Exploring small non-coding RNAs as blood-based biomarkers to predict Alzheimer's disease.

BACKGROUND: Alzheimer's disease (AD) diagnosis relies on clinical symptoms complemented with biological biomarkers, the Amyloid Tau Neurodegeneration (ATN) framework. Small non-coding RNA (sncRNA) in the blood have emerged as potential predictors of AD. We identified sncRNA signatures specific to ATN and AD, and evaluated both their contribution to improving AD conversion prediction beyond ATN alone. METHODS: This nested case-control study was conducted within the ACE cohort and included MCI patients matched by sex. Patients free of type 2 diabetes underwent cerebrospinal fluid (CSF) and plasma collection and were followed-up for a median of 2.45-years. Plasma sncRNAs were profiled using small RNA-sequencing. Conditional logistic and Cox regression analyses with elastic net penalties were performed to identify sncRNA signatures for A+(T|N)+ and AD. Weighted scores were computed using cross-validation, and the association of these scores with AD risk was assessed using multivariable Cox regression models. Gene ontology (GO) and Kyoto encyclopaedia of genes and genomes (KEGG) enrichment analysis of the identified signatures were performed. RESULTS: The study sample consisted of 192 patients, including 96 A+(T|N)+ and 96 A-T-N- patients. We constructed a classification model based on a 6-miRNAs signature for ATN. The model could classify MCI patients into A-T-N- and A+(T|N)+ groups with an area under the curve of 0.7335 (95% CI, 0.7327 to 0.7342). However, the addition of the model to conventional risk factors did not improve the prediction of AD beyond the conventional model plus ATN status (C-statistic: 0.805 [95% CI, 0.758 to 0.852] compared to 0.829 [95% CI, 0.786, 0.872]). The AD-related 15-sncRNAs signature exhibited better predictive performance than the conventional model plus ATN status (C-statistic: 0.849 [95% CI, 0.808 to 0.890]). When ATN was included in this model, the prediction further improved to 0.875 (95% CI, 0.840 to 0.910). The miRNA-target interaction network and functional analysis, including GO and KEGG pathway enrichment analysis, suggested that the miRNAs in both signatures are involved in neuronal pathways associated with AD. CONCLUSIONS: The AD-related sncRNA signature holds promise in predicting AD conversion, providing insights into early AD development and potential targets for prevention.

Multiple long-term conditions in people with psoriasis: a latent class and bidirectional Mendelian randomization analysis.

BACKGROUND: Coexisting long-term conditions (LTCs) in psoriasis and their potential causal associations with the disease are not well -established. OBJECTIVES: To determine distinct clusters of LTCs in people with psoriasis and the potential bidirectional causal association between these LTCs and psoriasis. METHODS: Using latent class analysis, cross-sectional data from people with psoriasis from the UK Biobank were analysed to identify distinct psoriasis-related comorbidity profiles. Linkage disequilibrium score regression (LDSR) was applied to compute the genetic correlation between psoriasis and LTCs. Two-sample bidirectional Mendelian randomization (MR) analysis assessed the potential causal direction using independent genetic variants that reached genome-wide significance (P < 5 × 10-8). RESULTS: Five comorbidity clusters were identified in a population of 10 873 people with psoriasis. LDSR revealed that psoriasis was positively genetically correlated with heart failure [genetic correlation (rg) = 0.23, P = 8.8 × 10-8], depression (rg = 0.12, P = 2.7 × 10-5), coronary artery disease (CAD; rg = 0.15, P = 2 × 10-4) and type 2 diabetes (rg = 0.19, P = 3 × 10-3). Genetic liability to CAD was associated with an increased risk of psoriasis [inverse variance weighted (IVW) odds ratio (ORIVW) 1.159, 95% confidence interval (CI) 1.055-1.274; P = 2 × 10-3]. The MR pleiotropy residual sum and outlier (MR-PRESSO; ORMR-PRESSO 1.13, 95% CI 1.042-1.228; P = 6 × 10-3) and the MR-robust adjusted profile score (RAPS) (ORMR-RAPS 1.149, 95% CI 1.062-1.242; P = 5 × 10-4) approaches corroborate the IVW findings. The weighted median (WM) generated similar and consistent effect estimates but was not statistically significant (ORWM 1.076, 95% CI 0.949-1.221; P = 0.25). Evidence for a suggestive increased risk was detected for CAD (ORIVW 1.031, 95% CI 1.003-1.059; P = 0.03) and heart failure (ORIVW 1.019, 95% CI 1.005-1.033; P = 9 × 10-3) in those with a genetic liability to psoriasis; however, MR sensitivity analyses did not reach statistical significance. CONCLUSIONS: Five distinct clusters of psoriasis comorbidities were observed with these findings to offer opportunities for an integrated approach to comorbidity prevention and treatment. Coexisting LTCs share with psoriasis common genetic and nongenetic risk factors, and aggressive lifestyle modification in these people is anticipated to have an impact beyond psoriasis risk. Genetically predicted CAD is possibly associated with an increased risk of psoriasis, altering our prior knowledge.

