Periodontitis is an incredibly prevalent chronic inflammatory disease, which results in the destruction of tooth supporting structures. However, in addition to causing tooth and alveolar bone loss, this oral inflammatory disease has been shown to contribute to disease states and inflammatory pathology at sites distant from the oral cavity. Epidemiological and experimental studies have linked periodontitis to the development and/or exacerbation of a plethora of other chronic diseases ranging from rheumatoid arthritis to Alzheimer's disease. Such studies highlight how the inflammatory status of the oral cavity can have a profound impact on systemic health. In this review we discuss the disease states impacted by periodontitis and explore potential mechanisms whereby oral inflammation could promote loss of homeostasis at distant sites. Barrier sites such as the mouth, gut and skin are interfaces between our inside bodies and the outside world. Maintaining their integrity is crucial to survival. Each barrier has unique requirements and must perform its physiological function whilst maintaining control of commensal microbes and responding to environmental insults and pathogen invasion. The immune system critically promotes barrier integrity in the face of these challenges and is carefully tailored to barrier environments, creating highly-specialized immuno-surveillance networks that police these sites. One area of intense research focus is to understand how tissue-specific signals balance immunity and regulation at barrier sites , 2. ElucSpecific bacteria have long been thought to drive development of periodontitis , howeverIndeed, recurring inflammation at the oral barrier has been shown to adversely affect systemic health, which may be especially important in individuals with pre-existing conditions. Periodontitis has been routinely associated with a multitude of diseases, ranging from inflammatory to infectious, as well as developmental, cardiovascular, and neurodegenerative conditions. Although aberrant immune responses, heightened inflammation, and oral bacteria are frequently proposed to explain these associations, the exact contribution of periodontitis to the etiology and/or progression of systemic disease is unclear in most instances. What is clear, however, is that pathology in the oral cavity can lead to potentially deleterious consequences for the rest of the body. In this review we will briefly discuss the diseases that have been associated with periodontitis as well as outlining the possible mechanisms by which periodontal inflammation could mediate its deleterious effects at distal body sites. We aim to cover the key mechanisms that have already been suggested but will additionally highlight novel mechanisms by which periodontitis could affect distal inflammatory diseases; taking lessons from inflammation occurring at extra-oral sites.Porphyromonas gingivalis, Streptococcus sanguis, Aggregatibacter actinomycetemcomitans, and Tannerella forsythia have been isolated from atheromas . An association between periodontitis and CVD was first reported 20 years ago . Since, theromas –20. Thestheromas , with P.l models .As periodontitis is causally linked to CVD, periodontitis is also by association often linked with cerebrovascular disease –26, a liP. gingivalis has been isolated from joints and is thought to drive RA pathology through molecular mimicry which promotes pathogenic self-reactive T cells that exacerbate disease (discussed further in the next section)  also lessen the severity of RA  –35. For section) . Given tty of RA –42, implMore recent evidence has also implicated periodontitis with an increase in cognitive decline in Alzheimer's disease (AD) –45. In pFusobacterium nucleatum has been shown to directly promote colorectal cancer  as well as habitual brushing, flossing, and mastication all increase the rate of blood contamination  and in t in vivo –99 and c in vivo –102. In  in vivo , and, whIn addition to microbial factors, chronic oral inflammation can also result in sustained and increased levels of host inflammatory mediators in the circulation, which is a trigger for the acute-phase response. Indeed, the acute-phase reactants, interleukin (IL)-6, C-reactive protein (CRP), haptoglobin, fibrinogen, serum amyloid A, and serum amyloid P are elevated in periodontitis patients –107. ProMoreover, there are reports of serum increases in levels of the pro-inflammatory cytokines IL-6 , IFN-γ , as wellP. gingivalis to promote RA pathology via molecular mimicry , and therefore is a direct contributor to the production of pathogenic antibodies, driving auto-reactive T cells to promote inflammatory synovial destruction -DRβ1 humanized mice, which are susceptible to RA, exposure to oral ype mice . This suIn a similar sense, changes in inflammatory genes can not only confer susceptibility to periodontitis, but can also account for the increased risk of adverse systemic effects due to periodontitis. IL-17 is a major driver of disease in periodontitis , RA 131131, as wP. gingivalis induced periodontitis enhances the severity of articular injury during experimental arthritis; this aggravation of arthritis did not occur in IL-17RA-deficient mice , thymic stromal lymphopoietin (TSLP), and IL-17 as candidates that can mediate long-range signals that influence the fundamental process of haematopoiesis –155. ForIn conjunction with relaying signals to the bone marrow, systemic cytokines could directly modulate other distal tissues such as the CNS. It has been recently demonstrated that a gut-initiated Th17 response is capable of inducing cognitive decline through the effects of systemic IL-17 on the cerebrovasculature, inducing endothelial dysfunction . As cytoAs well as cytokines, neuronal signals, particularly those of the autonomic nervous system have also emerged as critical regulators that can relay long-range signals to the haematopoietic compartment during homeostasis and inflammation –160. As 2 adrenergic receptor have been shown to be indispensable for Granulocyte colony-stimulating factor (G-CSF)-mediated mobilization of haematopoietic stem and progenitor cells (HSPC), through the downregulation of the bone marrow anchor, CXCL12   and mevaIt is conceivable that the systemic dissemination of cytokines, microbial products, and metabolites that occurs during periodontitis, could drive innate immune cell training. Unlike the changes to global haematopoiesis discussed in the previous sections, periodontitis could drive fundamental changes to monocyte function, resulting in the specification of immunogenic phenotypes in monocytes generated in the bone marrow. This could have catastrophic consequences as the generation of trained innate immune cells with altered immunogenic potential could well be a key driver of aberrant inflammation at extra-oral sites. Indeed alterations in peripheral blood monocytes have been noted in periodontitis patients –199, pot+CD4+ T cell recruitment from the lungs to the gut  that promote the homing of CD4+ T cells to the gastrointestinal tract through the up-regulation of the integrin α4β7 and CCR9 (Usually a consequence of alterations in the cytokine milieu, altering immune cell trafficking is also an effective means to modulate immunity at a distal site. This concept also contributes to the idea of a common mucosal immune system, extending immune responses beyond compartmentalized tissues , 201. Fo the gut . This reand CCR9 , again hIn fact, when considering the cross-talk between the oral barrier and distal tissues, it is particularly salient to probe mucosal sites, after all it is well-established that oral vaccination induces protective immunity at distal mucosal barriers , 203, inin situ (It is now well-established that commensal-derived signals play crucial roles in shaping both local immune networks at barrier surfaces, as well as distal tissue sites like the brain . This isin situ –211. Impin situ –214 and in situ , 216. Thin situ , 217–219in situ –223. Whein situ –226, genin situ –229. ThuData from pre-clinical animal models and epidemiological studies indicate strong associations between the presence of periodontitis and amplification of plethora of diseased states ranging from joint inflammation to cognitive decline. Despite this, only a few detailed mechanisms have emerged outlining how periodontitis mediates these deleterious effects. As discussed in this review, it is not difficult to envisage possible periodontitis-induced mediators that could be driving distal inflammatory consequences; what remains now is to better delineate these mechanisms and definitively establish cause-and-effect relationships during periodontitis. This can be achieved through well-designed animal experiments utilizing cutting-edge technologies to establish systemic and tissue-specific changes during periodontitis. Moreover, large scale, well-powered, human studies should be undertaken to assess the impact of periodontitis treatment on extra-oral disease pathology. This should be done alongside the careful clinical evaluation of oral parameters in patients with diseases associated with periodontitis, to generate detailed insight into the oral health of these patients. Better understanding of the cross-talk between the oral barrier and distal sites could support a step-change in the clinical treatment of many diseases. Not only could oral health parameters be employed to stratify patients and/or monitor disease progression but in some cases it may emerge that aggressive intervention to improve oral health could mediate dramatic improvements in a plethora of life-limiting diseases.CO reviewed data and wrote the sections regarding the systemic consequences of periodontitis and already postulated mechanisms driving these consequences. SK reviewed data and wrote the sections regarding possible mechanisms whereby periodontitis drives its systemic inflammatory risks. JK supervised the review process, wrote, and compiled the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Psychological resilience is critical to minimize the health effects of traumatic events. Trauma may induce a chronic state of hyperarousal, resulting in problems such as anxiety, insomnia, or posttraumatic stress disorder. Mind-body practices, such as relaxation breathing and mindfulness meditation, help to reduce arousal and may reduce the likelihood of such psychological distress. To better understand resilience-building practices, we are conducting the Biofeedback-Assisted Resilience Training (BART) study to evaluate whether the practice of slow, paced breathing with or without heart rate variability biofeedback can be effectively learned via a smartphone app to enhance psychological resilience.Our objective was to conduct a limited, interim review of user interactions and study data on use of the BART resilience training app and demonstrate analyses of real-time sensor-streaming data.We developed the BART app to provide paced breathing resilience training, with or without heart rate variability biofeedback, via a self-managed 6-week protocol. The app receives streaming data from a Bluetooth-linked heart rate sensor and displays heart rate variability biofeedback to indicate movement between calmer and stressful states. To evaluate the app, a population of military personnel, veterans, and civilian first responders used the app for 6 weeks of resilience training. We analyzed app usage and heart rate variability