Nivolumab plus ONC201 plus in microsatellite stable (MSS) metastatic colorectal cancer (mCRC) patients: a Brown University Oncology Research Group phase Ib/II study (BrUOG379).

Background: Immune checkpoint inhibitors alone, or in combination with chemotherapy failed to provide meaningful clinical activity for patients with microsatellite stable (MSS) colorectal cancer (CRC). ONC201 is a small molecule that inactivates AKT and ERK signaling and actives the TRAIL pathway. Preclinical studies indicated potential benefits of combining ONC201 with checkpoint inhibitors. This is a phase Ib/II trial of ONC201 plus nivolumab for patient with MSS CRC who progressed on standard treatment. Methods: Enrolled patients received ONC201 plus nivolumab in a dose de-escalation fashion to determine the maximum tolerated dose (MTD). Additional patients were enrolled in the dose-expansion cohort. ONC201 at a dose of 625 mg was given orally at day -7 of cycle 1, followed by weekly dosing. Nivolumab was given every 2 weeks at 240 mg IV starting on day 1 of every cycle (cycle =28 days). The primary end point was dose-limiting toxicity (DLT) during the observation window (run-in dose day -7, cycle 1 to assessment pre-dosing cycle 2). The plan was to enroll 28 additional patients at the MTD so that a total of 34 patients would be treated at the MTD. Pharmacokinetics (PKs) and tumor biopsies were collected at several time points per study protocol. Results: A total of 13 patients (8 patients in the dose escalation *6 evaluable*) were enrolled between December 4, 2019 and March 2021. All patients had received ≥2 previous lines of chemotherapy and had confirmed microsatellite stability or mismatch repair-proficient tumors. No DLTs were observed with 625 mg ONC201 in the first three patients. Three additional patients were enrolled at the same dose to confirm safety. Two patients progressed during the DLT period and had to be replaced. During the dose-expansion part, five patients were enrolled and none required dose reduction or modification. No objective tumor response was observed in the 13 treated patients. Disease progression was confirmed at the time of the first imaging evaluation at 8 weeks following cycle 2. Post discussion at the Data and Safety Monitoring Board (DSMB) on May 25, 2021, the principal investigator (PI) and Committee voted to close the study to new patient enrollment prior to reaching accrual of 34 patients, secondary to lack of efficacy. Conclusions: In this study of patients with advanced MSS CRC, combination ONC201/nivolumab was well-tolerated; objective responses to ONC201/nivolumab were not observed.

Tribulations and future opportunities for artificial intelligence in precision medicine.

Upon a diagnosis, the clinical team faces two main questions: what treatment, and at what dose? Clinical trials' results provide the basis for guidance and support for official protocols that clinicians use to base their decisions. However, individuals do not consistently demonstrate the reported response from relevant clinical trials. The decision complexity increases with combination treatments where drugs administered together can interact with each other, which is often the case. Additionally, the individual's response to the treatment varies with the changes in their condition. In practice, the drug and the dose selection depend significantly on the medical protocol and the medical team's experience. As such, the results are inherently varied and often suboptimal. Big data and Artificial Intelligence (AI) approaches have emerged as excellent decision-making tools, but multiple challenges limit their application. AI is a rapidly evolving and dynamic field with the potential to revolutionize various aspects of human life. AI has become increasingly crucial in drug discovery and development. AI enhances decision-making across different disciplines, such as medicinal chemistry, molecular and cell biology, pharmacology, pathology, and clinical practice. In addition to these, AI contributes to patient population selection and stratification. The need for AI in healthcare is evident as it aids in enhancing data accuracy and ensuring the quality care necessary for effective patient treatment. AI is pivotal in improving success rates in clinical practice. The increasing significance of AI in drug discovery, development, and clinical trials is underscored by many scientific publications. Despite the numerous advantages of AI, such as enhancing and advancing Precision Medicine (PM) and remote patient monitoring, unlocking its full potential in healthcare requires addressing fundamental concerns. These concerns include data quality, the lack of well-annotated large datasets, data privacy and safety issues, biases in AI algorithms, legal and ethical challenges, and obstacles related to cost and implementation. Nevertheless, integrating AI in clinical medicine will improve diagnostic accuracy and treatment outcomes, contribute to more efficient healthcare delivery, reduce costs, and facilitate better patient experiences, making healthcare more sustainable. This article reviews AI applications in drug development and clinical practice, making healthcare more sustainable, and highlights concerns and limitations in applying AI.