Comparison of a rapid fluorescence immunochromatographic test with an enzyme-linked immunosorbent assay for measurement of SARS-CoV-2 spike protein antibody neutralizing activity.

BACKGROUND: SARS-CoV-2 Spike protein Receptor Binding Domain neutralizing antibodies (NAbs-RBD) inhibit the viral binding to angiotensin-converting enzyme 2 (ACE2) receptors. We compared an ELISA and a fluorescence immunochromatography (FIC) method in NAbs-RBD detection after COVID-19 immunization. METHOD: Serum samples from healthcare workers (HCWs) vaccinated with BNT162b2 were collected one and four months after the second dose. NAbs-RBD (%) detection was performed using ELISA cPass™ (FDA approved) and FIC n-AbCOVID-19® assays. RESULTS: Samples from 200 HCWs [median age (IQR): 45(35-53)] were tested with both assays. There was a good qualitative agreement between the two methods [AUC: 0.92(95%C.I.: 0.89-0.94, P-value:0.007)]. NAbs-RBD (%), one and four months after immunization, were significantly lower with FIC compared to ELISA for all age groups (P-value<0.0001). The quantitative comparison between FIC and ELISA detected slight agreement one month after the second dose [(Lin's Concordance Correlation Coefficient (CCC): 0.21(95%CI: 0.15-0.27)] which improved four months after the second dose [CCC: 0.6(95%CI: 0.54-0.66)]. CONCLUSION: FIC had good qualitative agreement with ELISA in the detection of positive NAbs-RBD (%) and could be an alternative for rapid NAbs-RBD (%) testing.

Mediterranean diet related metabolite profiles and cognitive performance.

BACKGROUND & AIMS: Evidence suggests that adherence to the Mediterranean diet (MedDiet) affects human metabolism and may contribute to better cognitive performance. However, the underlying mechanisms are not clear. OBJECTIVE: We generated a metabolite profile for adherence to MedDiet and evaluated its cross-sectional association with aspects of cognitive performance. METHODS: A total of 1250 healthy Greek middle-aged adults from the Epirus Health Study cohort were included in the analysis. Adherence to the MedDiet was assessed using the 14-point Mediterranean Diet Adherence Screener (MEDAS); cognition was measured using the Trail Making Test, the Verbal Fluency test and the Logical Memory test. A targeted metabolite profiling (n = 250 metabolites) approach was applied, using a high-throughput nuclear magnetic resonance platform. We used elastic net regularized regressions, with a 10-fold cross-validation procedure, to identify a metabolite profile for MEDAS. We evaluated the associations of the identified metabolite profile and MEDAS with cognitive tests, using multivariable linear regression models. RESULTS: We identified a metabolite profile composed of 42 metabolites, mainly lipoprotein subclasses and fatty acids, significantly correlated with MedDiet adherence (Pearson r = 0.35, P-value = 5.5 × 10-37). After adjusting for known risk factors and accounting for multiple testing, the metabolite profile and MEDAS were not associated with the cognitive tests. CONCLUSIONS: A plasma metabolite profile related to better adherence to the MedDiet was not associated with the tested aspects of cognitive performance, in a middle-aged Mediterranean population.

The Effect of Commonly Used Fixed-Dose Single Pill Combinations of Renin-Angiotensin-System Blockers and Calcium Channel Blockers on HOMA-IR Index in Hypertensive Patients with Impaired Fasting Glucose: a 12-Week Randomized Open-Label Prospective Study.