measures during rest, cognitive stress, and paced breathing. Currently released for the BART research study, the BART app is being used to collect self-reported survey and heart rate sensor data for comparative evaluation of paced breathing relaxation training with and without heart rate variability biofeedback.To date, we have analyzed the results of 328 participants who began using the BART app for 6 weeks of stress relaxation training via a self-managed protocol. Of these, 207 (63.1%) followed the app-directed procedures and completed the training regimen. Our review of adherence to protocol and app-calculated heart rate variability measures indicated that the BART app acquired high-quality data for evaluating self-managed stress relaxation training programs.The BART app acquired high-quality data for studying changes in psychophysiological stress according to mind-body activity states, including conditions of rest, cognitive stress, and slow, paced breathing. Psychological resilience—the ability to recover from a traumatic experience and return to mental well-being—is critical to minimize health effects, such as anxiety, substance abuse, sleep problems, or posttraumatic stress disorder (PTSD) -6. ExposReduction of arousal during or shortly after trauma exposure may prevent or reduce the likelihood of psychological distress, including PTSD symptoms -17. MindThe Biofeedback-Assisted Resilience Training (BART) study is evaluating whether routine practice of slow, paced breathing with and without HRV biofeedback can enhance psychological resilience by facilitating an HRV rebound after a stressor task. To support the study, we developed the BART mobile app, enabling participants to practice relaxation training outside of a formal training environment. This paper describes the BART resilience training app, demonstrates HRV biofeedback, presents processes that may have wider applicability for mobile health research, and reports the interim results of app usage.The BART study is being conducted in a mixed population of military personnel, veterans, and civilian first responders at multiple sites across multiple states in the United States. We recruited participants from a convenience sample of Navy, Marine Corps, and Army Reserve units and National Guard armories from North Carolina, Georgia, and Virginia, and fire and police units in the Raleigh-Durham, North Carolina, area who volunteered to participate for a 60- to 90-minute onsite training session, practice their training at home, and complete a suite of survey assessments over the course of 1 year. Eligibility criteria included having a smartphone and knowing their password. We offered monetary incentives in addition to allowing them to keep their study-related heart rate (HR) monitor chest strap.This study was approved by the University of North Carolina Institutional Review Board under an authorization agreement with the RTI International Committee for the Protection of Human Subjects; and the US Army Medical Research and Materiel Command, Office of Research Protections, Human Research Protection Office.The BART study is comparing 4 resilience training regimens: paced breathing at 5 or 6 breaths per minute, each with or without HRV biofeedback. Participants are randomly assigned to 1 of these 4 regimens and asked to practice paced breathing at least 3 times a week for 6 weeks, and thereafter for 12 months . ParticiThe study begins with a setup day (day 0) on which individuals provide their consent to participate, install the app on their smartphone, complete baseline assessments, learn to use their HR monitor , and practice 1 resilience training session, which includes a cognitive stress game. Special consideration is given to wearing the Polar HR sensor, linking the sensor to the BART app, and acquiring good-quality HR measurements. After this initial setup and instruction, participants execute all activities on their own for the duration of the study under the scheduling and direction of the BART app.BART app design was governed by the study protocol and schedule of participant activities , the preOur previous work in predeployment stress inoculation training, HRV biofeedback, and mobile technologies for mindfulness-based stress reduction strongly influenced our design of the BART app ,25,26. EWe implemented the BART app using the Personal Health Informatics and Intervention Toolkit (PHIT), a development framework geared to research-oriented mobile apps -30. The PHIT modules are implemented using XML and employ PHITScript to construct program logic and activate special app functions, such as collecting sensor data or scheduling notifications. Apps using the PHIT framework run locally without the need for an active internet connection. PHIT is based on Apache Flex (Apache Software Foundation) and AIR (Adobe Systems) technologies, which are both open source and widely used for mobile game development. A requirement for the BART study was that participants would use their own smartphones or tablets, necessitating app compatibility with both Android and iOS devices as provided by Adobe AIR.All acquired and derived data are stored on the device in an encrypted SQLite (SQLite Consortium) database and periodically uploaded by the participant to a secure central data server. To eliminate financial burden, neither continuous internet access nor use of the participant’s cellular data plan is required. Rather, data are uploaded whenever Wi-Fi internet access is available, and at the participant’s direction and convenience, either via Wi-Fi or the participant’s cellular data plan.The BART operational schema  centers Primary outcome measures acquired via the app are resilience , coping measures , and sleep problems . Secondary outcomes are mental health , physical health , and alcohol use problems (Alcohol Use Disorders Identification Test). Covariates are combat and deployment, recent tobacco and caffeinated beverage use, age, education, use of other relaxation techniques, and interest in learning relaxation skills. These measures, along with demographic information, were aggregated into a set of brief survey instruments to be completed at baseline (surveys 1-3), weekly, quarterly, and at 12 months.Health assessments are administered via brief self-report instruments, typically with a single question per screen b and c. The BART project employs real-time HRV analysis to provide physiological biofeedback during resilience training. Beat-by-beat heart intervals, also called interbeat intervals, are acquired continuously during each training session from a Bluetooth Low Energy  HR monitor. The raw interbeat intervals are streamed in real time to an HRV analysis module and stored in the app database to allow for subsequent offline quality review and analysis.Three variants of HRV measures are determined using the Porges-Bohrer HRV analysis methodology ,32: respWe asked participants to practice resilience training 3 times each week for 6 weeks, a 2-step process comprising a 3-minute resting segment and a 5-minute resilience training segment. Each participant was randomly allocated after consent to receive 1 of 4 resilience training regimens: paced breathing at 5 or 6 breaths per minute, with or without HRV biofeedback. Before training, the participant is asked to be in a quiet place and put on the Polar H7 HR monitor. When the participant is ready, the HR monitor is activated and a beat-by-beat HR trend is displayed to check signal quality a. The pawithout biofeedback, an animated ball is displayed as rising and falling upon a triangular graphic for paced breathing resilience training  and stressful (red) psychophysiological states, reflecting higher and lower parasympathetic activation.For participants receiving resilience training On study days 0 and 1, and after 6 weeks of training, participants complete an enhanced training regimen called the Training Game. The Training Game builds on the basic resilience training exercise by incorporating the Eriksen flanker task , a game-The Training Game begins with a 3-minute rest, followed by instructions on performing the Eriksen flanker task a. When rAdherence to study interventions and data collection is a common challenge in any research study, and especially when participants are asked to essentially perform the study on their own, albeit with app support. To support the frequency of resilience training (3 time per week), weekly assessments, and the yearlong period of follow-up assessments, the BART study design incorporated an incremental incentives approach to encourage participants to do scheduled activities and stay engaged across the duration. We were concerned, however, that manual monitoring of several hundred participants with time-shifted protocol schedules could be error prone and cause missed payments or awarding unearned payments. To mitigate such risk, we implemented incentive management to standardize both incentive qualification and automated distribution of incentive awards .In concert with the BART protocol , incentiTo further support the incentive process, monitor payments, and validate the accuracy of the incentive management process, a report of incentives earned and paid is produced weekly so that study staff may check each participant’s incentive record. This report not only aids in confirming payments, but also helps to resolve any problems that may have been experienced by participants and supports monitoring adherence across all participants.Ensuring privacy and security of data and on-device analysis results is an absolute necessity for ethical reasons, to meet human studies requirements, and to support data quality in the conduct of self-managed mobile research protocols. Participants are provided a randomized participant identification (ID), which uniquely links all acquired data to that individual without any personally identifiable information. They also enter a self-defined secret 4-digit personal identification number (PIN) to prevent access by other individuals. When in use, the app screen deactivates after a set period  of no interaction, and current data and activity is hidden. The 4-digit PIN must then be entered to unlock the screen and allow the participant to continue.Implementing a study using an app installed on the participants’ devices requires app installation from a public app store. Since anyone might download and install the app, and possibly upload false data, we addressed this quality and security risk by including an app lockout requiring an unlock password. After participants consent to take part in the study, the unlock is revealed, the app installed, and the password entered to activate. This prevents extraneous persons from entering and corrupting the study.All data are stored locally on the device in an encrypted SQLite database within the BART app, thereby permitting use without requiring a continuous internet connection. Data are stored using a 128-bit Advanced Encryption Standard algorithm with no personal identifying information. Data are periodically uploaded to a central secure data server whenever Wi-Fi internet access is available, thereby reducing use of the participants’ cellular data plans. Data are transferred using the secure https protocol and stored in a secure SQL server database, which is accessible only to authorized persons via user ID and password authentication.To showcase how the BART app is being used and to present examples of