Temporal trends and regional variability in BRAF and KRAS genetic testing in Denmark (2010-2022): Implications for precision medicine.

OBJECTIVE: This study aims to evaluate the developments in the testing of Kirsten Rat Sarcoma viral oncogene homolog (KRAS) and v-Raf murine sarcoma viral oncogene homolog B1 (BRAF) mutations across different cancer types and regions in Denmark from 2010 to 2022. STUDY DESIGN AND SETTING: Using comprehensive data from the Danish health registries, we linked molecular test results from the Danish Pathology Registry with cancer diagnoses from the Danish National Patient Registry between 2010 and 2022. We assessed the frequency and distribution of KRAS and BRAF mutations across all cancer types, years of testing, and the five Danish regions. RESULTS: The study included records of KRAS testing for 30 671 patients and BRAF testing for 30 860 patients. Most KRAS testing was performed in colorectal (78%) and lung cancer (18%), and BRAF testing in malignant melanoma (13%), colorectal cancer (67%), and lung cancer (12%). Testing rates and documentation mutational subtypes increased over time. Reporting of wildtype results varied between lung and colorectal cancer, with underreporting in lung cancer. Regional variations in testing and reporting were observed. CONCLUSION: Our study highlights substantial progress in KRAS and BRAF testing in Denmark from 2010 to 2022, evidenced by increased and more specific reporting of mutational test results, thereby improving the precision of cancer diagnosis and treatment. However, persistent regional variations and limited testing for cancer types beyond melanoma, colorectal, and lung cancer highlight the necessity for a nationwide assessment of the optimal testing approach.

Gut metabolome and microbiota signatures predict response to treatment with exclusive enteral nutrition in a prospective study in children with active Crohn's disease.

BACKGROUND: Predicting response to exclusive enteral nutrition (EEN) in active Crohn's disease (CD) could lead to therapy personalization and pretreatment optimization. OBJECTIVES: This study aimed to explore the ability of pretreatment parameters to predict fecal calprotectin (FCal) levels at EEN completion in a prospective study in children with CD. METHODS: In children with active CD, clinical parameters, dietary intake, cytokines, inflammation-related blood proteomics, and diet-related metabolites, metabolomics and microbiota in feces, were measured before initiation of 8 wk of EEN. Prediction of FCal levels at EEN completion was performed using machine learning. Data are presented with medians (IQR). RESULTS: Of 37 patients recruited, 15 responded (FCal < 250 µg/g) to EEN (responders) and 22 did not (nonresponders). Clinical and immunological parameters were not associated with response to EEN. Responders had lesser (µmol/g) butyrate [responders: 13.2 (8.63-18.4) compared with nonresponders: 22.3 (12.0-32.0); P = 0.03], acetate [responders: 49.9 (46.4-68.4) compared with nonresponders: 70.4 (57.0-95.5); P = 0.027], phenylacetate [responders: 0.175 (0.013-0.611) compared with nonresponders: 0.943 (0.438-1.35); P = 0.021], and a higher microbiota richness [315 (269-347) compared with nonresponders: 243 (205-297); P = 0.015] in feces than nonresponders. Responders consumed (portions/1000 kcal/d) more confectionery products [responders: 0.55 (0.38-0.72) compared with nonresponders: 0.19 (0.01-0.38); P = 0.045]. A multicomponent model using fecal parameters, dietary data, and clinical and immunological parameters predicted response to EEN with 78% accuracy (sensitivity: 80%; specificity: 77%; positive predictive value: 71%; negative predictive value: 85%). Higher taxon abundance from Ruminococcaceae, Lachnospiraceae, and Bacteroides and phenylacetate, butyrate, and acetate were the most influential variables in predicting lack of response to EEN. CONCLUSIONS: We identify microbial signals and diet-related metabolites in feces, which could comprise targets for pretreatment optimization and personalized nutritional therapy in pediatric CD.

Precision medicine in colorectal cancer: Leveraging multi-omics, spatial omics, and artificial intelligence.