Trials and Tribulations of MicroRNA Therapeutics.

The discovery of the link between microRNAs (miRNAs) and a myriad of human diseases, particularly various cancer types, has generated significant interest in exploring their potential as a novel class of drugs. This has led to substantial investments in interdisciplinary research fields such as biology, chemistry, and medical science for the development of miRNA-based therapies. Furthermore, the recent global success of SARS-CoV-2 mRNA vaccines against the COVID-19 pandemic has further revitalized interest in RNA-based immunotherapies, including miRNA-based approaches to cancer treatment. Consequently, RNA therapeutics have emerged as highly adaptable and modular options for cancer therapy. Moreover, advancements in RNA chemistry and delivery methods have been pivotal in shaping the landscape of RNA-based immunotherapy, including miRNA-based approaches. Consequently, the biotechnology and pharmaceutical industry has witnessed a resurgence of interest in incorporating RNA-based immunotherapies and miRNA therapeutics into their development programs. Despite substantial progress in preclinical research, the field of miRNA-based therapeutics remains in its early stages, with only a few progressing to clinical development, none reaching phase III clinical trials or being approved by the US Food and Drug Administration (FDA), and several facing termination due to toxicity issues. These setbacks highlight existing challenges that must be addressed for the broad clinical application of miRNA-based therapeutics. Key challenges include establishing miRNA sensitivity, specificity, and selectivity towards their intended targets, mitigating immunogenic reactions and off-target effects, developing enhanced methods for targeted delivery, and determining optimal dosing for therapeutic efficacy while minimizing side effects. Additionally, the limited understanding of the precise functions of miRNAs limits their clinical utilization. Moreover, for miRNAs to be viable for cancer treatment, they must be technically and economically feasible for the widespread adoption of RNA therapies. As a result, a thorough risk evaluation of miRNA therapeutics is crucial to minimize off-target effects, prevent overdosing, and address various other issues. Nevertheless, the therapeutic potential of miRNAs for various diseases is evident, and future investigations are essential to determine their applicability in clinical settings.

Circulating microRNAs as Potential Biomarkers in Pancreatic Cancer-Advances and Challenges.

There is an urgent unmet need for robust and reliable biomarkers for early diagnosis, prognosis, and prediction of response to specific treatments of many aggressive and deadly cancers, such as pancreatic cancer, and liquid biopsy-based miRNA profiling has the potential for this. MiRNAs are a subset of non-coding RNAs that regulate the expression of a multitude of genes post-transcriptionally and thus are potential diagnostic, prognostic, and predictive biomarkers and have also emerged as potential therapeutics. Because miRNAs are involved in the post-transcriptional regulation of their target mRNAs via repressing gene expression, defects in miRNA biogenesis pathway and miRNA expression perturb the expression of a multitude of oncogenic or tumor-suppressive genes that are involved in the pathogenesis of various cancers. As such, numerous miRNAs have been identified to be downregulated or upregulated in many cancers, functioning as either oncomes or oncosuppressor miRs. Moreover, dysregulation of miRNA biogenesis pathways can also change miRNA expression and function in cancer. Profiling of dysregulated miRNAs in pancreatic cancer has been shown to correlate with disease diagnosis, indicate optimal treatment options and predict response to a specific therapy. Specific miRNA signatures can track the stages of pancreatic cancer and hold potential as diagnostic, prognostic, and predictive markers, as well as therapeutics such as miRNA mimics and miRNA inhibitors (antagomirs). Furthermore, identified specific miRNAs and genes they regulate in pancreatic cancer along with downstream pathways can be used as potential therapeutic targets. However, a limited understanding and validation of the specific roles of miRNAs, lack of tissue specificity, methodological, technical, or analytical reproducibility, harmonization of miRNA isolation and quantification methods, the use of standard operating procedures, and the availability of automated and standardized assays to improve reproducibility between independent studies limit bench-to-bedside translation of the miRNA biomarkers for clinical applications. Here I review recent findings on miRNAs in pancreatic cancer pathogenesis and their potential as diagnostic, prognostic, and predictive markers.

Advances in Liquid Biopsy Technology and Implications for Pancreatic Cancer.