the HRV measures during resilience training, we conducted a limited, interim review of user interactions and study data. Consequently, data presented here do not address the study hypotheses on the effectiveness of various training modes on building resilience. Analysis of training effectiveness on resilience and other outcome measurements will be addressed separately after completion of data collection.We based data regarding app usage on participant rostering records and earned incentives reported. For each study activity , we tallWe reviewed the psychophysiological stress response during the cognitive stress and biofeedback training using the wideband biofeedback HRV measure across all segments . Our analysis was restricted to data taken during the first week of participation, before substantive resilience practice would yield any training effect.t tests to evaluate changes in HRV for sequential training segments. We conducted statistical analyses using IBM SPSS Statistics 25 (IBM Corporation).We computed descriptive statistics for the subpopulation extracted for the HRV measurement examples, with categorical variables reported by frequencies and numeric variables by mean (SE). We analyzed grouped HRV data using a univariate general linear model and present the data graphically as mean (2 SE). We used unpaired Of the 328 enrolled participants to date, 207 (63.1%) adhered to the study training regimen of 3 resilience training sessions per week for at least six weeks. In total, 3136 training episodes had been performed in this subset across the first 180 days of each participant’s involvement , in the HRV review. Of the 49 participants in the subset, 23 (47%) were female and 26 (53%) were male. We excluded HRV values that were out of the expected range (HRV<0 or HRV>10) as outliers, as such data are likely due to interbeat interval artifacts. We included multiple HRV measures per individual segment, ranging from 305 to 613 measures.P<.001). Later during the poststress recovery segment, the HRV rebounded to mean 7.148 , approaching the prestress baseline (P=.02). During training, HRV increased very significantly to mean 8.205 , reflecting strong parasympathetic activation with slow paced breathing (P<.001).We present grouped results for HRV, using the wideband biofeedback HRV measure, for each segment of the cognitive Training Game stressor exercise . As expeA large variety of mobile apps for stress reduction ,34,35, mPhysiological biofeedback during paced breathing resilience training and objective assessment of psychological arousal would not be possible without real-time continuous monitoring of HRV by the BART app. The HRV results during the Training Game exercise for the rest, cognitive stressor, recovery, and training segments  are consA limitation in this study is the use of cognitive stress as a surrogate for combat and operational stressors in this military population. Risk of death, exposure to combat or casualties, disconnection from loved ones, and working in extreme and unusual environments are examples of trauma that our study population might experience. Such stressors cannot be readily mimicked, nor should they, as previously exposed participants could experience negative reactions to simulated exposures. Use of a controlled cognitive exercise provides an alternative, safe, and common context to assess stress reactivity for evaluation of relaxation training.Along with the stated benefits, the BART study has yielded a variety of lessons for such self-directed app-based research. Using personal mobile apps not only to collect information, but also to manage protocol-based task scheduling, reminder notifications, and intervention activities, makes the study essentially self-administered by each participant. Unforeseen events, such as participant smartphone replacement, forgetting 4-digit security PINs, and assorted HR monitor failures, necessitated the implementation of technical support resources. We did this via website, telephone, and email interactions, with issue and resolution tracking using Jira Software v7.11.2 (Atlassian). Maintenance of personal interest, usability of sensors and devices, adherence to procedures, and timely technical support are critical in retaining participation for the study duration.The nature of our study population (primarily military reserve units) imposed a requirement to recruit participants, then immediately install the BART app and provide initial training in a group setting, often with more than 20 individuals present. These large groups compromised our process to establish Bluetooth links between individual participant’s HR monitor and smartphone in a multiparticipant environment. We addressed this by having participants configure their app in small subgroups, which eased the installation and setup process considerably.Furthermore, while the selected HR monitors work quite well with exercise, obtaining a good HR signal was often difficult while the participant is sitting at rest . Multiple adjustments of the sensor strap and repeated configuration attempts were often required, and we suppose that continued problems of this sort likely contributed to participant dropout. Advances in wearable HR sensor technology, such as upper arm photoplethysmography, may make them easier to use and more reliable under resting conditions than a device designed for exercise. As such devices emerge with enough accuracy for HRV measurement, we expect to improve protocol adherence and reduce participant dropout due to problems experienced with the HR sensor.Incorporation and automation of incentive management is a vital aspect of the BART app. We are using monetary incentives, an important component of research projects, to support adherence to study procedures and reward participants for carrying out certain tasks, such as completing a survey or resilience training. Since participants have individual start dates, their individual calendar of study activities will differ across the study population, making manual monitoring of study adherence both time consuming and error prone. By embedding adherence management, we can check protocol activities frequently, then reward participants immediately using automatic, incremental incentive payments. Weekly reports to study staff on incentive payments yielded useful feedback on protocol adherence and the potential for intervention by study staff to help keep individual participants on track.Retention of users is a common issue with mobile apps in general. Bonnie  reportedWhile a key component of ensuring optimal study participation, automation of incentive management was not without issues. Initially we had a somewhat complex set of requirements for participant incentives, including requiring their resilience trainings plus completion of the weekly survey in each of the first 4 weeks to receive the incentive payment. Furthermore, participants were given 4 days to compete the survey, and then it was removed from the activities menu. Despite instructions via the embedded incentive requirements table, several participants complained that they did not receive incentives. Upon review, we found that they did not fully meet the requirements but, as they met most, we decided to award the incentives anyway. We then relaxed the requirements, while still asking that these tasks be completed (or at least initiated), so that such persons would not drop out of the study. Nonetheless, having the automated incentive checking and database recording was helpful to review these cases and to consider the participant’s actions and understanding how to better incentivize study activities.Results presented is this paper merely showcase features and capabilities of the BART app, along with preliminary data on app usage and demonstration of analyses of real-time sensor-streaming data, such as the psychophysiological HRV response to cognitive stress and paced breathing training.Currently distributed for the BART research study, the BART app is being used to collect self-reported survey and HR sensor data for comparative evaluation of paced breathing relaxation training with and without HRV biofeedback. Our preliminary ad hoc analyses indicate that the app acquires high-quality data for studying changes in psychophysiological stress according to mind-body activity states, including relaxation and cognitive stress conditions. However, no conclusion of effectiveness, or noneffectiveness, of the biofeedback-assisted relaxation training intervention should be drawn from these data.


The activity of the commensal microbiota significantly impacts human health and has been linked to the development of many diseases, including cancer. Gnotobiotic animal models have shown that the microbiota has many effects on host physiology, including on the development and regulation of immune responses. More recently, evidence has indicated that the microbiota can more specifically influence the outcome of cancer immunotherapy. Therapeutic interventions to optimize microbiota composition to improve immunotherapy outcomes have shown promise in mouse studies. Ongoing endeavors are translating these pre-clinical findings to early stage clinical testing. In this review we summarize 1) basic methodologies and considerations for studies of host-microbiota interactions; 2) experimental evidence towards a causal link between gut microbiota composition and immunotherapeutic efficacy; 3) possible mechanisms governing the microbiota-mediated impact on immunotherapy efficacy. Moving forward, there is need for a deeper understanding of the underlying biological mechanisms that link specific bacterial strains to host immunity. Integrating microbiome effects with other tumor and host factors regulating immunotherapy responsiveness versus resistance could facilitate optimization of therapeutic outcomes. The commensal microbiota and the human host have co-evolved in a mutualistic relationship, in which each benefits the fitness of the other and the two can be collectively viewed as a superorganism. Much recent research has focused on the bacterial component of the microbiota. On average, a healthy human body is comprised of approximately 30 trillion cells and is inhabited by approximately 39 trillion bacterial cells [microbiome and vastly outnumbers human genes. The microbiota is capable of synthesizing or transforming a wide variety of metabolites, including hormones, essential vitamins, and other bioactive compounds, which cannot be otherwise acquired by the host [The human body is a complex ecosystem inhabited and influenced by an abundance of microorganisms including bacteria, yeast, fungi, protozoa, archaea, and viruses, all of which collectively constitute the commensal al cells . The colthe host . These mthe host –15. In tthe host . Preclinthe host , 18.In adults the microbiota consists of about a dozen phyla, primarily Firmicutes and Bacteroidetes, followed by Actinobacteria, Proteobacteria, Fusobacteria, and others . The relCulturomics is a strategy which incorporates multiple culture conditions, coupled with MALDI-TOF mass spectrometry and/or 16S ribosomal RNA (rRNA) or total genome sequencing for bacterial identification [Culturing of bacterial strains has been central to classical microbiology and has enabled the study of individual pathogens and some commensal bacteria. For most commensal bacteria, culture methods had not been optimized for their in vitro isolation and