Backround: The effect of antihypertensive drugs on glucose homeostasis and insulin resistance remains an issue under investigation. There is evidence that renin-angiotensin system (RAS) blockers may favorably affect glucose metabolism, while treatment with calcium channel blockers (CCBs) is considered to have an overall neutral metabolic effect. However, the effects on glycemic indices may differ among agents within the same class of antihypertensive drugs. Objective: To evaluate the effects of different fixed-dose single pill combinations of RAS blockers with CCBs on homeostatic model assessment for insulin resistance (HOMA-IR). Methods:Drug-naive patients with arterial hypertension (AH) and impaired fasting glucose (IFG) were randomly allocated to open-label fixed, single pill combinations of valsartan 160 mg/day plus amlodipine 5 mg/day (VAL/AMLO group, n = 54), delapril 30 mg/day and manidipine 10 mg/day (DEL/MANI group, n = 53) or telmisartan 80 mg/day and amlodipine 5 mg/day (TEL/AMLO group, n = 51) for 12 weeks. Glycemic indices and HOMA-IR were determined at baseline and post-treatment. Results:A total of 158 patients were included. All treatment combinations effectively reduced blood pressure (systolic and diastolic) to similar levels (all p < 0.001). A decrease in the HOMA-IR index by 22.55% (p <0.01) was noted following treatment with TEL/AMLO, while an increase by 1.4% (p = 0.57) and 12.65% (p = 0.072) was observed in the VAL/AMLO group and the DEL/MANI group, respectively. These changes were significantly different between TEL/AMLO and DEL/MANI (p < 0.05) as well as between TEL/AMLO and VAL/AMLO (p < 0.001). Conclusion:Despite similar antihypertensive action, the effect of fixed, single pill combinations with TEL/AMLO, VAL/AMLO and DEL/MANI on insulin resistance is in favor of TEL/AMLO. Trial registration: The study protocol was published online in https://diavgeia.gov.gr/ (No: ÂÈ6Ó46906Ç-ÁÅÓ) via the Ministry of Digital Governance, after receiving approval from the Scientific Council and Administrative Council of University Hospital of Ioannina (No. of approval: 1/12-06-2014 (issue 150). https://diavgeia.gov.gr/decision/view/%CE%92%CE%986%CE%A346906%CE%97- %CE%91%CE%95%CE%A3 h t t p s : / / d i a v g e i a . g o v . g r / d o c / % C E % 9 2 % C E % 9 8 6 % C E % A 3 4 6 9 0 6 % C E % 9 7 - %CE%91%CE%95%CE%A3?inline=true.

Cost-consequence of abatacept as first-line therapy in Japanese rheumatoid arthritis patients using IORRA real-world data.

OBJECTIVES: To investigate the cost-effectiveness of abatacept (ABA) as first-line (1L) therapy in Japanese rheumatoid arthritis (RA) patients using data from the Institute of Rheumatology, Rheumatoid Arthritis database. METHODS: A decision-analytic model was used to estimate the cost per American College of Rheumatology response of at least 50% improvement (ACR50) responder and per patient in Clinical Disease Activity Index (CDAI) and Simplified Disease Activity Index (SDAI) remission from a Japanese healthcare payers' perspective over a 2-year time horizon. Clinical characteristics of patients on ABA-1L were matched with those of patients on ABA second or later line (2L+) or tumour necrosis factor inhibitor (TNFi)-1L directly or using propensity scores. Resource utilisation and medical costs were calculated from the Japan Medical Data Center claims database. Parameter uncertainty was addressed by sensitivity and subgroup analyses (age, treatment duration, Japanese version of Health Assessment Questionnaire [J-HAQ] score). RESULTS: Incremental costs per member per month (ΔPMPM) for ABA-1L versus TNFi-1L and ABA-2L+ were -1,571 Japanese Yen (JPY) and 81 JPY, respectively. For ABA-1L versus TNFi-1L, ΔPMPM by ACR50 response was -11,715 JPY and by CDAI and SDAI remission 11,602 JPY and 47,003 JPY, respectively. Corresponding costs for ABA-1L were lower for all outcome parameters versus those for ABA-2L+. Scenario analyses showed that ABA-1L was cost-effective over TNFi-1L in patients <65 years for any outcome. Furthermore, ABA-1L was cost-effective over ABA-2L+ for all outcomes in patients with age <65 years, disease duration <5 years and J-HAQ ≥1.5. CONCLUSIONS: ABA-1L demonstrated a favourable cost-effectiveness profile in RA patients, accruing savings for the Japanese healthcare payers.

SARS-CoV-2 seroepidemiology in paediatric population during Delta and Omicron predominance.