Pancreatic cancer is a highly aggressive malignancy with a climbing incidence. The majority of cases are detected late, with incurable locally advanced or metastatic disease. Even in individuals who undergo resection, recurrence is unfortunately very common. There is no universally accepted screening modality for the general population and diagnosis, evaluation of treatment response, and detection of recurrence relies primarily on the use of imaging. Identification of minimally invasive techniques to help diagnose, prognosticate, predict response or resistance to therapy, and detect recurrence are desperately needed. Liquid biopsies represent an emerging group of technologies which allow for non-invasive serial sampling of tumor material. Although not yet approved for routine use in pancreatic cancer, the increasing sensitivity and specificity of contemporary liquid biopsy platforms will likely change clinical practice in the near future. In this review, we discuss the recent technological advances in liquid biopsy, focusing on circulating tumor DNA, exosomes, microRNAs, and circulating tumor cells.

Therapeutic targeting of TRAIL death receptors.

The discovery of tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) along with its potent and selective antitumor effects initiated a decades-long search for therapeutic strategies to target the TRAIL pathway. First-generation approaches were focused on the development of TRAIL receptor agonists (TRAs), including recombinant human TRAIL (rhTRAIL) and TRAIL receptor-targeted agonistic antibodies. While such TRAIL pathway-targeted therapies showed promise in preclinical data and clinical trials have been conducted, none have advanced to FDA approval. Subsequent second-generation approaches focused on improving upon the specific limitations of first-generation approaches by ameliorating the pharmacokinetic profiles and agonistic abilities of TRAs as well as through combinatorial approaches to circumvent resistance. In this review, we summarize the successes and shortcomings of first- and second-generation TRAIL pathway-based therapies, concluding with an overview of the discovery and clinical introduction of ONC201, a compound with a unique mechanism of action that represents a new generation of TRAIL pathway-based approaches. We discuss preclinical and clinical findings in different tumor types and provide a unique perspective on translational directions of the field.

Advanced Strategies for Therapeutic Targeting of Wild-Type and Mutant p53 in Cancer.

TP53 is a tumor suppressor gene that encodes a sequence-specific DNA-binding transcription factor activated by stressful stimuli; it upregulates target genes involved in growth suppression, cell death, DNA repair, metabolism, among others. TP53 is the most frequently mutated gene in tumors, with mutations not only leading to loss-of-function (LOF), but also gain-of-function (GOF) that promotes tumor progression, and metastasis. The tumor-specific status of mutant p53 protein has suggested it is a promising target for cancer therapy. We summarize the current progress of targeting wild-type and mutant p53 for cancer therapy through biotherapeutic and biopharmaceutical methods for (1) boosting p53 activity in cancer, (2) p53-dependent and p53-independent strategies for targeting p53 pathway functional restoration in p53-mutated cancer, (3) targeting p53 in immunotherapy, and (4) combination therapies targeting p53, p53 checkpoints, or mutant p53 for cancer therapy.

Colorectal cancer extracellular acidosis decreases immune cell killing and is partially ameliorated by pH-modulating agents that modify tumor cell cytokine profiles.

Tumor cells upregulate myriad proteins that are important for pH regulation, resulting in the acidification of the extracellular tumor microenvironment (TME). Abnormal pH is known to dampen immune function, resulting in a worsened anti-tumor immune response. Understanding how extrinsic alterations in pH modulate the interactions between immune cells and tumors cells will help elucidate opportunities for new therapeutic approaches. We observed that pH impacts the function of immune cells, both natural killer (NK) and T cells, which is relevant in the context of a highly acidic TME. Decreased NK and T cell activity was correlated with decreasing pH in a co-culture immune cell-mediated tumor cell-killing assay. The addition of pH-modulating drugs cariporide, lansoprazole, and acetazolamide to the co-culture assay was able to partially mitigate this dampened immune cell function. Treatment of colorectal cancer (CRC) cells with NHE1 inhibitor cariporide increased CRC cell-secreted cytokines involved in immune cell recruitment and activation and decreased cytokines involved in epithelial-mesenchymal transition (EMT). Cariporide treatment also decreased CRC cell shed TRAIL-R2, TRAIL-R3, and PD-L1 which is relevant in the context of immunotherapy. These experiments can help inform future investigations into how the pH of the tumor microenvironment may be extrinsically modulated to improve anti-tumor immune response in solid tumors such as colorectal cancer.