Colorectal cancer (CRC) is a leading cause of cancer-related deaths. Recent advancements in genomic technologies and analytical approaches have revolutionized CRC research, enabling precision medicine. This review highlights the integration of multi-omics, spatial omics, and artificial intelligence (AI) in advancing precision medicine for CRC. Multi-omics approaches have uncovered molecular mechanisms driving CRC progression, while spatial omics have provided insights into the spatial heterogeneity of gene expression in CRC tissues. AI techniques have been utilized to analyze complex datasets, identify new treatment targets, and enhance diagnosis and prognosis. Despite the tumor's heterogeneity and genetic and epigenetic complexity, the fusion of multi-omics, spatial omics, and AI shows the potential to overcome these challenges and advance precision medicine in CRC. The future lies in integrating these technologies to provide deeper insights and enable personalized therapies for CRC patients.

Mitochondrial calcium uniporter as biomarker and therapeutic target for breast cancer: Prognostication, immune microenvironment, epigenetic regulation and precision medicine.

INTRODUCTION: Mitochondrial calcium uniporter (MCU) is a central subunit of MCU complex that regulate the levels of calcium ions within mitochondria. A comprehensive understanding the implications of MCU in clinical prognostication, biological understandings and therapeutic opportunity of breast cancer (BC) is yet to be determined. OBJECTIVES: This study aims to investigate the role of MCU in predictive performance, tumor progression, epigenetic regulation, shaping of tumor immune microenvironment, and pharmacogenetics and the development of anti-tumor therapy for BC. METHODS: The downloaded TCGA datasets were used to identify predictive ability of MCU expressions via supervised learning principle. Functional enrichment, mutation landscape, immunological profile, drug sensitivity were examined using bioinformatics analysis and confirmed by experiments exploiting human specimens, in vitro and in vivo models. RESULTS: MCU copy numbers increase with MCU gene expression. MCU expression, but not MCU genetic alterations, had a positive correlation with known BC prognostic markers. Higher MCU levels in BC showed modest efficacy in predicting overall survival. In addition, high MCU expression was associated with known BC prognostic markers and with malignancy. In BC tumor and sgRNA-treated cell lines, enrichment pathways identified the involvement of cell cycle and immunity. miR-29a was recognized as a negative epigenetic regulator of MCU. High MCU levels were associated with increased mutation levels in oncogene TP53 and tumor suppression gene CDH1, as well as with an immunosuppressive microenvironment. Sigle-cell sequencing indicated that MCU mostly mapped on to tumor cell and CD8 T-cells. Inter-databases verification further confirmed the aforementioned observation. miR-29a-mediated knockdown of MCU resulted in tumor suppression and mitochondrial dysfunction, as well as diminished metastasis. Furthermore, MCU present pharmacogenetic significance in cellular docetaxel sensitivity and in prediction of patients' response to chemotherapeutic regimen. CONCLUSION: MCU shows significant implication in prognosis, outcome prediction, microenvironmental shaping and precision medicine for BC. miR-29a-mediated MCU inhibition exerts therapeutic effect in tumor growth and metastasis.

Clinical impact of panel gene sequencing on therapy of advanced cancers of the digestive system: a retrospective, single center study.

BACKGROUND: Panel gene sequencing is an established diagnostic tool for precision oncology of solid tumors, but its utility for the treatment of cancers of the digestive system in clinical routine is less well documented. METHODS: We retrospectively identified patients with advanced or metastatic gastrointestinal, pancreaticobiliary or hepatic cancers who received panel gene sequencing at a tertiary university hospital from 2015 to 2022. For these cases, we determined the spectrum of genetic alterations, clinicopathological parameters and treatment courses. Assessment of actionability of genetic alterations was based on the OncoKB database, cancer-specific ESMO treatment guidelines, and recommendations of the local molecular tumor board. RESULTS: In total, 155 patients received panel gene sequencing using either the Oncomine Focus (62 cases), Comprehensive (91 cases) or Childhood Cancer Research Assay (2 cases). The mean age of patients was 61 years (range 24-90) and 37% were female. Most patients suffered from either colorectal cancer (53%) or cholangiocellular carcinoma (19%). 327 genetic alterations were discovered in 123 tumor samples, with an average number of 2.1 alterations per tumor. The most frequently altered genes were TP53, KRAS and PIK3CA. Actionable gene alterations were detected in 13.5-56.8% of tumors, according to ESMO guidelines or the OncoKB database, respectively. Thirteen patients were treated with targeted therapies based on identified molecular alterations, with a median progression-free survival of 8.8 months. CONCLUSIONS: Actionable genetic alterations are frequently detected by panel gene sequencing in patients with advanced cancers of the digestive tract, providing clinical benefit in selected cases. However, for the majority of identified actionable alterations, sufficient clinical evidence for targeted treatments is still lacking.