Limited prospective severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) data in children regarding the impact of Omicron variant in seropositivity have been reported. We investigated SARS-CoV-2 seropositivity in children between 1 September 2021 and 30 April 2022, representing Delta and Omicron predominance periods. Serum samples from children admitted to the major tertiary Greek paediatric hospital for any cause, except for COVID-19, were randomly collected and tested for SARS-CoV-2 natural infection antibodies against nucleocapsid antigen (Elecsys® Anti-SARS-CoV-2 reagent). A total of 506/1312 (38.6%) seropositive children (0-16 years) were detected (males: 261/506(51.6%); median age (IQR): 95.2 months(24-144)). Seropositivity rates (%) increased from Delta to Omicron period from 29.7% to 48.5% (P-value<0.0001). Seropositivity increased for all age groups, except for the age group of 0-1 year (P-value:0.914). The highest seropositivity rate was detected in April 2022 (52.6%) and reached 73.9% specifically for the age group 12-16 years. No significant differences were detected in seropositivity with respect to gender, origin, or hospitalisation status. Median (IQR) antibody titres were higher in the Omicron vs. Delta period in all age groups, especially in 12-16 years [32.2 COI (7-77.1) vs. 11.4 COI(2.8-50.2), P-value:0.009). During Omicron variant period increased SARS-CoV-2 seropositivity was detected in paediatric population, especially in adolescents, implicating either increased transmissibility or reinfection rates.

Efficacy and safety of first-line therapies in EGFR-mutated advanced non-small-cell lung cancer: a network meta-analysis.

Aim: To evaluate the comparative efficacy and safety of identified first-line therapies for patients with EGFR mutation-positive (EGFRm+) advanced non-small-cell lung cancer (NSCLC), with a focus on ramucirumab + erlotinib. Methods: In the absence of head-to-head studies, a Bayesian network meta-analysis was conducted using randomized clinical trial data to evaluate first-line systemic therapies with erlotinib/gefitinib as the reference treatment. Results: For progression-free survival, ramucirumab + erlotinib was comparable to osimertinib and dacomitinib in the primary analysis. Conclusion: The analysis showed ramucirumab + erlotinib efficacy to be comparable to best-in-class treatment options for previously untreated patients with EGFRm+ advanced NSCLC. Registration information: PROSPERO ID: CRD42020136247.

Invariable Ribosome Stoichiometry During Murine Erythroid Differentiation: Implications for Understanding Ribosomopathies.

Heterogeneity of the main ribosomal composition represents an emerging, yet debatable, mechanism of gene expression regulation with a purported role in ribosomopathies, a group of disorders caused by mutations in ribosomal protein genes (RPs). Ribosomopathies, mysteriously relate with tissue-specific symptoms (mainly anemia and cancer predisposition), despite the ubiquitous expression and necessity of the associated RPs. An outstanding question that may shed light into disease pathogenicity and provide potential pharmacological interventions, is whether and how the ribosomal composition is modified during, the highly affected by RP mutations, process of erythroid differentiation. To address this issue, we analyzed ribosome stoichiometry using an established model of erythroid differentiation, through sucrose gradient ultracentrifugation and quantitative proteomics. We found that differentiation associates with an extensive reprogramming of the overall ribosomal levels, characterized by an increase in monosomes and a decrease in polysomes. However, by calculating a stoichiometry score for each independent ribosomal protein, we found that the main ribosomal architecture remained invariable between immature and differentiated cells. In total, none of the 78 Ribosomal Proteins (RPs- 74 core RPs, Rack1, Fau and 2 paralogs) detected was statistically different between the samples. This data was further verified through antibody-mediated quantification of 6 representative RPs. Moreover, bioinformatic analysis of whole cell proteomic data derived out of 4 additional models of erythropoiesis revealed that RPs were co-regulated across these cell types, too. In conclusion, ribosomes maintain an invariant protein stoichiometry during differentiation, thus excluding ribosome heterogeneity from a potential mechanism of toxicity in ribosomopathies and other erythroid disorders.

Dissecting miRNA-Gene Networks to Map Clinical Utility Roads of Pharmacogenomics-Guided Therapeutic Decisions in Cardiovascular Precision Medicine.