Insights and Strategies of Melanoma Immunotherapy: Predictive Biomarkers of Response and Resistance and Strategies to Improve Response Rates.

Despite the recent successes and durable responses with immune checkpoint inhibitors (ICI), many cancer patients, including those with melanoma, do not derive long-term benefits from ICI therapies. The lack of predictive biomarkers to stratify patients to targeted treatments has been the driver of primary treatment failure and represents an unmet medical need in melanoma and other cancers. Understanding genomic correlations with response and resistance to ICI will enhance cancer patients' benefits. Building on insights into interplay with the complex tumor microenvironment (TME), the ultimate goal should be assessing how the tumor 'instructs' the local immune system to create its privileged niche with a focus on genomic reprogramming within the TME. It is hypothesized that this genomic reprogramming determines the response to ICI. Furthermore, emerging genomic signatures of ICI response, including those related to neoantigens, antigen presentation, DNA repair, and oncogenic pathways, are gaining momentum. In addition, emerging data suggest a role for checkpoint regulators, T cell functionality, chromatin modifiers, and copy-number alterations in mediating the selective response to ICI. As such, efforts to contextualize genomic correlations with response into a more insightful understanding of tumor immune biology will help the development of novel biomarkers and therapeutic strategies to overcome ICI resistance.

Therapeutic Targeting of Autophagy in Pancreatic Ductal Adenocarcinoma.

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive disease characterized by early metastasis, late detection, and poor prognosis. Progress towards effective therapy has been slow despite significant efforts. Novel treatment approaches are desperately needed and autophagy, an evolutionary conserved process through which proteins and organelles are recycled for use as alternative energy sources, may represent one such target. Although incompletely understood, there is growing evidence suggesting that autophagy may play a role in PDAC carcinogenesis, metastasis, and survival. Early clinical trials involving autophagy inhibiting agents, either alone or in combination with chemotherapy, have been disappointing. Recently, evidence has demonstrated synergy between the MAPK pathway and autophagy inhibitors in PDAC, suggesting a promising therapeutic intervention. In addition, novel agents, such as ONC212, have preclinical activity in pancreatic cancer, in part through autophagy inhibition. We discuss autophagy in PDAC tumorigenesis, metabolism, modulation of the immune response, and preclinical and clinical data with selected autophagy modulators as therapeutics.

Therapeutic Targeting of Alternative RNA Splicing in Gastrointestinal Malignancies and Other Cancers.

Recent comprehensive genomic studies including single-cell RNA sequencing and characterization have revealed multiple processes by which protein-coding and noncoding RNA processing are dysregulated in many cancers. More specifically, the abnormal regulation of mRNA and precursor mRNA (pre-mRNA) processing, which includes the removal of introns by splicing, is frequently altered in tumors, producing multiple different isoforms and diversifying protein expression. These alterations in RNA processing result in numerous cancer-specific mRNAs and pathogenically spliced events that generate altered levels of normal proteins or proteins with new functions, leading to the activation of oncogenes or the inactivation of tumor suppressor genes. Abnormally spliced pre-mRNAs are also associated with resistance to cancer treatment, and certain cancers are highly sensitive to the pharmacological inhibition of splicing. The discovery of these alterations in RNA processing has not only provided new insights into cancer pathogenesis but identified novel therapeutic vulnerabilities and therapeutic opportunities in targeting these aberrations in various ways (e.g., small molecules, splice-switching oligonucleotides (SSOs), and protein therapies) to modulate alternative RNA splicing or other RNA processing and modification mechanisms. Some of these strategies are currently progressing toward clinical development or are already in clinical trials. Additionally, tumor-specific neoantigens produced from these pathogenically spliced events and other abnormal RNA processes provide a potentially extensive source of tumor-specific therapeutic antigens (TAs) for targeted cancer immunotherapy. Moreover, a better understanding of the molecular mechanisms associated with aberrant RNA processes and the biological impact they play might provide insights into cancer initiation, progression, and metastasis. Our goal is to highlight key alternative RNA splicing and processing mechanisms and their roles in cancer pathophysiology as well as emerging therapeutic alternative splicing targets in cancer, particularly in gastrointestinal (GI) malignancies.

Targeting the Integrated Stress Response in Cancer Therapy.

