aforementioned data, in recent years, many efforts have been made to unravel the effects of autophagy in melanoma tumor progression; however, there is still a need for the development of more melanoma models where tumor-specific autophagy inhibition is tested in the context of activated oncogenes, tumor suppressor gene loss, and modulated signaling pathways that drive melanoma growth and survival. This would allow the development of therapeutic strategies that most effectively halt the survival and progression of aggressive melanoma.in vitro andin vivo models using autophagy inhibition or combinatorial therapies in melanoma.Aggressive tumor cells with high autophagy levels are also prone to developing drug resistance by using autophagy to escape drug-induced stresses. For instance, in esophageal cancer, inhibition of Beclin 1 and ATG7 greatly increases the effects of the chemotherapeutic agent 5-FCUATG7 inV600EBRAF andPten-deficient melanomas suppressed tumor growth and extended survival of mice29. In this model, combination of ATG7 deficiency and dabrafenib treatment significantly decreased melanoma tumor growth and induced senescence29. These findings highlight the dependency of tumor cells on autophagy to survive and progress. Another study correlated autophagy activity with patient outcome in the clinic and proposed that autophagy is a potential prognostic factor for predicting melanoma cell invasiveness and patient outcome30. In this study, autophagy was measured in tumor biopsies obtained from metastatic melanoma patients enrolled in a phase II trial of temozolomide and sorafenib. Overall, patients whose tumors displayed high autophagy levels had a poorer clinical outcome compared to patients with low autophagy activity in their tumors. This positive correlation between autophagy activity and tumor aggressiveness was recapitulated in a tumor xenograft model where aggressive melanoma tumor xenografts displayed a higher autophagy flux compared to the indolent ones. Furthermore, autophagy inhibition by genetic knockdown ofATG5 or hydroxychloroquine (HCQ) treatment increased temozolomide-induced cell death in 3D culture30. An important point to note from the latter study is that not all melanoma patients will benefit from a treatment that targets autophagy; autophagy inhibition or combinatorial treatments involving autophagy inhibition will more likely benefit those patients whose tumors have high autophagy activity. It is also important to note that therapy can increase autophagy activity in patients’ tumors, and while it is known that therapy-induced autophagy can lead to the development of drug resistance, it is crucial to further dissect mechanisms by which autophagy induces drug resistance in order to have a rationale for the development of combinatorial therapies.In recent years, autophagy modulation through genetic knockdown of major autophagy genes or through the use of pharmacological inhibitors has been widely used with the goal of sensitizing tumor cells to metabolic stress. Using a genetically engineered mouse model (GEMM), Mehnert and colleagues showed that tumor-specific deletion of34. These trials evaluated maximum tolerated doses, pharmacodynamics, clinical activity, and toxicities in patients. HCQ is an anti-malarial drug that has been shown to inhibit the late stage of autophagy35. A phase I clinical trial of HCQ and temozolomide involved 40 patients with advanced solid tumors, 73% of whom had metastatic melanoma; >4 months of prolonged stable disease was observed in patients with metastatic melanoma. Partial responses and stable disease were observed in 14% (3/22) and 27% (6/22) of patients with metastatic melanoma, respectively. Pharmacodynamic activity of the combined therapyin vivo was measured by a significant accumulation of autophagy vacuoles in peripheral blood mononuclear cells31. Another phase I clinical trial in patients with advanced solid tumors and melanoma involved the combination of HCQ with the mTOR inhibitor temsirolimus. While no responses were observed, the majority of patients treated achieved stable disease. In 13 melanoma patients treated with HCQ at 1200 mg/d in combination with temsirolimus, the median progression-free survival was 3.5 months. In addition to measuring toxicity, this trial utilized FDG-PET measurements, which predicted clinical outcome and provided supporting evidence that this therapy increased metabolic stress in the tumors of patients who experienced clinical improvement32. Clinical trials involving HCQ have also been performed in other cancers such as pancreatic adenocarcinoma, where HCQ produced negligible anti-tumor effects due to inconsistent autophagy inhibition33. In myeloma, the combination of the proteasome inhibitor bortezomib and HCQ in 22 patients with relapsed or refractory myeloma resulted in 14% partial responses, 14% minor responses, and 45% stable disease34. Similar to other trials, the combination of HCQ and bortezomib resulted in accumulation of autophagy vacuoles as a pharmacodynamic marker of autophagy modulation. The aforementioned clinical trials show that therapy-induced autophagy inhibition is achievable and that there has been considerable progress in the modulation of autophagy for cancer therapy (In the clinic, the emergence of therapy resistance in melanoma and other cancers is a major problem. This has prompted immense efforts to develop autophagy inhibitors designed to increase chemosensitivity. In recent years, phase I/II clinical trials that involve HCQ-mediated autophagy inhibition have been undertaken in various cancers including melanoma, pancreatic cancer, and myelomatherapy . HoweverAlthough it is established that autophagy has a dual role in cancer, the dynamics by which this catabolic process suppresses or promotes cancer still remain complex. Efforts to unravel molecular and cellular mechanisms that might modulate autophagy activity in cancer cells have started to emerge. The overall findings reveal that the consequence of defective autophagy in the context of cancer is fundamentally contingent upon the stage of cancer development. Deficient autophagy can induce metabolic stress, which can lead to the accumulation of protein aggregates and dysfunctional mitochondria; this disruption of cellular homeostasis can in turn induce genomic instability and promote cancer development. On the other hand, many studies have now showed that in advanced stages of cancer, autophagy can promote therapy resistance and survival of aggressive tumor cells. Hence, the challenge lies in specifically targeting autophagy in the right subpopulation of tumor cells, and in the clinic it makes scientific sense that patients whose tumors have high basal autophagy will be the ones who benefit most from autophagy inhibition. A major challenge that also requires attention is the need for autophagy inhibitors that consistently inhibit autophagy and convey potent anti-tumor activity. In the particular case of melanoma, pre-clinical models and clinical trials have indeed demonstrated the potential of autophagy inhibition for therapy; however, more studies are needed to dissect the mechanisms that regulate autophagy in aggressive melanoma cells for the development of therapeutic strategies that will benefit patient outcome.CTLA-4, cytotoxic T-lymphocyte-associated protein 4; ER, endoplasmic reticulum; eGFP, enhanced green fluorescent protein; HCQ, hydroxychloroquine; IGFR, insulin-like growth factor receptor; LC3, microtubule-associated protein light chain 3; MAPK, mitogen-activated protein kinase; PI3-K, phosphoinositide-3-kinase; PD-1, programmed cell death protein 1.