Integrating decision modeling and machine learning to inform treatment stratification.

There is increasing interest in moving away from "one size fits all (OSFA)" approaches toward stratifying treatment decisions. Understanding how expected effectiveness and cost-effectiveness varies with patient covariates is a key aspect of stratified decision making. Recently proposed machine learning (ML) methods can learn heterogeneity in outcomes without pre-specifying subgroups or functional forms, enabling the construction of decision rules ('policies') that map individual covariates into a treatment decision. However, these methods do not yet integrate ML estimates into a decision modeling framework in order to reflect long-term policy-relevant outcomes and synthesize information from multiple sources. In this paper, we propose a method to integrate ML and decision modeling, when individual patient data is available to estimate treatment-specific survival time. We also propose a novel implementation of policy tree algorithms to define subgroups using decision model output. We demonstrate these methods using the SPRINT (Systolic Blood Pressure Intervention Trial), comparing outcomes for "standard" and "intensive" blood pressure targets. We find that including ML into a decision model can impact the estimate of incremental net health benefit (INHB) for OSFA policies. We also find evidence that stratifying treatment using subgroups defined by a tree-based algorithm can increase the estimates of the INHB.

Implementing Meta-Session Autoregulation Strategies for Exercise - A Scoping Review.

Meta-session autoregulation, a person-adaptive form of exercise prescription that adjusts training variables according to daily fluctuations in performance considering an individual's daily fitness, fatigue, and readiness-to-exercise is commonly used in sports-related training and may be beneficial for non-athlete populations to promote exercise adherence. To guide refinement of meta-session autoregulation, it is crucial to examine the existing literature and synthesize how these procedures have been practically implemented. Following PRIMSA guidelines a scoping review of two databases was conducted from August 2021 to September 2021 to identify and summarize the selected measures of readiness-to-exercise and decision-making processes used to match workload to participants in meta-session autoregulatory strategies, while also evaluating the methodological quality of existing study designs using a validated checklist. Eleven studies reported utilizing a form of meta-session autoregulation for exercise. Primary findings include: (i) readiness-to-exercise measures have been divided into either objective or subjective measures, (ii) measures of subjective readiness measures lacked evidence of validity, and (iii) fidelity to autoregulatory strategies was not reported. Results of the risk of bias assessment indicated that 45% of the studies had a poor-quality score. Existing implementations of meta-session autoregulation are not directly translatable for use in health promotion and disease prevention settings. Considerable refinement research is required to optimize this person-adaptive strategy prior to estimating effects related to exercise adherence and/or health and fitness outcomes. Based on the methodological deficits uncovered, researchers implementing autoregulation strategies would benefit reviewing existing models and frameworks created to guide behavioral intervention development.

From understanding to action: Exploring molecular connections of Down syndrome to Alzheimer's disease for targeted therapeutic approach.

Down syndrome (DS) is caused by a third copy of chromosome 21. Alzheimer's disease (AD) is a neurodegenerative condition characterized by the deposition of amyloid-beta (Aß) plaques and neurofibrillary tangles in the brain. Both disorders have elevated Aß, tau, dysregulated immune response, and inflammation. In people with DS, Hsa21 genes like APP and DYRK1A are overexpressed, causing an accumulation of amyloid and neurofibrillary tangles, and potentially contributing to an increased risk of AD. As a result, people with DS are a key demographic for research into AD therapeutics and prevention. The molecular links between DS and AD shed insights into the underlying causes of both diseases and highlight potential therapeutic targets. Also, using biomarkers for early diagnosis and treatment monitoring is an active area of research, and genetic screening for high-risk individuals may enable earlier intervention. Finally, the fundamental mechanistic parallels between DS and AD emphasize the necessity for continued research into effective treatments and prevention measures for DS patients at risk for AD. Genetic screening with customized therapy approaches may help the DS population in current clinical studies and future biomarkers.