study. With recent improvements in methodology, a large proportion of commensal bacteria is now considered culturable , 26. Culfication , 28. ThiThe most common method for taxonomic characterization of complex bacterial communities is based on selective amplification and sequencing of part of the gene encoding the 16S rRNA, part of the small ribosomal subunit in prokaryotes. This is a ubiquitous 1.5 kb gene, containing conserved sequences and hypervariable regions (nine regions: V1-V9), the latter being useful for bacterial taxonomic classification, as originally described by Woese and colleagues . In the Metagenomic shotgun sequencing generates short reads representing the whole genomic content within an environmental sample and is considered less biased than 16S rRNA gene amplicon sequencing, because it does not contain a PCR amplification step. However, this can result in contamination with human genomic DNA and requires higher sequence coverage to detect bacterial species of low abundance. This necessitates additional data storage, computing power, and more sophisticated analysis pipelines. Errors can also be introduced in the downstream analysis at the step of genome assembly or gene prediction . Variousgnotobiotic pertains to animals with known (defined) microbiota composition and encompasses GF, as well as ex-GF animals colonized with defined microbial communities. The commensal microbiota broadly impacts host physiology, and this has been mainly shown in studies with GF mice, which have inefficient energy extraction from the diet, abnormal fluid balance and electrolyte status, and disturbances in liver, lung, cardiovascular system, endocrine organ, nervous system, and immune system functions [The role of the commensal microbiota in modulating host physiology becomes particularly evident when conventionally raised specific pathogen-free (SPF) mice are compared to germ-free  mice. GF mice are defined as devoid of detectable microbiota during their life. The term unctions , 46.+ T cells, plasma cells, and decreased IgA production leading to further impaired intestinal barrier function [+ T cell numbers, but also for proper programming of the local Treg/Th17 balance. GF mice are almost completely devoid of Th17 cells, but have increased frequency of FoxP3+ T cells [The gut microbiota is intimately involved in the development and regulation of the immune system, especially with respect to local mucosal immunity. This has been demonstrated in GF mice, which show deficiencies in the gastrointestinal immune compartment rendering them more susceptible to infections. However, such deficiencies can be corrected by colonization with commensal bacteria. For instance, in GF mice, the mucus-producing goblet cells are fewer and smaller. As a result, the mucus layer, the first line of defense against pathogens in the intestine, is thinner and has a different mucin composition , 48. Addfunction , 56. The T cells .Systemic innate immune modulation is also influenced by the commensal microbiota, with multiple lines of evidence indicating stimulatory effects on myelopoiesis at the level of granulocyte-macrophage progenitors in the bone marrow and in the periphery, as well as on the function of DCs, macrophages, and neutrophils (reviewed in ). In manBacteroides fragilis [Clostridium clusters XIVa, IV, and XVIII [B. fragilis can polarize towards Th1-type responses [+ dendritic cells (DCs), macrophages and mononuclear phagocytes [Different members of the commensal microbiota are not equivalent in their capacity to polarize T cell responses. For instance, in SPF mice the group of segmented filamentous bacteria (SFB), which colonize the mouse terminal ileum and adhere to the epithelial cells, are particularly potent inducers of Th17 cell differentiation . SFB arefragilis  and Closnd XVIII , 69. Polesponses . Higher esponses . Monocolagocytes . Notablyagocytes . This isSPF mice have been used to gain valuable insight in the impact of microbiota-host interactions on host physiology in health and disease. When it comes to clinical translatability, a question that arises regarding the degree of similarity between the microbiomes of humans and laboratory mice. Although a direct comparison between datasets from different studies can be blurred by differences in analysis platforms and protocols, a general consensus exists that on a phylum through family level, the microbiomes of SPF mice and humans are similar with both species being predominantly colonized by Bacteroidetes and Firmicutes , 71. ComLactobacillae, whereas in humans, the stomach contains mainly Streptococcus, Prevotella spp. and Helicobacter pylori [plicae circularis) in the human small intestinal mucosa, which are absent in mice [There are some differences between mice and humans which might affect the efficiency of human gut microbiota engraftment into mice or their spatial establishment throughout the GI tract. A potentially relevant difference in GI tract anatomy is the presence of a non-glandular fore-stomach in mice, which takes up two thirds of the stomach, has no secretory activity, and serves for temporary food storage. This allows for food to be ingested in bulk, but to be released for downstream digestion more gradually according to energy demands. The lack of gastric secretions in the fore-stomach results in higher pH of its contents (pH 4.8)  and the r pylori , 73. Ano in mice , 74. The in mice . Mice al in mice . In mice in mice .GF mice have many physiological defects, which can become a confounding factor in microbiome studies. Notably, due to compromised intestinal barrier function and immature immune system in GF mice microbial colonization could result in systemic translocation and abnormal magnitudes and sites of microbe-host interactions . A more An alternative to using GF mice as human microbiota recipient is the use of antibiotic-treated SPF mice. Although SPF mice with intact microbiota are generally not receptive to human microbiota, engraftment can be substantially improved with certain antibiotic regimens, which deplete the bulk of the pre-existing commensals, thus opening up an niche for subsequent colonization , 82. Suc+ T cells and Treg cells in the MLN and IL-4 and IL-12 cytokine responses in spleen cells [When interpreting results from experiments with GF mice, it should also be considered that even though GF mice are devoid of detectable viable microbiota, they are exposed to microbial residues  derived from dead bacteria in sterile diet and bedding . If presen cells . Indeed,en cells . Use of B. fragilis was reported to enhance anti-CTLA-4 efficacy via a proposed mechanism involving the activation of Th1 cells with cross-reactivity to bacterial antigens and tumor neoantigens [Bifidobacterium increased tumor infiltration and IFN-γ production by CD8+ tumor-specific T cells and improved both basal tumor control and anti-PD-L1 efficacy via a proposed mechanism involving increased activation of splenic and intratumoral DCs [Multiple studies support that gut microbes can profoundly influence the potency of immunotherapy and some chemotherapies with immunostimulatory functions ? Such a messenger would be able to enter the circulation in order to access the distant tumor site and can be classified as microbiota- or host-derived cell (live microbes or host immune cells) or molecule . The second question is what is the nature of the immune effect that the messenger confers within the tumor? An immunosuppressive effect could be achieved by augmenting regulatory functions  or directly inhibiting anti-tumor immunity; an immunostimulatory effect could be achieved by alleviating regulatory functions or stimulating anti-tumor T cell responses . The exact mechanisms of microbiota-mediated effects on tumor growth and efficacy of immunotherapy are only beginning to be understood. Figure When it comes to exploring the possible mechanisms of microbiota-mediated modulation of anti-tumor immunity, two general questions arise. First, what is the nature of the antigenicity as well as adjuvanticity, as described below.Commensal bacteria have been identified in extra-gastrointestinal tissues typically considered to be sterile. Notably, Geller et al. identified bacteria within the TME in human pancreatic ductal adenocarcinoma . In this+ T cells) or through direct killing (CD8+ T cells). In a preclinical study, adoptive transfer of B. fragilis-reactive CD4+ T cells conferred enhanced tumor control and restored anti-CTLA-4 efficacy in GF mice [Some data suggest a mechanistic role for T cell epitopes shared between bacteria and tumor cells , 89, 95. GF mice . PeripheBifidobacterium sp. showed superior priming of naïve CD8+ T cells ex vivo [. Enrichment in Faecalibacterium genus in patients with metastatic melanoma associated with responsiveness to ICB therapy was also associated with increase in antigen processing and presentation markers in the tumor [Microbiota-derived MAMPs or PAMPs can traverse the mucosal barrier and enter the circulation. For instance, serum from healthy individuals was demonstrated to contain stimuli capable of activating a range of TLR and NOD receptors . In the  ex vivo . Enrichmhe tumor .Gut bacteria produce various bioactive molecules as byproducts of their metabolism. These metabolites can exhibit diverse effects on the host, including modulating the immune system . SCFAs a. To address this question, metagenomic and metatranscriptomic sequencing approaches coupled with metabolomic analysis of patient serum and stool samples will be critical for a more complete characterization of the biosynthetic pathways present within a given microbiome. Insights into metabolic contributions of the microbiome in the context of immunotherapy also may lead to new candidate therapeutic strategies, either through provision of desired metabolites as drugs, or via genetic manipulation of selected commensals for clinical administration.Given the predicted importance of bacterial metabolic contribution to host immunity and immunotherapy efficacy, there is significant interest in identifying both the specific bacteria exerting immune modulatory effects, as well as the functional and metabolic characteristics of these bacteriaAkkermansia muciniphila improved the efficacy of PD-1 blockade in an IL-12–dependent manner in mice [Another potential mechanism by which gut bacteria could modulate systemic immune responses is through local induction of soluble immunomodulatory factors that then disseminate systemically. Circulating cytokines may shift the activation threshold of key immune subsets within the TME or TdLN, thus leading to augmented adaptive immune responses in the context of immunotherapy. Candidate mechanisms include increased production of type I interferons, IL-12 and TNFα, or decreased production of immune suppressive cytokines such as IL-10 and TGF-β. As an example, segmented filamentous bacteria can induce secretion of IL-22 from type 3 innate lymphoid cells in mice, causing production of serum amyloid A in the terminal ileum which, in turn, acts on the LP DCs to drive Th17 polarization , 108. In in mice .A recurring theme in many of the described mechanistic studies is that innate immune cells, often DCs, represent the central cell type affected by perturbations within the commensal community , 110. DCDifferent mechanisms of microbial sensing by DCs might be in play in the context of a damaged versus intact intestinal barrier. Compromised