Longitudinal molecular profiling elucidates immunometabolism dynamics in breast cancer.

Although metabolic reprogramming within tumor cells and tumor microenvironment (TME) is well described in breast cancer, little is known about how the interplay of immune state and cancer metabolism evolves during treatment. Here, we characterize the immunometabolic profiles of tumor tissue samples longitudinally collected from individuals with breast cancer before, during and after neoadjuvant chemotherapy (NAC) using proteomics, genomics and histopathology. We show that the pre-, on-treatment and dynamic changes of the immune state, tumor metabolic proteins and tumor cell gene expression profiling-based metabolic phenotype are associated with treatment response. Single-cell/nucleus RNA sequencing revealed distinct tumor and immune cell states in metabolism between cold and hot tumors. Potential drivers of NAC based on above analyses were validated in vitro. In summary, the study shows that the interaction of tumor-intrinsic metabolic states and TME is associated with treatment outcome, supporting the concept of targeting tumor metabolism for immunoregulation.

PIK3CA mutations in endocrine-resistant breast cancer.

Around 75% of breast cancer (BC) patients have tumors expressing the predictive biomarker estrogen receptor α (ER) and are offered endocrine therapy. One-third eventually develop endocrine resistance, a majority with retained ER expression. Mutations in the phosphatidylinositol bisphosphate 3-kinase (PI3K) catalytic subunit encoded by PIK3CA is a proposed resistance mechanism and a pharmacological target in the clinical setting. Here we explore the frequency of PIK3CA mutations in endocrine-resistant BC before and during treatment and correlate to clinical features. Patients with ER-positive (ER +), human epidermal growth factor receptor 2 (HER2)-negative primary BC with an ER + relapse within 5 years of ongoing endocrine therapy were retrospectively assessed. Tissue was collected from primary tumors (n = 58), relapse tumors (n = 54), and tumor-free lymph nodes (germline controls, n = 62). Extracted DNA was analyzed through panel sequencing. Somatic mutations were observed in 50% (31/62) of the patients, of which 29% occurred outside hotspot regions. The presence of PIK3CA mutations was significantly associated with nodal involvement and mutations were more frequent in relapse than primary tumors. Our study shows the different PIK3CA mutations in endocrine-resistant BC and their fluctuations during therapy. These results may aid investigations of response prediction, facilitating research deciphering the mechanisms of endocrine resistance.

Prognostic impact of HER2 biomarker levels in trastuzumab-treated early HER2-positive breast cancer.

BACKGROUND: Overexpression of human epidermal growth factor receptor 2 (HER2) caused by HER2 gene amplification is a driver in breast cancer tumorigenesis. We aimed to investigate the prognostic significance of manual scoring and digital image analysis (DIA) algorithm assessment of HER2 copy numbers and HER2/CEP17 ratios, along with ERBB2 mRNA levels among early-stage HER2-positive breast cancer patients treated with trastuzumab. METHODS: This retrospective study comprised 371 early HER2-positive breast cancer patients treated with adjuvant trastuzumab, with HER2 re-testing performed on whole tumor sections. Digitized tumor tissue slides were manually scored and assessed with uPath HER2 Dual ISH image analysis, breast algorithm. Targeted ERBB2 mRNA levels were assessed by the Xpert® Breast Cancer STRAT4 Assay. HER2 copy number and HER2/CEP17 ratio from in situ hybridization assessment, along with ERBB2 mRNA levels, were explored in relation to recurrence-free survival (RFS). RESULTS: The analysis showed that patients with tumors with the highest and lowest manually counted HER2 copy number levels had worse RFS than those with intermediate levels (HR = 2.7, CI 1.4-5.3, p = 0.003 and HR = 2.1, CI 1.1-3.9, p = 0.03, respectively). A similar trend was observed for HER2/CEP17 ratio, and the DIA algorithm confirmed the results. Moreover, patients with tumors with the highest and the lowest values of ERBB2 mRNA had a significantly worse prognosis (HR = 2.7, CI 1.4-5.1, p = 0.003 and HR = 2.8, CI 1.4-5.5, p = 0.004, respectively) compared to those with intermediate levels. CONCLUSIONS: Our findings suggest that the association between any of the three HER2 biomarkers and RFS was nonlinear. Patients with tumors with the highest levels of HER2 gene amplification or ERBB2 mRNA were associated with a worse prognosis than those with intermediate levels, which is of importance to investigate in future clinical trials studying HER2-targeted therapy.