The potential role of precision medicine to alleviate racial disparities in prostate, bladder and renal urological cancer care.

Background: Racial disparities in oncological outcomes resulting from differences in social determinants of health (SDOH) and tumour biology are well described in prostate cancer (PCa) but similar inequities exist in bladder (BCa) and renal cancers (RCCs). Precision medicine (PM) aims to provide personalized treatment based on individual patient characteristics and has the potential to reduce these inequities in GU cancers. Objective: This article aims to review the current evidence outlining racial disparities in GU cancers and explore studies demonstrating improved oncological outcomes when PM is applied to racially diverse patient populations. Evidence acquisition: Evidence was obtained from Pubmed and Web of Science using keywords prostate, bladder and renal cancer, racial disparity and precision medicine. Because limited studies were found, preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines were not applied but rather related articles were studied to explore existing debates, identify the current status and speculate on future applications. Results: Evidence suggests addressing SDOH for PCa can reverse racial inequities in oncological outcomes but differences in incidence remain. Similar disparities in BCa and RCC are seen, and it would be reasonable to suggest achieving parity in SDOH for all races would do the same. Research applying a PM approach to different ethnicities is lacking although in African Americans (AAs) with metastatic castrate-resistant prostate cancer (mCRPCa) better outcomes have been shown with androgen receptor inhibitors, radium-223 and sipuleucel. Exploiting the abscopal effect with targeted radiation therapy (RT) and immunotherapy has promise but requires further study, as does defining actionable mutations in specific patient groups to tailor treatments as appropriate. Conclusion: For all GU cancers, the historical underrepresentation of ethnic minorities in clinical trials still exists and there is an urgent need for recruitment strategies to address this. PM is a promising development with the potential to reduce inequities in GU cancers, however, both improved understanding of race-specific tumour biology, and enhanced recruitment of minority populations into clinical trials are required. Without this, the benefits of PM will be limited.

Blood-Based Multiomics-Guided Detection of a Precancerous Pancreatic Tumor.

Over a decade ago, longitudinal multiomics analysis was pioneered for early disease detection and individually tailored precision health interventions. However, high sample processing costs, expansive multiomics measurements along with complex data analysis have made this approach to precision/personalized medicine impractical. Here we describe in a case report, a more practical approach that uses fewer measurements, annual sampling, and faster decision making. We also show how this approach offers promise to detect an exceedingly rare and potentially fatal condition before it fully manifests. Specifically, we describe in the present case report how longitudinal multiomics monitoring (LMOM) helped detect a precancerous pancreatic tumor and led to a successful surgical intervention. The patient, enrolled in an annual blood-based LMOM since 2018, had dramatic changes in the June 2021 and 2022 annual metabolomics and proteomics results that prompted further clinical diagnostic testing for pancreatic cancer. Using abdominal magnetic resonance imaging, a 2.6 cm lesion in the tail of the patient's pancreas was detected. The tumor fluid from an aspiration biopsy had 10,000 times that of normal carcinoembryonic antigen levels. After the tumor was surgically resected, histopathological findings confirmed it was a precancerous pancreatic tumor. Postoperative omics testing indicated that most metabolite and protein levels returned to patient's 2018 levels. This case report illustrates the potentials of blood LMOM for precision/personalized medicine, and new ways of thinking medical innovation for a potentially life-saving early diagnosis of pancreatic cancer. Blood LMOM warrants future programmatic translational research with the goals of precision medicine, and individually tailored cancer diagnoses and treatments.

The emergence of highly resistant and hypervirulent Klebsiella pneumoniae CC14 clone in a tertiary hospital over 8 years.