The integrated stress response (ISR) is an evolutionarily conserved intra-cellular signaling network which is activated in response to intrinsic and extrinsic stresses. Various stresses are sensed by four specialized kinases, PKR-like ER kinase (PERK), general control non-derepressible 2 (GCN2), double-stranded RNA-dependent protein kinase (PKR) and heme-regulated eIF2α kinase (HRI) that converge on phosphorylation of serine 51 of eIF2α. eIF2α phosphorylation causes a global reduction of protein synthesis and triggers the translation of specific mRNAs, including activating transcription factor 4 (ATF4). Although the ISR promotes cell survival and homeostasis, when stress is severe or prolonged the ISR signaling will shift to regulate cellular apoptosis. We review the ISR signaling pathway, regulation and importance in cancer therapy.

EZH2i EPZ-6438 and HDACi vorinostat synergize with ONC201/TIC10 to activate integrated stress response, DR5, reduce H3K27 methylation, ClpX and promote apoptosis of multiple tumor types including DIPG.

ONC201/TIC10 activates TRAIL signaling through ATF4 and the integrated stress response (ISR). ONC201 demonstrated tumor regressions and disease stability in patients with histone H3K27M-mutated midline-glioma. H3K27M-mutation prevents H3K27-methylation on the mutated allele. EZH2 inhibitors (EZH2i) reduce H3K27 methylation and have anti-tumor effects. We hypothesized ONC201 sensitivity and tumor apoptosis may increase by reducing H3K27-methylation with EZH2i or HDACi as mimics of H3K27M-mutation. EZH2i EPZ-6438 (tazemetostat) or PF-06821497 and HDACi vorinostat were combined with ONC201 to treat multiple cancer cell lines and cell viability and histone modifications were analyzed. We observed synergistic effects towards cell viability in multiple cancers by EPZ-6438 or PF-06821497 plus ONC201 or triple therapy with vorinostat, EPZ-6438, and ONC201. EPZ-6438 and vorinostat synergized with ONC201 to enhance apoptosis. Activation of the ISR and TRAIL-DR5 were observed in cells treated with ONC201 -/+ epigenetic modulators. Knockdown of ATF4 reduced DR5 induction and apoptosis following EZH2i and ONC201 treatment of U251 glioma cells. mRNA expression of dopamine-receptors did not correlate with ONC201 sensitivity in the tumor cell lines tested (N = 12), including changes after epigenetic drugs. Dopamine did not rescue apoptosis by ONC201 in different tumor cell lines (N = 10) including 2 GBM, 3 DIPG and did not prevent DR5 activation or apoptosis. DRD2 agonist sumanirole did not protect brain tumor cells (N = 6 including 4 DIPG cell lines) from ONC201 reduction in viability. Although synergy was observed with ONC201 and vorinostat, there was no significant increase in H3K27 acetylation in cell lines including DIPG as compared to vorinostat alone, and in some cases the acetylation was less than vorinostat alone at 72 H. H3K27 methylation reduction correlated with synergy from combinations of either EPZ-6438 or vorinostat with ONC201 or triple combination. Our findings provide a rationale for combination of ONC201 and epigenetic modulators including triple therapy for in vivo and clinical testing in treatment of human malignancies including brain tumors and DIPG.

ONC201 and imipridones: Anti-cancer compounds with clinical efficacy.

ONC201 was originally discovered as TNF-Related Apoptosis Inducing Ligand (TRAIL)-inducing compound TIC10. ONC201 appears to act as a selective antagonist of the G protein coupled receptor (GPCR) dopamine receptor D2 (DRD2), and as an allosteric agonist of mitochondrial protease caseinolytic protease P (ClpP). Downstream of target engagement, ONC201 activates the ATF4/CHOP-mediated integrated stress response leading to TRAIL/Death Receptor 5 (DR5) activation, inhibits oxidative phosphorylation via c-myc, and inactivates Akt/ERK signaling in tumor cells. This typically results in DR5/TRAIL-mediated apoptosis of tumor cells; however, DR5/TRAIL-independent apoptosis, cell cycle arrest, or antiproliferative effects also occur. The effects of ONC201 extend beyond bulk tumor cells to include cancer stem cells, cancer associated fibroblasts and immune cells within the tumor microenvironment that can contribute to its efficacy. ONC201 is orally administered, crosses the intact blood brain barrier, and is under evaluation in clinical trials in patients with advanced solid tumors and hematological malignancies. ONC201 has single agent clinical activity in tumor types that are enriched for DRD2 and/or ClpP expression including specific subtypes of high-grade glioma, endometrial cancer, prostate cancer, mantle cell lymphoma, and adrenal tumors. Synergy with radiation, chemotherapy, targeted therapy and immune-checkpoint agents has been identified in preclinical models and is being evaluated in clinical trials. Structure-activity relationships based on the core pharmacophore of ONC201, termed the imipridone scaffold, revealed novel potent compounds that are being developed. Imipridones represent a novel approach to therapeutically target previously undruggable GPCRs, ClpP, and innate immune pathways in oncology.