MicroRNAs (miRNAs) create systems networks and gene-expression circuits through molecular signaling and cell interactions that contribute to health imbalance and the emergence of cardiovascular disorders (CVDs). Because the clinical phenotypes of CVD patients present a diversity in their pathophysiology and heterogeneity at the molecular level, it is essential to establish genomic signatures to delineate multifactorial correlations, and to unveil the variability seen in therapeutic intervention outcomes. The clinically validated miRNA biomarkers, along with the relevant SNPs identified, have to be suitably implemented in the clinical setting in order to enhance patient stratification capacity, to contribute to a better understanding of the underlying pathophysiological mechanisms, to guide the selection of innovative therapeutic schemes, and to identify innovative drugs and delivery systems. In this article, the miRNA-gene networks and the genomic signatures resulting from the SNPs will be analyzed as a method of highlighting specific gene-signaling circuits as sources of molecular knowledge which is relevant to CVDs. In concordance with this concept, and as a case study, the design of the clinical trial GESS (NCT03150680) is referenced. The latter is presented in a manner to provide a direction for the improvement of the implementation of pharmacogenomics and precision cardiovascular medicine trials.

FOXO1 controls protein synthesis and transcript abundance of mutant polyglutamine proteins, preventing protein aggregation.

FOXO1, a transcription factor downstream of the insulin/insulin like growth factor axis, has been linked to protein degradation. Elevated expression of FOXO orthologs can also prevent the aggregation of cytosine adenine guanine (CAG)-repeat disease causing polyglutamine (polyQ) proteins but whether FOXO1 targets mutant proteins for degradation is unclear. Here, we show that increased expression of FOXO1 prevents toxic polyQ aggregation in human cells while reducing FOXO1 levels has the opposite effect and accelerates it. Although FOXO1 indeed stimulates autophagy, its effect on polyQ aggregation is independent of autophagy, ubiquitin-proteasome system (UPS) mediated protein degradation and is not due to a change in mutant polyQ protein turnover. Instead, FOXO1 specifically downregulates protein synthesis rates from expanded pathogenic CAG repeat transcripts. FOXO1 orchestrates a change in the composition of proteins that occupy mutant expanded CAG transcripts, including the recruitment of IGF2BP3. This mRNA binding protein enables a FOXO1 driven decrease in pathogenic expanded CAG transcript- and protein levels, thereby reducing the initiation of amyloidogenesis. Our data thus demonstrate that FOXO1 not only preserves protein homeostasis at multiple levels, but also reduces the accumulation of aberrant RNA species that may co-contribute to the toxicity in CAG-repeat diseases.

miR-16-5p Promotes Erythroid Maturation of Erythroleukemia Cells by Regulating Ribosome Biogenesis.

miRNAs constitute a class of non-coding RNA that act as powerful epigenetic regulators in animal and plant cells. In order to identify putative tumor-suppressor miRNAs we profiled the expression of various miRNAs during differentiation of erythroleukemia cells. RNA was purified before and after differentiation induction and subjected to quantitative RT-PCR. The majority of the miRNAs tested were found upregulated in differentiated cells with miR-16-5p showing the most significant increase. Functional studies using gain- and loss-of-function constructs proposed that miR-16-5p has a role in promoting the erythroid differentiation program of murine erythroleukemia (MEL) cells. In order to identify the underlying mechanism of action, we utilized bioinformatic in-silico platforms that incorporate predictions for the genes targeted by miR-16-5p. Interestingly, ribosome constituents, as well as ribosome biogenesis factors, were overrepresented among the miR-16-5p predicted gene targets. Accordingly, biochemical experiments showed that, indeed, miR-16-5p could modulate the levels of independent ribosomal proteins, and the overall ribosomal levels in cultured cells. In conclusion, miR-16-5p is identified as a differentiation-promoting agent in erythroleukemia cells, demonstrating antiproliferative activity, likely as a result of its ability to target the ribosomal machinery and restore any imbalanced activity imposed by the malignancy and the blockade of differentiation.

The histone methyltransferase inhibitor A-366 enhances hemoglobin expression in erythroleukemia cells upon co-exposure with chemical inducers in culture.