BACKGROUND: Klebsiella pneumoniae is a major bacterial and opportunistic human pathogen, increasingly recognized as a healthcare burden globally. The convergence of resistance and virulence in K. pneumoniae strains has led to the formation of hypervirulent and multidrug-resistant strains with dual risk, limiting treatment options. K. pneumoniae clones are known to emerge locally and spread globally. Therefore, an understanding of the dynamics and evolution of the emerging strains in hospitals is warranted to prevent future outbreaks. METHODS: In this study, we conducted an in-depth genomic analysis on a large-scale collection of 328 multidrug-resistant (MDR) K. pneumoniae strains recovered from 239 patients from a single major hospital in the western coastal city of Jeddah in Saudi Arabia from 2014 through 2022. We employed a broad range of phylogenetic and phylodynamic methods to understand the evolution of the predominant clones on epidemiological time scales, virulence and resistance determinants, and their dynamics. We also integrated the genomic data with detailed electronic health record (EHR) data for the patients to understand the clinical implications of the resistance and virulence of different strains. RESULTS: We discovered a diverse population underlying the infections, with most strains belonging to Clonal Complex 14 (CC14) exhibiting dominance. Specifically, we observed the emergence and continuous expansion of strains belonging to the dominant ST2096 in the CC14 clade across hospital wards in recent years. These strains acquired resistance mutations against colistin and extended spectrum ß-lactamase (ESBL) and carbapenemase genes, namely blaOXA-48 and blaOXA-232, located on three distinct plasmids, on epidemiological time scales. Strains of ST2096 exhibited a high virulence level with the presence of the siderophore aerobactin (iuc) locus situated on the same mosaic plasmid as the ESBL gene. Integration of ST2096 with EHR data confirmed the significant link between colonization by ST2096 and the diagnosis of sepsis and elevated in-hospital mortality (p-value < 0.05). CONCLUSIONS: Overall, these results demonstrate the clinical significance of ST2096 clones and illustrate the rapid evolution of an emerging hypervirulent and MDR K. pneumoniae in a clinical setting.

The impact of rare cancer and early-line treatments on the benefit of comprehensive genome profiling-based precision oncology.

BACKGROUND: Comprehensive genome profiling (CGP) serves as a guide for suitable genomically matched therapies for patients with cancer. However, little is known about the impact of the timing and types of cancer on the therapeutic benefit of CGP. MATERIALS AND METHODS: A single hospital-based pan-cancer prospective study (TOP-GEAR; UMIN000011141) was conducted to examine the benefit of CGP with respect to the timing and types of cancer. Patients with advanced solid tumors (>30 types) who either progressed with or without standard treatments were genotyped using a single CGP test. The subjects were followed up for a median duration of 590 days to examine therapeutic response, using progression-free survival (PFS), PFS ratio, and factors associated with therapeutic response. RESULTS: Among the 507 patients, 62 (12.2%) received matched therapies with an overall response rate (ORR) of 32.3%. The PFS ratios (≥1.3) were observed in 46.3% (19/41) of the evaluated patients. The proportion of subjects receiving such therapies in the rare cancer cohort was lower than that in the non-rare cancer cohort (9.6% and 17.4%, respectively; P = 0.010). However, ORR of the rare cancer patients was higher than that in the non-rare cancer cohort (43.8% and 20.0%, respectively; P = 0.046). Moreover, ORR of matched therapies in the first or second line after receiving the CGP test was higher than that in the third or later lines (62.5% and 21.7%, respectively; P = 0.003). Rare cancer and early-line treatment were significantly and independently associated with ORR of matched therapies in multivariable analysis (P = 0.017 and 0.004, respectively). CONCLUSION: Patients with rare cancer preferentially benefited from tumor mutation profiling by increasing the chances of therapeutic response to matched therapies. Early-line treatments after profiling increase the therapeutic benefit, irrespective of tumor types.

Detection of atypical attentional behaviors in young subjects.

BACKGROUND: Vigilance ability refers to the accuracy and speed with which a person performs a cognitive-motor task, either voluntarily (endogenous mode) or following a warning stimulus (exogenous mode). In the context of a force production task, our study focuses on the impact of the states of vigilance by proposing an original approach that allows distinguishing between good (inlier) and poor (outlier) participants. We assume that the use of an external signal and duration of the temporal preparation (foreperiod) increase the speed and the precision of motor responses. Our objective is particularly challenging in the context of a limited dataset with a high level of noise. NEW METHOD: Our original methodological approach consists of coupling the RANSAC (RANdom SAmple Consensus) algorithm with a statistical machine learning algorithm to handle noise. COMPARISON WITH EXISTING METHODS: Our clustering approach, based on the coupling of RANSAC methodology with ensemble classifiers, overcomes the limitations of conventional supervised algorithms that are either not robust to outliers (such as K-Nearest Neighbors) and/or not adapted to few-shot learning (such as Support Vector Machines and Artificial Neural Networks). RESULTS: The clustering results were validated in terms of reaction time distributions and force error distributions with respect to participant groups. We show that the use of an external signal and duration of the temporal preparation (foreperiod) increase the speed and the precision of motor responses. CONCLUSION: Our study has allowed us to detect atypical attentional patterns and succeeds in separating the inliers from the outliers.