Natural Killer cell activation, reduced ACE2, TMPRSS2, cytokines G-CSF, M-CSF and SARS-CoV-2-S pseudovirus infectivity by MEK inhibitor treatment of human cells.

COVID-19 affects vulnerable populations including elderly individuals and patients with cancer. Natural Killer (NK) cells and innate-immune TRAIL suppress transformed and virally-infected cells. ACE2, and TMPRSS2 protease promote SARS-CoV-2 infectivity, while inflammatory cytokines IL-6, or G-CSF worsen COVID-19 severity. We show MEK inhibitors (MEKi) VS-6766, trametinib and selumetinib reduce ACE2 expression in human cells. In some human cells, remdesivir increases ACE2-promoter luciferase-reporter expression, ACE2 mRNA and protein, and ACE2 expression is attenuated by MEKi. In serum-deprived and stimulated cells treated with remdesivir and MEKi we observed correlations between pRB, pERK, and ACE2 expression further supporting role of proliferative state and MAPK pathway in ACE2 regulation. We show elevated cytokines in COVID-19-(+) patient plasma (N=9) versus control (N=11). TMPRSS2, inflammatory cytokines G-CSF, M-CSF, IL-1α, IL-6 and MCP-1 are suppressed by MEKi alone or with remdesivir. We observed MEKi stimulation of NK-cell killing of target-cells, without suppressing TRAIL-mediated cytotoxicity. Pseudotyped SARS-CoV-2 virus with a lentiviral core and SARS-CoV-2 D614 or G614 SPIKE (S) protein on its envelope infected human bronchial epithelial cells, small airway epithelial cells, or lung cancer cells and MEKi suppressed infectivity of the pseudovirus. We show a drug class-effect with MEKi to stimulate NK cells, inhibit inflammatory cytokines and block host-factors for SARS-CoV-2 infection leading also to suppression of SARS-CoV-2-S pseudovirus infection of human cells. MEKi may attenuate SARS-CoV-2 infection to allow immune responses and antiviral agents to control disease progression.

Novel biomarkers of a peripheral blood interferon signature associated with drug-naïve early arthritis patients distinguish persistent from self-limiting disease course.

We profiled gene expression signatures to distinguish rheumatoid arthritis (RA) from non-inflammatory arthralgia (NIA), self-limiting arthritis (SLA), and undifferentiated arthritis (UA) as compared to healthy controls as novel potential biomarkers for therapeutic responsiveness. Global gene expression profiles of PBMCs from 43 drug-naïve patients presenting with joint symptoms were evaluated and differentially expressed genes identified by comparative analysis with 24 healthy volunteers. Patients were assessed at presentation with follow up at 6 and 12 months. Gene ontology and network pathway analysis were performed using DAVID Bioinformatics Resources v6.7. Gene expression profiles were also determined after disease-modifying anti-rheumatic drug (DMARD) treatment in the inflammatory arthritis groups (i.e. RA and UA) and confirmed by qRT-PCR. Receiver operating characteristic (ROC) curves analysis and Area Under the Curve (AUC) estimation were performed to assess the diagnostic value of candidate gene expression signatures. A type I interferon (IFN) gene signature distinguished DMARD-naïve patients who will subsequently develop persistent inflammatory arthritis (i.e. RA and UA) from those with NIA. In patients with RA, the IFN signature is characterised by up-regulation of SIGLEC1 (p = 0.00597) and MS4A4A (p = 0.00000904). We also identified, EPHB2 (p = 0.000542) and PDZK1IP1 (p = 0.0206) with RA-specific gene expression profiles and elevated expression of the ST6GALNAC1 (p = 0.0023) gene in UA. ROC and AUC risk score analysis suggested that MSA4A (AUC: 0.894, 0.644, 0.720), PDZK1IP1 (AUC: 0.785, 0.806, 0.977), and EPHB2 (AUC: 0.794, 0.723, 0.620) at 0, 6, and 12 months follow-up can accurately discriminate patients with RA from healthy controls and may have practical value for RA diagnosis. In patients with early inflammatory arthritis, ST6GALNAC1 is a potential biomarker for UA as compared with healthy controls whereas EPHB2, MS4A4A, and particularly PDZK1IP1 may discriminate RA patients. SIGLEC1 may also be a useful marker of disease activity in UA.