barrier integrity could allow for translocation of live bacteria or microbial products into the circulation. These could then be recognized by PRRs on innate immune cells, such as DCs, and affect downstream innate and adaptive immunity. Such potential mechanisms may contribute to microbiota-mediated modulation of anti-tumor immunity in situations of gut inflammation, such as with total body irradiation, chemotherapy agents that cause mucositis, or with anti-CTLA-4 treatment where 11% of patients experience colitis and 34% develop diarrhea . HoweverGiven the complexity of the commensal-host interaction, the diversity of the microbiome, and inter-individual variability, it is likely that multiple modalities contribute to the impact of the microbiota on immunotherapy efficacy. Furthermore, the relative contribution of the microbiome will need to be integrated along with other dimensions affecting the potency of immunotherapy, including germline genetic determinants and tumor cell-intrinsic oncogenic alterations –118. Det+ Tregs. In those defined instances, appropriate antibiotics might decrease the abundance of such immune regulatory bacteria, perhaps allowing immune-potentiating bacteria to bloom and support improved tumor control. Studies are ongoing in reconstituted GFM to test these ideas.The collective evidence linking the gut microbiome to immunotherapy efficacy creates exciting opportunities to improve clinical treatment strategies. A straightforward implication is that antibiotics administration to patients receiving cancer immunotherapies should be pursued with caution. Routy et al. found that antibiotics administration to patients in conjunction with immunotherapy was associated with shorter PFS and shorter overall survival (OS)  and thesThe modulatory effects of the microbiome could foreseeably offer multiple avenues of clinical intervention. Microbiome composition could be considered as a complementary prognostic or predictive biomarker for treatment outcomes. Higher bacterial diversity in the gut  was identified to be associated with better response rates to ICB . More spPreclinical evidence extends the correlative relationship between the microbiome and response observed in patients to support a causal role. This scenario opens the exciting possibility to improve efficacy by manipulating the gut flora. Intervention strategies range from less precise or “blunt” approaches to more targeted therapeutic approaches . For example, fecal samples could be prepared from anti-PD-1 responders that show a favorable composition of commensal bacteria, then transplanted endoscopically or prepared for oral delivery into patients who are anti-PD-1-resistant and show an unfavorable composition of gut microbes. This approach would parallel the strategies being used to treat refractory patients . This apAlistipes, Bilophila and Bacteroides) and decreased levels of Firmicutes that metabolize dietary plant polysaccharides  [A subtler means of intervention may include modulating the existing commensal community via prebiotics or dietary changes to favor the expansion of beneficial bacteria that require specific substrates, or conversely, “starving” detrimental bacteria of their required nutrients. For example, short-term changes in human macronutrient consumption towards a high fat, low fiber animal-based diet increased bile-tolerant microorganisms ( bromii) . SimilarBacteroides strain modified to carry a gene cluster to utilize porphyran stabilized its engraftment into mice fed a porphyran-supplemented diet [Escherichia coli, genetic manipulation is routine, but for many human commensals, incomplete genomic information leaves fewer tools available for these strategies currently. To circumvent this limitation, it is possible to express bacterial genes of interest heterologously in common laboratory hosts such as E. coli or Bacillus subtilis [Alternatively, beneficial or immune-potentiating bacteria could be prepared as a probiotic and provided as an immunotherapy adjuvant. Once molecular mechanisms are determined, genetic manipulation of the selected bacteria could be utilized to maximize beneficial effects. Historically, certain bacterial species have been some of the most amenable organisms to genetic manipulation, and the breadth of tools available to study and modify bacteria continues to expand. This technology allows the modification of a bacterium’s existing function or the introduction of completely novel genes . For exated diet . This stted diet . For welsubtilis . An altesubtilis .Finally, if a bacterial metabolic pathway is identified along with defined metabolic products that mediate improved anti-tumor immunity and immunotherapy, then small molecule entities could be tested as candidate immune-potentiating drugs. In all cases, appropriately controlled clinical trials will be required to validate any potential microbiome-based therapy and to assess benefits and risks. Clinical trials to evaluate the impact of fecal microbiome transplant and probiotic administration with checkpoint inhibitors are already underway .+ mononuclear phagocytes [Given the intricacy of the microbiome, it will be challenging to tease out the essential mechanistic elements in such a complex system. Even if two individuals harbor the same species of bacteria, there can be variation of each bacterium at the strain level, which could yield divergent functions upon interaction with the host. Moreover, two identical strains in two disparate communities may contribute differently to their collective consortium and thus function differently with respect to the host. As such, tremendous care will need to be taken when assigning specific functional attributes to given commensal bacteria. Furthermore, a large majority of focus on cancer immunotherapy and the microbiome has investigated the contribution of bacteria but has yet to thoroughly investigate non-bacterial components including viruses, fungi and protozoa. Evidence in non-cancer disease models has indicated that the mycobiome (fungi) and the virome (viruses) can regulate systemic immunity. For example, manipulation of the mycobiome by oral antifungal drugs increased the severity of allergic airway disease in mice and was dependent on gut-resident CX3CR1agocytes , 128. Thagocytes . Supportagocytes , and infagocytes  and haveagocytes , 133. InLooking forward, it is important to recognize that the microbiome contributes only one dimension to the many facets that govern the interface between cancer and the host immune response. Cancer cells grow and evolve under the selective pressure of therapy, and molecular evolution of the tumor could still occur when the microbiome is manipulated to maximize immunotherapy efficacy. In addition, it is conceivable that the composition of the microbiome similarly may evolve over the course of cancer progression and therapy administration. This variation offers additional research challenges, but with this pliability also comes exciting promise for intervention and exploiting the host-microbiome interdependency to deliver more potent therapy. In the future, it will be important to consider the microbiota as one of several parameters to be incorporated into considerations of personalized cancer therapy.


NTR, but it binds more strongly to p75NTR and more weakly to TrkA than does mature NGF. This renders proNGF more sensitive to receptor balance than mature NGF. In the healthy brain, where BFCNs express both TrkA and p75NTR, proNGF is neurotrophic, activating TrkA-dependent signaling pathways such as MAPK and Akt-mTOR and eliciting cell survival and neurite outgrowth. However, if TrkA is lost or if p75NTR is increased, proNGF activates p75NTR-dependent apoptotic pathways such as JNK. This receptor sensitivity serves as a neurotrophic/apoptotic switch that eliminates BFCNs that cannot maintain TrkA/p75NTR balance and therefore synaptic connections with their targets. TrkA is increasingly lost in mild cognitive impairment (MCI) and AD. In addition, proNGF accumulates at BFCN terminals in cortex and hippocampus, reducing the amount of trophic factor that reaches BFCN cell bodies. The loss of TrkA and accumulation of proNGF occur early in MCI and correlate with cognitive impairment. Increased levels of proNGF and reduced levels of TrkA lead to BFCN neurodegeneration and eventual p75NTR-dependent apoptosis. In addition, in AD BFCNs suffer from reduced TrkA-dependent retrograde transport which reduces neurotrophic support. Thus, BFCNs are particularly vulnerable to AD due to their dependence upon retrograde trophic support from proNGF signaling and transport.Profound and early basal forebrain cholinergic neuron (BFCN) degeneration is a hallmark of Alzheimer’s disease (AD). Loss of synapses between basal forebrain and hippocampal and cortical target tissue correlates highly with the degree of dementia and is thought to be a major contributor to memory loss. BFCNs depend for their survival, connectivity and function on the neurotrophin nerve growth factor (NGF) which is retrogradely transported from its sites of synthesis in the cortex and hippocampus. The form of NGF found in human brain is proNGF. ProNGF binds to the NGF receptors TrkA and p75 The Alzheimer’s disease (AD) brain undergoes progressive dysfunction, degeneration and loss of neurons and synapses in selective areas of the brain . AmyloidBasal forebrain cholinergic neurons (BFCNs) are extremely important for learning, memory, and attention . They arin vitro  for survival and proper function. They do not make NGF themselves and must obtain it through retrograde transport from their targets. Older literature focused on the mature form of NGF, demonstrating that it is highly expressed in developing and adult hippocampus and cerebral cortex and is retrogradely transported from these target areas by BFCNs . NGF supin vitro  and in v and its ligand Lingo-1  pathways for p75NTR , which express high levels of p75NTR compared to TrkA, respond to proNGF with increased apoptosis (NTR levels, apoptotic activity of proNGF in vivo has been shown only in situations where TrkA is missing or down-regulated and p75NTR is up-regulated (nnr5 cells but is neurotrophic for TrkA-over-expressing PC12nnr5-B5 cells (In contrast to these data, NTR . ProNGF poptosis . Importapoptosis . Supportegulated . Furtheregulated . Lastly,B5 cells .It was reported that proNGF requires intracellular proteolysis to activate TrkA , a findiNTR determines whether proNGF is neurotrophic or apoptotic. This is of critical importance because TrkA is lost in AD (In sum, proNGF can signal without cleavage, and the balance between TrkA and p75st in AD , as discAxonal transport defects are common characteristics of many neurodegenerative diseases, and mutations in components of the axonal transport machinery have demonstrated that impaired axonal transport can cause neurodegeneration . Lack ofReduced proNGF signaling and transport may be due to disrupted transport machinery or to reduced TrkA, or both. In animal models, unilateral fimbrial transection, which severs cholinergic projections from the medial septum to the hippocampus, and colchicine, which disrupts axonal transport, increase hippocampal NGF-immunoreactivity but not NGF mRNA , consistNTR levels (NTR is not required for NGF transport (TrkA mRNA is lost in the basal forebrain of persons with AD . This deR levels . InternaR levels , but wheransport  but may ransport . Interesransport .Recently, TrkA has been shown to bind APP, the precursor to amyloid-β, resulting in its non-pathological processing . Thus, lReduced retrograde transport of NGF has been demonstrated in animal models of aging and Down’s syndrome . Animal NTR, but it also binds to TrkA and elicits survival signaling through the MAPK and Akt pathways. ProNGF controls survival and death of NGF-dependent neurons in the basal forebrain, depending on the balance of TrkA and p75NTR. This is particularly important because TrkA receptors are lost in AD.ProNGF is abundant in the CNS and can have both neurotrophic and apoptotic activities, depending on the receptor complement. ProNGF binds strongly to p75Axonal transport defects are common characteristics of many neurodegenerative diseases, and mutations in components of the axonal transport machinery have demonstrated that impaired axonal transport can cause neurodegeneration. BFCNs are uniquely dependent upon a constant supply of target-derived proNGF for their survival and function, and therefore reduced retrograde axonal transport of proNGF may cause degeneration and death of BFCNs. These neurons are crucial for learning, memory and attention, they are among the most vulnerable neurons in aging and AD, and they depend upon target-derived proNGF for their survival and function.NTR apoptotic pathways, thus initiating a neurodegenerative cascade. Rescue of axonal transport of signaling endosomes carrying cargoes such as BDNF, which supports motor neurons, ameliorates disease progression in a mouse model of ALS (Multiple mechanisms may limit survival of BFCNs in AD. ProNGF accumulates in cortex and hippocampus in AD but is reduced in basal forebrain, suggesting a retrograde transport defect. The transport deficit may be the result of AD pathology or loss of TrkA, or both. The accumulation of proNGF, along with loss of TrkA, reduces retrograde survival signals and switches proNGF signaling to p75l of ALS . Thus, rAll authors listed have made a substantial, direct and intellectual contribution to the work, and approved it for publication.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


The efforts to personalize treatment for patients with breast cancer have led to a focus on the deeper characterization of genotypic and phenotypic heterogeneity among breast cancers. Traditional pathology utilizes microscopy to profile the morphologic features and organizational architecture of tumor tissue for predicting the course of disease, and is the first-line set of guiding tools for customizing treatment decision-making. Currently, clinicians use this information, combined with the disease stage, to predict patient prognosis to some extent. However, tumoral heterogeneity stubbornly persists among patient subgroups delineated by these clinicopathologic characteristics, as currently used methodologies in diagnostic pathology lack the capability to discern deeper genotypic and subtler phenotypic differences among individual patients. Recent advancements in molecular pathology, however, are poised to change this by joining forces with multiple-omics technologies  that provide a wealth of data about the precise molecular complement of each patient’s tumor. In addition, these technologies inform the drivers of disease aggressiveness, the determinants of therapeutic response, and new treatment targets in the individual patient. The tumor architecture information can be integrated with the knowledge of the detailed mutational, transcriptional, and proteomic phenotypes of cancer cells within individual tumors to derive a new level of biologic insight that enables powerful, data-driven patient stratification and customization of treatment for each patient, at each stage of the disease. This review summarizes the prognostic and predictive insights provided by commercially available gene expression-based tests and other multivariate or clinical -omics-based prognostic/predictive models currently under development, and proposes a more inclusive multiplatform approach to tackling the challenging heterogeneity of breast cancer to individualize its management. “The future is already here—it’s just not very evenly distributed.”-William Ford Gibson It has become increasingly apparent over the past few decades that in order to grasp and effectively combat the heterogeneity that typifies breast cancer (BC), high-granularity tumor biomarker profiling is not merely desirable, but in fact, indispensable. Increasingly affordable novel technologies and deep-content analytics are enabling molecular profiling of tumors throughout the course of patient care. Specifically, the interrogation of the tumor tissue as well as its genome, transcriptome, epigenome, proteome, metabolome, and other aspects of both the tumor and the host characterize the burgeoning field of -omics research, which uses bioinformatics and computational technology to explore the mechanistic properties of molecules. The discovery and validation of definitive genetic and phenotypic biomarkers have emerged as the cornerstone of predictive and prognostic testing that can be used to parse patients with BC into subgroups and risk categories for analysis, thus helping to identify targeted treatments for each patient’s unique molecular profile by “matching the pill to the ill.”Molecular diagnostic tests, however, are only as good as the biomarkers they identify or measure. Like any diagnostic test, a tumor biomarker test, whether genetic or phenotypic, must have analytic and clinical validity as well as clinical utility. In the current BC landscape, several commercial genomic assays available to oncologists are transforming patient treatment. The assays to determine the status of the biomarkers such as estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) have long been used for the primary identification of tumors for targeted therapy and prognostication. Other assays serve as companion diagnostic (CDx) tests due to their ability to predict tumor response to specific cancer therapy drugs. These CDx assays are useful for existing as well as new drugs, increasing the clinical value of therapy by selecting for potential responders or excluding patients at risk for severe adverse effects. For pharmaceutical companies, CDx assays facilitate regulatory approval of new therapeutic regimens, enhance the probability of success in clinical trials, and in combination with adaptive trial designs, make trials more cost-effective.Clinical decision making in BC chiefly relies on determining clinicopathologic features of a tumor as well as on protein- and gene-based biomarker panels. The review, ordered in a broadly chronological fashion, begins with examining these mainstays and developments therein. This is followed by a discussion on more recent technologies for data gleaning  that are receiving tremendous attention in consonance with the significant information they generate. The advances in digital pathology, particularly the use of convoluted and deep neural networks, adding invaluable tools to the repertoire, have also been covered in the review. The clinico-pathological parameters, typically the tumor size, grade, nodal status, age of patient are crucial variables that when combined meaningfully can effectively determine the prognosis in BC patients. In primary breast cancer, the Nottingham prognostic index (NPI) calculated using the tumor size, lymph-node stage, and pathological grade is considered the standard . The NotThe most widely used protein markers  are well-described predictive markers for hormonal and anti-HER2 therapy. Immunohistochemistry (IHC) is a commonly used technique to measure the expression of these biomarkers. Additionally, in situ hybridization  is performed to quantify HER2 gene amplification which often results in HER2 overexpression. The IHC4 index is a non-commercial algorithm that assesses these four protein markers, generating a disease recurrence score. A lack of validation studies and poor reproducibility has marred this prognostic tool’s prospects in general clinical application . The IHCThe urokinase plasminogen activator (uPA) and its inhibitor protein plasminogen activator inhibitor-1 (PAI-1) have shown to be promising independent prognostic markers and have attained the highest level of evidence (LOE-1a) in terms of clinical utility in BC ,11. In sThe multiplexed immunohistochemistry (mIHC) is a recent tool that allows for simultaneous probing of several protein biomarkers on the same biological sample. The staining of samples can be chromogenic or fluorescent. This is crucial when the tumor sample size is limiting. The mIHC can provide valuable insights about the co-expression and spatial distribution of many targets without compromising tissue integrity . DespiteMany currently available prognostic and predictive tests in breast oncology utilize genomic and gene expression-based biomarkers, a trend that was spurred by the continually decreasing costs of whole-genome, gene panel, and RNA sequencing, and that requires only small sample volumes for processing. Multigene assays often interrogate one or more pathways that drive tumor biology, and predict the natural progression of the disease (with or without therapeutic intervention) based on its inherent aggressiveness. Thus, these tests help distinguish patients who need more aggressive treatments from those for whom the current standard-of-care may suffice, reducing healthcare expenditures. Several multigene tests (MGTs) are now routinely used in the clinical setting, and have been described in previous literature ,69,70,71The performance of six multigene signatures were compared in women with early ER-positive BC who underwent endocrine therapy for 5 years. These multigene signatures included the oncotype Dx recurrence score, the PAM50-based Prosigna risk of recurrence (ROR), the breast cancer index (BCI), EndoPredict (EPclin), the clinical treatment score, and the 4-marker immunohistochemical score. The BCI, EPclin, and the PAM50-based Prosigna ROR showed significant prognostic value for predicting the overall and late distant recurrence in patients with lymph node (LN)-negative disease. The results from this telling study have proven useful for guiding oncologists and patients in choosing the most suitable testing to inform decisions regarding chemotherapy and/or extended endocrine therapy. These tests, however, have provided limited prognostic information for patients with node-positive disease .BRCA1, BRCA2, PALB2 and PTEN genes by sequencing, can be especially useful in selecting BC patients who may be eligible for poly ADP-ribose polymerase (PARP) inhibitors [BRCA1 and BRCA2 as well as tumoral genomic instability. The assay uses DNA extracted from FFPE or frozen tumor tissue and labels a tumor as homologous recombination-deficient or -nondeficient, thus identifying patients who are most likely to benefit from treatment with PARP inhibitors. The BRACAnalysis CDx (Myriad Genetics) is an FDA-approved test for BRCA1 and BRCA2 for selecting patients suitable for olaparib treatment [Identifying specific mutations such as in the hibitors . Comprehreatment ,75.Of all aforementioned BC assays, only two prognostic assays, namely, Oncotype DX and Prosigna, originally assigned triple-category risk groups. However, Oncotype DX has recently discarded the intermediate recurrence score group. The intermediate recurrence score (RS)  in Oncotype DX had