Optimized models and deep learning methods for drug response prediction in cancer treatments: a review.

Recent advancements in deep learning (DL) have played a crucial role in aiding experts to develop personalized healthcare services, particularly in drug response prediction (DRP) for cancer patients. The DL's techniques contribution to this field is significant, and they have proven indispensable in the medical field. This review aims to analyze the diverse effectiveness of various DL models in making these predictions, drawing on research published from 2017 to 2023. We utilized the VOS-Viewer 1.6.18 software to create a word cloud from the titles and abstracts of the selected studies. This study offers insights into the focus areas within DL models used for drug response. The word cloud revealed a strong link between certain keywords and grouped themes, highlighting terms such as deep learning, machine learning, precision medicine, precision oncology, drug response prediction, and personalized medicine. In order to achieve an advance in DRP using DL, the researchers need to work on enhancing the models' generalizability and interoperability. It is also crucial to develop models that not only accurately represent various architectures but also simplify these architectures, balancing the complexity with the predictive capabilities. In the future, researchers should try to combine methods that make DL models easier to understand; this will make DRP reviews more open and help doctors trust the decisions made by DL models in cancer DRP.

Use of an automatic fruit-zone cooling system to cope with multiple summer stresses in Sangiovese and Montepulciano grapes.

Grapevines are frequently subjected to heatwaves and limited water availability during ripening. These conditions can have consequences for the physiological health of the vines. Moreover, the situation is often exacerbated by intense solar radiation, resulting in reduced yield due to sunburn and a decline in quality. In light of these challenges, our study aimed to develop a fruit-zone cooling system designed to mitigate grape sunburn damage and improve the microclimate conditions within the vineyard. The system comprises a network of proximal sensors that collect microclimate data from the vineyard and an actuator that activates nebulizers when the temperature exceeds the threshold of 35°C. The research was conducted over two years (2022 and 2023) in Bologna (Italy) using potted Sangiovese and Montepulciano vines. These two vintages were characterized by high temperatures, with varying amounts of rainfall during the test period, significantly impacting the evaporative demand, which was notably higher in 2023. Starting from the veraison stage we compared three treatments: Irrigated control vines (WW); Control vines subjected to 50% water restriction during the month of August (WS); WS vines treated with nebulized water in the bunch area during the stress period (WS+FOG). The application of nebulized water effectively reduced the temperature of both the air around the clusters and the clusters themselves. As we expected, Montepulciano showed better single leaf assimilation rate and stomatal conductance under non-limiting water conditions than Sangiovese while their behavior was unaffected under water-scarce conditions. Importantly, for the first time, we demonstrated that nebulized water positively affected gas exchange in both grape varieties. In addition to this, the vines treated with the misting system exhibited higher productivity compared to WS vines without affecting technological maturity. In the 2023 vintage, the activation of the system prevented the ripening blockage that occurred in Montepulciano under water stress. Regarding the concentration of total anthocyanins, a significant increase in color was observed in WS+FOG treatment, suggesting a predominant role of microclimate on anthocyanin biosynthesis and reduction of oxidative phenomena. In conclusion, the fruit-zone cooling system proved to be an invaluable tool for mitigating the adverse effects of multiple summer stresses.

Hepatitis B virus genotypes in precision medicine of hepatitis B-related hepatocellular carcinoma: Where we are now.

Hepatitis B virus (HBV) infection is a major player in chronic hepatitis B that may lead to the development of hepatocellular carcinoma (HCC). HBV genetics are diverse where it is classified into at least 9 genotypes (A to I) and 1 putative genotype (J), each with specific geographical distribution and possible different clinical outcomes in the patient. This diversity may be associated with the precision medicine for HBV-related HCC and the success of therapeutical approaches against HCC, related to different pathogenicity of the virus and host response. This Editorial discusses recent updates on whether the classification of HBV genetic diversity is still valid in terms of viral oncogenicity to the HCC and its precision medicine, in addition to the recent advances in cellular and molecular biology technologies.