Are innovation and new technologies in precision medicine paving a new era in patients centric care?

Healthcare is undergoing a transformation, and it is imperative to leverage new technologies to generate new data and support the advent of precision medicine (PM). Recent scientific breakthroughs and technological advancements have improved our understanding of disease pathogenesis and changed the way we diagnose and treat disease leading to more precise, predictable and powerful health care that is customized for the individual patient. Genetic, genomics, and epigenetic alterations appear to be contributing to different diseases. Deep clinical phenotyping, combined with advanced molecular phenotypic profiling, enables the construction of causal network models in which a genomic region is proposed to influence the levels of transcripts, proteins, and metabolites. Phenotypic analysis bears great importance to elucidat the pathophysiology of networks at the molecular and cellular level. Digital biomarkers (BMs) can have several applications beyond clinical trials in diagnostics-to identify patients affected by a disease or to guide treatment. Digital BMs present a big opportunity to measure clinical endpoints in a remote, objective and unbiased manner. However, the use of "omics" technologies and large sample sizes have generated massive amounts of data sets, and their analyses have become a major bottleneck requiring sophisticated computational and statistical methods. With the wealth of information for different diseases and its link to intrinsic biology, the challenge is now to turn the multi-parametric taxonomic classification of a disease into better clinical decision-making by more precisely defining a disease. As a result, the big data revolution has provided an opportunity to apply artificial intelligence (AI) and machine learning algorithms to this vast data set. The advancements in digital health opportunities have also arisen numerous questions and concerns on the future of healthcare practices in particular with what regards the reliability of AI diagnostic tools, the impact on clinical practice and vulnerability of algorithms. AI, machine learning algorithms, computational biology, and digital BMs will offer an opportunity to translate new data into actionable information thus, allowing earlier diagnosis and precise treatment options. A better understanding and cohesiveness of the different components of the knowledge network is a must to fully exploit the potential of it.

Predicting and understanding the response to short-term intensive insulin therapy in people with early type 2 diabetes.

OBJECTIVE: Short-term intensive insulin therapy (IIT) early in the course of type 2 diabetes acutely improves beta-cell function with long-lasting effects on glycemic control. However, conventional measures cannot determine which patients are better suited for IIT, and little is known about the molecular mechanisms determining response. Therefore, this study aimed to develop a model that could accurately predict the response to IIT and provide insight into molecular mechanisms driving such response in humans. METHODS: Twenty-four patients with early type 2 diabetes were assessed at baseline and four weeks after IIT, consisting of basal detemir and premeal insulin aspart. Twelve individuals had a beneficial beta-cell response to IIT (responders) and 12 did not (nonresponders). Beta-cell function was assessed by multiple methods, including Insulin Secretion-Sensitivity Index-2. MicroRNAs (miRNAs) were profiled in plasma samples before and after IIT. The response to IIT was modeled using a machine learning algorithm and potential miRNA-mediated regulatory mechanisms assessed by differential expression, correlation, and functional network analyses (FNA). RESULTS: Baseline levels of circulating miR-145-5p, miR-29c-3p, and HbA1c accurately (91.7%) predicted the response to IIT (OR = 121 [95% CI: 6.7, 2188.3]). Mechanistically, a previously described regulatory loop between miR-145-5p and miR-483-3p/5p, which controls TP53-mediated apoptosis, appears to also occur in our study population of humans with early type 2 diabetes. In addition, significant (fold change > 2, P < 0.05) longitudinal changes due to IIT in the circulating levels of miR-138-5p, miR-192-5p, miR-195-5p, miR-320b, and let-7a-5p further characterized the responder group and significantly correlated (|r| > 0.4, P < 0.05) with the changes in measures of beta-cell function and insulin sensitivity. FNA identified a network of coordinately/cooperatively regulated miRNA-targeted genes that potentially drives the IIT response through negative regulation of apoptotic processes that underlie beta cell dysfunction and concomitant positive regulation of proliferation. CONCLUSIONS: Responses to IIT in people with early type 2 diabetes are associated with characteristic miRNA signatures. This study represents a first step to identify potential responders to IIT (a current limitation in the field) and provides important insight into the pathophysiologic determinants of the reversibility of beta-cell dysfunction. ClinicalTrial.gov identifier: NCT01270789.