arguably been a grey area, leaving many women uncertain and concerned about their best treatment options (to omit chemotherapy or not) ,33. To aIn summary, MGTs offer several advantages. MGTs assign appropriate weightage to each variable and optimally extract information provided by multiple continuous variables. The information they provide is robust due to redundancy by capturing similar information from multiple genes. Even though these tests require specialized expertise to perform and interpret the results, overall, they prove to be cost-effective. Gene expression signatures are, however, unable to capture the prognostic information contributed by variables, such as tumor size or LN spread status, that lack an equivalent gene expression imprint. Therefore, there is a need to elevate the use of these clinicopathologic prognostic variables from merely providing complementary information to their incorporation as integral components of multivariate clinicogenomic risk models. These models could be built for distinct subtypes of BC because the prognostic value of each variable varies with the subtype and its unique tumor biology. In this regard, recently, Sparano et al., determined whether clinical risk assessment i.e., integrating tumor size and histologic grade, added prognostic and/or predictive information to the Oncotype DX RS. This was accomplished via secondary analyses of the TAILORx trial, and the results concluded that combining these information , provided prognostic information but was not predictive of chemotherapy benefit .As the currently available MGTs assess the different pathways/gene sets, there remains the issue of discordance in risk assignment for a given patient sample by different MGTs. This ambiguity poses a challenge and increases the practical difficulty for clinicians in recommending a particular test, necessitating a head-on-head comparison of the MGTs. Although the prognostic gene signatures are being applied in clinical research trials, their ability to predict response to specific therapeutic agents is not as clear-cut. They are yet to graduate into routine clinical use for BC management. Furthermore, the gene expression-based tests focus only on the transcriptome, and it is becoming increasingly clear that gene expression and proteomic landscapes can diverge substantially. The MGTs entail gene expression profiling of a single sample from a tumor and evaluating a limited number of genes. They are thus, unable to adequately capture several aspects of the tumor’s phenotype, including intratumoral heterogeneity, the tumor microenvironment, and profiles of tumor infiltrating cells, all of which profoundly influence tumor biology and patient prognosis. Moreover, the current gene panels do not inform about driver mutations and epigenetic events involved in disease progression. Intratumoral heterogeneity has implications in therapy resistance as well as cancer progression and recurrence. Early detection of resistant subclones and tracking evolution of tumors requires longitudinal tissue sampling which is not practically feasible. This information can be gleaned by liquid biopsies instead, that offer a relatively non-invasive real-time monitoring method for serial sampling of circulating tumor DNA and tumor cells.In many ways, nucleic acid markers seem ideal for elucidating disease pathology, and a fair number of molecular diagnostic tests exploit genetic variations , and allow the capture of information pertaining to their subcellular localization, thus providing an edge over their nucleic acid counterparts. Furthermore, protein-based biomarkers are able to capture intratumoral heterogeneity and the expression of biomarkers in the tumor microenvironment, combining biological with morphological information. The following sections focus on the development of assays to analyse secreted protein molecules, circulating tumor cells and nucleic acids.Liquid biopsy involves the analysis of circulating tumor cells (CTCs), cell-free circulating nucleic acids  and exosomes, released into the peripheral blood or urine from the primary tumor and/or metastatic deposits. It has recently emerged as a noninvasive prognostic, surveillance, and predictive tool in both early and metastatic BC that may complement, augment, or replace (in some cases) the use of tissue biopsy. The ease of sampling combined with the ability to monitor tumor burden or mutation changes temporally with ctDNA, allows for disease monitoring, the evaluation of therapeutic response, and molecular profiling in the advanced disease setting to determine therapeutic targets. The research in using ctDNA to tailor treatments has shown encouraging results. For example, the BELLE-2 trial and the SoFEA trial have demonstrated the clinical applicability of ctDNA to detect PI3K and ESR1 mutations, respectively, and the benefit of targeting these mutations with PI3K inhibitors and fulvestrant, respectively ,79. The 9 normal blood cells in metastatic cancer, their identification and isolation is particularly difficult [In addition to ctDNA, CTCs may be used to predict the risk of relapse in early-stage disease . The ECOifficult . DespiteThe CELLSEARCH Circulating Tumor Cell Kit (Menarini-Silicon Biosystems), a real time liquid biopsy currently licensed by Janssen Diagnostics among other companies, is the only CTC technology accredited by the FDA for the management of patients with metastatic BC. The semi-automated system uses a simple, actionable blood test based on an immunomagnetic enrichment technology . A cut-oThe EPISPOT assay  is also used to detect living CTCs although it employs a strategy different from CELLSEARCH ,93. A muThe Nagrath Laboratory at the University of Michigan has created a superior CTC isolation technology in the form of a prototype wearable that continuously and directly traps CTCs from the patient’s blood. As the remaining blood products are returned post-CTC enrichment, larger blood volumes can be scanned, providing a lucid picture of tumor cell heterogeneity. This counters one of the major shortcomings in the current CTC technologies that rely on smaller blood draws, thus suffering from statistical variability .When integrated at different points in the disease course, liquid biopsies can proffer information over and above that provided by standard clinicopathologic variables alone. Compared with CTC-based assays, ctDNA assays are superior when it comes to providing an individualized snapshot of a patient’s disease status, and they have greater sensitivity for early cancer detection. Unlike CTCs, ctDNA capture does not require specialized equipment . AlthougVidessa Breast (Provista Diagnostics) is a combinatorial multi-protein biomarker blood test for BC that evaluates 11 serum protein biomarkers (SPBs) and 33 tumor-associated autoantibodies (TAAbs) . The datA few FDA approved serum BC markers worth mentioning are the Carcinoma Antigen 15-3 (CA 15-3), Carcinoma Antigen 27-29 (CA 27-29) and PIK3CA. These have proved useful in monitoring the disease course in metastatic BC . The cliSeveral microRNAs (miRNAs) are dysregulated in BC . This knEquipped with the information that cancer cells display altered metabolism, a signature indicative of the presence and behavior of cancer can be generated via metabolite profiling. The information regarding the variant levels of metabolites between healthy subjects and those with cancer can be obtained by combining techniques of nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry with multivariate statistical analysis. The application of metabolomics in cancer diagnostics and therapeutics is fairly new and promising, as it can provide a much-needed link between the genotype and phenotype together with some insight into oncogenesis . MoreoveTumor infiltrating lymphocytes (TILs) are an integral part of the tumor microenvironment and have been observed in all BC subtypes, with high counts detected in high-grade, aggressive tumors . ParticuEven though several studies have demonstrated the prognostic value of TIL assessment, and standardized methods are now available, the St. Gallen International Breast Cancer Conference guidelines from 2017 still do not require the inclusion of TILs in routine pathology reporting . The higAmong emerging biomarkers, neoantigens display great promise in predicting responses to immunotherapy . Exome sPathology has always been a driver behind precision medicine, and a H and E-stained slide is the touchstone of a pathologic analysis, especially when the tissue amounts are insufficient for molecular analysis . HistopaA 2017 study by Bejnordi et al. showed the use of convolutional neural networks (CNN) in diagnosing and classifying whole-slide images from breast biopsies into three classes . The overall classification accuracy for their system was 81.3% . More reCentrosome amplification (CA)  is commonly observed in pre-invasive lesions, such as DCIS as well as invasive breast tumors. Its reputation as a BC prognostic marker strengthened in light of research that showed, high-risk BC subtypes such as TNBC patients, display higher CA (and overexpression of CA associated genes), which is associated with tumor aggressiveness and poor clinical outcomes . FurtherMittal et al. have rigorously quantitated structural amplification of centrosomes in tumor samples by integrating immunofluorescence confocal microscopy with digital image analysis via an IP-protected semi-automated pipeline technology. This yields a quantifiable biomarker, the centrosome amplification score (CAS), which can stratify DCIS into low- and high-CA categories, the latter associated with a greater risk of local recurrence. The CAS may prove to be superior to the VNPI in terms of predicting the risk of local recurrence for women with DCIS of the breast .Ogden et al. identified and validated CA20, a 20 gene CA transcriptomic signature , in breast tumors. CA20 is an independent predictor of poor survival and a high score is indicative of high chromosomal instability (CIN) and tumor aggressiveness . Later, A major challenge for large-scale precision medicine research is in harmonizing data from different sources. This can be overcome by standardizing nomenclature and developing sophisticated metadata descriptions that enable data integration, and by enabling the portable reproducible reanalysis of datasets. In this context, two prominent BC staging systems are being discussed, the American Joint Committee on Cancer (AJCC) Tumor/Node/Metastasis (TNM) classification and the Neo-Bioscore system (University of Texas MD Anderson Cancer Center).Recognizing the need to incorporate biologic factors  and gene expression-based prognostic panels, in addition to the traditional anatomic factors into its staging system, the AJCC recently extensively revised its eighth edition of the TNM classification system, which remains the worldwide basis for BC staging. Furthermore, the AJCC Breast Expert Panel has recommended providing two BC Prognostic Stage tables; the Clinical Prognostic Stage Group  and the Pathologic Prognostic Stage Group .Furthermore, emphasizing and lending credence to the importance of tumor biology as critical for BC prognosis, researchers at the MD Anderson Cancer Center have developed the Neo-Bioscore system, a new BC staging system that builds on their previously developed CPS+EG staging system. The CPS+EG system predated the routine use of trastuzumab (Herceptin) in the