BACKGROUND: Erythroleukemia is caused by the uncontrolled multiplication of immature erythroid progenitor cells which fail to differentiate into erythrocytes. By directly targeting this class of malignant cells, the induction of terminal erythroid differentiation represents a vital therapeutic strategy for this disease. Erythroid differentiation involves the execution of a well-orchestrated gene expression program in which epigenetic enzymes play critical roles. In order to identify novel epigenetic mediators of differentiation, this study explores the effects of multiple, highly specific, epigenetic enzyme inhibitors, in murine and human erythroleukemia cell lines. RESULTS: We used a group of compounds designed to uniquely target the following epigenetic enzymes: G9a/GLP, EZH1/2, SMYD2, PRMT3, WDR5, SETD7, SUV420H1 and DOT1L. The majority of the probes had a negative impact on both cell proliferation and differentiation. On the contrary, one of the compounds, A-366, demonstrated the opposite effect by promoting erythroid differentiation of both cell models. A-366 is a selective inhibitor of the G9a methyltransferase and the chromatin reader Spindlin1. Investigation of the molecular mechanism of action revealed that A-366 forced cells to exit from the cell cycle, a fact that favored erythroid differentiation. Further analysis led to the identification of a group of genes that mediate the A-366 effects and include CDK2, CDK4 and CDK6. CONCLUSIONS: A-366, a selective inhibitor of G9a and Spindlin1, demonstrates a compelling role in the erythroid maturation process by promoting differentiation, a fact that is highly beneficial for patients suffering from erythroleukemia. In conclusion, this data calls for further investigation towards the delivery of epigenetic drugs and especially A-366 in hematopoietic disorders.

A Risk-Stratification Machine Learning Framework for the Prediction of Coronary Artery Disease Severity: Insights From the GESS Trial.

Our study aims to develop a data-driven framework utilizing heterogenous electronic medical and clinical records and advanced Machine Learning (ML) approaches for: (i) the identification of critical risk factors affecting the complexity of Coronary Artery Disease (CAD), as assessed via the SYNTAX score; and (ii) the development of ML prediction models for accurate estimation of the expected SYNTAX score. We propose a two-part modeling technique separating the process into two distinct phases: (a) a binary classification task for predicting, whether a patient is more likely to present with a non-zero SYNTAX score; and (b) a regression task to predict the expected SYNTAX score accountable to individual patients with a non-zero SYNTAX score. The framework is based on data collected from the GESS trial (NCT03150680) comprising electronic medical and clinical records for 303 adult patients with suspected CAD, having undergone invasive coronary angiography in AHEPA University Hospital of Thessaloniki, Greece. The deployment of the proposed approach demonstrated that atherogenic index of plasma levels, diabetes mellitus and hypertension can be considered as important risk factors for discriminating patients into zero- and non-zero SYNTAX score groups, whereas diastolic and systolic arterial blood pressure, peripheral vascular disease and body mass index can be considered as significant risk factors for providing an accurate estimation of the expected SYNTAX score, given that a patient belongs to the non-zero SYNTAX score group. The experimental findings utilizing the identified set of important risk factors indicate a sufficient prediction performance for the Support Vector Machine model (classification task) with an F-measure score of ~0.71 and the Support Vector Regression model (regression task) with a median absolute error value of ~6.5. The proposed data-driven framework described herein present evidence of the prediction capacity and the potential clinical usefulness of the developed risk-stratification models. However, further experimentation in a larger clinical setting is needed to ensure the practical utility of the presented models in a way to contribute to a more personalized management and counseling of CAD patients.

Pharmacogenomic Testing to Guide Personalized Cancer Medicine Decisions in Private Oncology Practice: A Case Study.

Innovative tumor profiling methodologies are utilized to elucidate the pharmacogenomic landscape of tumor cells in order to support the molecularly guided delivery of therapeutics. Indeed, improved clinical outcomes are achieved in oncology practice by providing the physicians with expert-guided, standardized, and easily interpretable knowledge, translated from molecular profiling analysis to support clinical decision-making. However, there is still limited utilization of the technology especially in small private oncology practices. In this work, we analyzed how molecularly guided interventions in 17 consented cancer patients led to an overall improvement of disease response rates in a private oncology center. The precision medicine strategy was based on the OncoDEEP™ profiling solutions and focused on finding clinically actionable relationships between tumor biomarkers and drug responses. The obtained data support the notion that (a) following the pharmacogenomic-derived recommendations favorably impacted cancer therapy progression, and (b) the earlier profiling followed by the delivery of molecularly targeted therapy led to more durable and improved pharmacological response rates. Moreover, we report the example of a patient with metastatic gastric adenocarcinoma who, based on the molecular profiling data, received an off-label therapy that resulted in a complete response and a current cancer-free maintenance status. Overall, our data provide a paradigm on how molecular tumor profiling can improve decision-making in the routine private oncology practice.