Elevated and Correlated Expressions of miR-24, miR-30d, miR-146a, and SFRP-4 in Human Abdominal Adipose Tissue Play a Role in Adiposity and Insulin Resistance.

OBJECTIVE: We explored the relationships among microRNAs (miRNAs) and SFRP4, as they relate to adipose tissue functions including lipolysis, glucose and glycerol turnover, and insulin sensitivity. METHODS: Abdominal adipose tissue (AbdAT) levels of thirteen microRNAs (miRNAs), SFRP4, and VEGF in lean nondiabetic subjects (n = 7), subjects with obesity (n = 5), and subjects with obesity and type 2 diabetes (T2DM) (n = 5) were measured by qPCR. Insulin sensitivity was measured by the euglycemic-hyperinsulinemic clamp. Osmium fixation and Coulter counting were used for adipocyte sizing. Data were analyzed using generalized linear models that adjusted for age, gender, and ethnicity. RESULTS: AbdAT miR-24, miR-30d, and miR-146a were elevated in subjects with obesity (P < 0.05) and T2DM (P < 0.1) and positively correlated with measures of percent body fat by DXA (rmiR.24 = 0.894, rmiR.146a = 0.883, P < 0.05), and AbdAT SFRP4 (rmiR.30 = 0.93, rmiR.146a = 0.88, P < 0.05). These three miRNAs additionally correlated among themselves (rmiR.24~miR.146a = 0.90, rmiR.30~miR.146a = 0.85, P < 0.01). CONCLUSIONS: This study suggests a novel association between the elevated levels of miRNAs miR-24, miR-30d, and miR-146a (apparently coregulated) and the level of SFRP4 transcript in AbdAT of subjects with obesity and T2DM. These molecules might be part of a regulatory loop involved in AbdAT remodeling/adiposity and systemic insulin resistance. This trial is registered with NCT00704197.

Circulating levels of miR-7, miR-152 and miR-192 respond to vitamin D supplementation in adults with prediabetes and correlate with improvements in glycemic control.

Vitamin D may play an important role in modifying the risk of type 2 diabetes. Supplementation with cholecalciferol has been shown to improve ß cell function and to attenuate the rise in glycated hemoglobin in people at high risk of diabetes. We examined whether circulating microRNAs (miRNAs) reflect disease progression and/or respond to vitamin D supplementation. We measured plasma levels of select miRNAs implicated in diabetes in people with prediabetes treated either with placebo (n=21) or 2000 U of cholecalciferol daily (n=21) for 4 months in the Calcium and Vitamin D for Diabetes Mellitus trial and compared the baseline-adjusted changes after correcting for age, body mass index, race, time of study entry (season) and baseline disposition index. Circulating levels of miR-7 (sixfold reduction, P=.01), miR-152 (1.5-fold increase, P=.03), and miR-192 (1.7-fold reduction, P=.026) displayed significant treatment-by-time interactions between the placebo- and the vitamin-D-treated groups. Plasma levels of miR-7 were reduced in the vitamin D and increased in the placebo group. The change in miR-152 positively correlated with the change in levels of the circulating metabolite 25-hydroxyvitamin D (r=0.33, P=.046) and negatively correlated with the change in glycated hemoglobin (r=-0.37, P=.024). The change in miR-192 positively correlated with the change in fasting glucose (r=0.41, P<.011). In conclusion, reduction of circulating miR-7 and miR-192, accompanied by elevation of miR-152, reflects a beneficial metabolic response to vitamin D treatment in people with prediabetes. These miRNAs may be useful biomarkers in diabetes prevention trials and other studies of vitamin D.