High throughput screening aids clinical decision-making in refractory acute myeloid leukaemia.

BACKGROUND: Despite advances in therapeutics for adverse-risk acute myeloid leukaemia (AML), overall survival remains poor, especially in refractory disease. Comprehensive tumour profiling and pre-clinical drug testing can identify effective personalised therapies. CASE: We describe a case of ETV6-MECOM fusion-positive refractory AML, where molecular analysis and in vitro high throughput drug screening identified a tolerable, novel targeted therapy and provided rationale for avoiding what could have been a toxic treatment regimen. Ruxolitinib combined with hydroxyurea led to disease control and enhanced quality-of-life in a patient unsuitable for intensified chemotherapy or allogeneic stem cell transplantation. CONCLUSION: This case report demonstrates the feasibility and role of combination pre-clinical high throughput screening to aid decision making in high-risk leukaemia. It also demonstrates the role a JAK1/2 inhibitor can have in the palliative setting in select patients with AML.

Paediatric clinical study of 3D printed personalised medicines for rare metabolic disorders.

Rare diseases are infrequent, but together they affect up to 6-10 % of the world's population, mainly children. Patients require precise doses and strict adherence to avoid metabolic or cardiac failure in some cases, which cannot be addressed in a reliable way using pharmaceutical compounding. 3D printing (3DP) is a disruptive technology that allows the real-time personalization of the dose and the modulation of the dosage form to adapt the medicine to the therapeutic needs of each patient. 3D printed chewable medicines containing amino acids (citrulline, isoleucine, valine, and isoleucine and valine combinations) were prepared in a hospital setting, and the efficacy and acceptability were evaluated in comparison to conventional compounded medicines in six children. The inclusion of new flavours (lemon, vanilla and peach) to obtain more information on patient preferences and the implementation of a mobile app to obtain patient feedback in real-time was also used. The 3D printed medicines controlled amino acid levels within target levels as well as the conventional medicines. The deviation of citrulline levels was narrower and closer within the target concentration with the chewable formulations. According to participants' responses, the chewable formulations were well accepted and can improve adherence and quality of life. For the first time, 3DP enabled two actives to be combined in the same formulation, reducing the number of administrations. This study demonstrated the benefits of preparing 3D printed personalized treatments for children diagnosed with rare metabolic disorders using a novel technology in real clinical practice.

Navigating uncharted territory: a case report and literature review on the remarkable response to personalized crizotinib containing combinational therapy in a pazopanib refractory patient with novel alterations.

This paper presents a patient with a novel Ig-like-III domain fibroblast growth factor receptor (FGFR2) alteration (W290_P307>C) along with CDKN2A/B alterations and a cadherin 1 (CDH1) alteration. Initial responsiveness to pazopanib monotherapy was encouraging, yet progression occurred after 7.5 months. Following progression, the molecular tumor board recommended a combination therapy approach comprising pazopanib, crizotinib, and palbociclib to target all of the changed pathways at the same time. Pazopanib was chosen to specifically target the FGFR2 alteration, while crizotinib was selected due to its potential synthetic lethality with the CDH1 alteration. In addition, the CDK4/6 inhibitor palbociclib was administered to address the CDKN2A/B alterations. The patient exhibited a remarkable and sustained response to this innovative combination. This case not only underscores the potential of tyrosine kinase inhibitors, exemplified by pazopanib, as a viable alternative for patients without access to pan-FGFR inhibitors, but it also emphasizes their efficacy beyond commonly detected point mutations and rearrangements. Notably, the outstanding response to combination therapy, including crizotinib, in a patient with a CDH1 alteration, further substantiates the preclinical evidence of synthetic lethality between crizotinib and CDH1 alterations. To our knowledge, this represents the first clinical evidence demonstrating the efficacy of crizotinib in a patient with a CDH1 alteration. Through careful dosage adjustments and consideration of individualized genomic information, this case exemplifies the power of personalized medicine in achieving favorable treatment outcomes.