neoadjuvant setting, and uses the clinical stage of cancer before NAC treatment and the pathologic stage post-NAC (CPS score), the estrogen receptor status (E), and cancer grade (G). The system generates a score that helps estimate 5-year distant metastasis-free survival post-NAC, but is unable to provide prognostic information for patients with HER2-positive disease. The Neo-Bioscore staging system overcomes this limitation by incorporating HER2 status into the score .Although NGS, the backbone of multigene assays and whole-exome/genome sequencing, has vastly improved our understanding of the origin and evolution of cancer, it has generated a deluge of information and new quandaries. The clinical interpretation of the results , as well as properly assigning pathogenicity to variants, is a work in progress. Importantly, the possibility of overinterpreting NGS testing results may lead to unnecessary medical action and add to the high levels of anxiety experienced by patients with BC and their families. Cancer gene panels do provide a middle ground by addressing the clinical questions while avoiding information overload. Additionally, NGS data yield variants of uncertain significance and incidental findings  that raise ethical-legal concerns. Moreover, privacy issues are inherent when placing genomic data in the public domain and sharing genetic information, particularly regarding heritable mutations, with genetic relatives. Clearly, physician training has become crucial. Physicians need to understand the value/limitations of the data derived from these assays in the context of clinical care, and collaborate closely with genetic counselors to help their patients receive the best treatments possible.The global profiling of an individual’s tumor at the genomic, proteomic, transcriptomic, metabolomic, and other – omic levels is technologically achievable now. A case in point is GPS Cancer, a molecular test by NantHealth that integrates whole-genome and whole-transcriptome sequencing with quantitative targeted proteomics of both normal and cancerous tissue. The presence of protein biomarkers in tumor cells at levels as low as attomoles/µg of tumor tissue can be ascertained, providing actionable insights for immunotherapy, chemotherapy, targeted therapy, hormonal therapy, and monoclonal antibody therapy. DNA, RNA, proteomic, copy number variant, and other information can now be seamlessly woven together using sophisticated big data analytics to generate probabilistic causal networks, improving the chances of identifying the perturbations that drive a tumor’s biology, or enabling a deeper segmentation of heterogeneous patient cohorts for precision medicine. However, all data are not created equal, and multi-omic analysis can be time- and cost-prohibitive. Thus, different variables might need to be accorded different weights depending on the subtype of BC and/or the stage of disease (early versus advanced) to optimize the treatment and achieve the best outcomes possible. There is also a pressing need for multivariate prognostic/predictive models that are not plagued by a lack of biomarker standardization and inter-observer variability. A useful addition to the current models would be that of a monitoring tool/biomarker (for a period > 10 years) to address the issue of late disease recurrence.Projects like the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA) are working toward a shared goal of cataloging oncogenic mutations in order to further our understanding of the genetic basis of cancer, which can have a direct bearing on the diagnosis and management of the disease. The TCGA has generated exhaustive, multidimensional maps of crucial genomic alterations in 33 cancer types. The ICGC is coordinating genomics studies in tumors from 50 different cancer types and/or subtypes. The International Cancer Genome Consortium for Medicine (ICGCmed) will link the (as yet) aggregated genomics data to clinical and health information and response to therapies. The concerted efforts of these and other similar global projects are generating huge amounts of data  that comprise RNA sequencing, proteomic, and imaging data, apart from genomic data.To effectively employ NGS and the various biomarkers in the field of precision medicine requires complement with next-generation functional diagnostic technologies. The next-generation functional testing approach works around the limitations of traditional chemosensitivity tests by involving new cultivation methods for patient-derived tumor cells ex vivo, entailing the monitoring of live tumor states, and exposing a patient’s tumor biopsy ex vivo to drugs, thus directly revealing the cellular response to the applied agent. This does not require prior knowledge of a drug’s mechanism of action, and if the tumor cells are sensitive , the drug can be clinically administered promptly . Novel mCutting- edge - omics technologies, digital pathology, and new multibiomarker assays, together with clinical annotation, have granted unprecedented insights into the biology driving tumor development and the exploitable vulnerabilities, and are daily transforming the management of BC. The key lies in the effective integration of these multi-platform data and mining it for meaningful information. While the field of precision medicine in BC is making remarkable strides, it is important not to lose sight of the potential roadblocks ahead and the limitations of the current biomarkers and technologies. One such limitation is the lack of sensitive and specific biomarkers for early detection of BC. Another matter of concern is the copious amounts of genomic data being generated currently, which is only set to multiply in the future. Based on the current infrastructure, most research organizations will struggle to store and manage these data, let alone optimally analyze them. There is also the problem of underrepresentation of minority populations in most research cohorts. Detecting significantly mutated genes and all alterations involved, requires the interrogation of thousands of samples. There is thus a pressing need for increasing sample sizes for precision medicine research. Finally, increasing cohort size tackles the problem that not all genetic variants associated with disease are equally common, or equally easy to detect. As the number of sequenced genomes grows, it may be found that rare variants make important contributions to many diseases.


The explosion of mobile health  interventions has prompted significant investment and exploration that has extended past industry into academia. Although research in this space is emerging, it focuses on the clinical and population level impact across different populations. To realize the full potential of mHealth, an intimate understanding of how mHealth is being used by patients and potential differences in usage between various demographic groups must also be prioritized. In this viewpoint, we use our experiences in building an mHealth intervention that incorporates an iOS app, Bluetooth-enabled blood pressure cuff, and Apple Watch to share knowledge on (1) how user interaction data can be tracked in the context of health care privacy laws, (2) what is required for effective, nuanced communication between clinicians and engineers to design mHealth interventions that are patient-centered and have high clinical impact, and (3) how to handle and set up a process to handle user interaction data efficiently. Mobile health  interventions promise to improve patient outcomes, increase self-management and health literacy, reduce health disparities, increase access to health services, and lower health care costs in ways previously unachievable ,2. Howev1c over 1 year compared with the usual care group [mHealth studies evaluating clinical and population-level impact have made strides in this direction. For example, BlueStar by WellDoc, a Food and Drug Administration (FDA) cleared mHealth intervention for patients with type 2 diabetes, demonstrated a significantly lower mean decrease in hemoglobin Are group . Similarre group . One conre group -7.Thus, to realize the full potential of mHealth interventions, validation of individual clinical outcomes is not enough. mHealth interventions are typically complex with multiple aims and components, including educational material, self-monitoring tools, and various other aspects of health behavior change constructs. Making meaningful insights and developing recommendations require understanding the causal model of how the intervention will achieve its intended benefit, how key components of the intervention interact with one another, and what combinations will optimize a return on investment . SmartphImportantly, an analysis of mHealth back-end data presents important challenges, and few studies have examined clinical outcomes in the context of app usage data . Here, wThe back-end data analysis allows mHealth teams to identify features that patients use most regularly and take that into account in an iterative design process, thus quantifying and supporting insights collected through patient surveys and focus groups. This enables teams to begin to understand if specific features may be associated with improved clinical outcomes and ultimately helps make interventions more patient-centered.events and (2) the recording of time elapsed on view controllers. Such collection of intrasession measures (within sessions) of user engagement allow for the evaluation of specific user interactions and behaviors, while intersession measures (across sessions) evaluate long-term user engagement and satisfaction [Although there are a number of different ways to track app usage , our intsfaction .events are generated any time a patient (user) undertakes a specific action—for example, taking vitals, creating follow-up appointments, and completing learning goals. View controllers correspond to individual screens on iPhone. These view controllers can then be grouped by the feature they are a part of, allowing for the identification of features that patients spend the most time on  files over the HIPAA-compliant Johns Hopkins secure virtual desktop. We then transitioned to sharing a JavaScript Object Notation (JSON) file (a data-interchange format) and hiring a data scientist, giving clinicians access to all of the back-end data without the need for extensive teamwide technical training. Although we advocate hiring a dedicated data scientist to bridge the gap between clinicians and engineers early on, as studies scale up and move toward pragmatic trials that evaluate real-world implementation, we believe the end-goal also includes an HIPAA-compliant, queryable dashboard for clinicians, with data visualization and electronic medical record integration  CreatingGoing forward, it will be essential for research teams to evaluate mHealth interventions in the context of potentially differential app usage patterns and to create environments that support continuous, technically nuanced communication between their clinical and engineering counterparts. Although more business than clinical in nature, these changes to practice are essential to building interventions that patients actively want to use in real-world settings. In our experience with mHealth, being consumer-centered is synonymous with being patient-centered and is the future of health care delivery. We hope our experiences help interdisciplinary teams navigate similar challenges , as the