A Rare Cause of Recurrent Pericarditis.

Recurrent pericarditis poses a significant challenge to clinicians, particularly when patients are unresponsive or intolerant to conventional treatments. Accurate diagnosis of recurrent pericarditis, potentially facilitated by collaboration with other medical specialties, is crucial for ensuring timely and appropriate treatment of symptoms and prevention of further episodes. We present a case of a 52-year-old male patient with a history of multiple episodes of pericarditis, who was admitted to the Cardiology Department due to another recurrence. The first episode of pericarditis was diagnosed nearly a year before his current hospitalization. Initially, the patient received high doses of Ibuprofen and colchicine, but there was no favorable response to this treatment regimen. At that point, intravenous prednisolone was initiated, which led to clinical and laboratory improvement. Since then, the patient had experienced two more recurrences while tapering off prednisolone. Immunological tests, Mantoux tuberculin skin test, and chest and abdominal computed tomography (CT) had revealed no evidence of an underlying cause. On admission the patient was febrile and the electrocardiogram showed diffuse ST elevation and PR depression in leads I, II, aVF, V2-V6. Bedside echocardiogram revealed a small pericardial effusion and since the chest X-ray was normal and no other potential infection sites were identified, the diagnosis of recurrent pericarditis was established. During his current hospitalization, intravenous prednisolone was initiated, colchicine was continued and a more detailed history was taken, raising the suspicion upon the presence of an auto-inflammatory disease. Genetic investigation identified an uncommon heterozygous mutation in the familial Mediterranean fever gene (MEFV) and after consideration of patient's history, familial Mediterranean fever was diagnosed. Anakinra was initiated on top of colchicine and gradual tapering of corticosteroids and the patient showed significant improvement, with no other recurrence during the two-year follow-up.

Towards building a Self-Sovereign Identity Framework for Healthcare.

Drifted by the hype of new and efficient machine learning and artificial intelligence models aiming to unlock the information wealth hidden inside heterogeneous datasets across different markets and disciplines, healthcare data are in the center of novel technological advancements in predictive health diagnostics, remote healthcare, assistive leaving and wellbeing. Nevertheless, this emerging market has underlined the necessity of developing new methods and updating existing ones for preserving the privacy of the data and their owners, as well as, ensuring confidentiality and trust throughout the health care data processing pipelines. This paper presents one of the key innovations of a Horizon Europe funded project named "TRUSTEE", which focuses on building a trust and privacy framework for cross-European data exchange by employing a secure and private federated framework to empower companies, organizations, and individuals to securely access data across different disciplines, use and re-use data and metadata to extract knowledge with trust. In particular we present our work on implementing strong authentication and continuous authorization schemes based on the duality of eIDAS trust framework and Self Sovereign Identity (SSI) management to ensure security and trust over authentication, authorization and accounting processes for healthcare.

Medical application of laser-induced breakdown spectroscopy (LIBS) for assessment of trace element and mineral in biosamples: Laboratory and clinical validity of the method.

BACKGROUND: Biomedical application is based on the use of LIBS-derived data on chemical contents of tissues in diagnosis of diseases, forensic investigation, as well as a mechanism for providing online feedback for laser surgery. Although LIBS has certain advantages, the issue of correlation of LIBS-derived data on chemical element content in different human and animal tissues with other methods, and especially ICP-MS, remains pertinent. The objective of the present review was to discuss the application of laser-induced breakdown spectroscopy (LIBS) for elemental analysis of human biosamples or tissues from experimental models of human diseases. METHODS: A systematic search in the PubMed-Medline, Scopus, and Google Scholar databases using the terms laser-induced breakdown spectroscopy, LIBS, metals, trace elements, minerals, and names of particular chemical elements was performed up through 25 February, 2023. Of all extracted studies only those dealing with human subjects, human tissues, in vivo animal and in vitro cell line models of human diseases were reviewed in detail. RESULTS: The majority of studies revealed a wide number of metals and metalloids in solid tissues including teeth (As, Ag, Ca, Cd, Cr, Cu, Fe, Hg, Mg, Ni, P, Pb, Sn, Sr, Ti, and Zn), bones (Al, Ba, Ca, Cd, Cr, K, Mg, Na, Pb, Sr), and nails (Al, As, Ca, Fe, K, Mg, Na, P, Pb, Si, Sr, Ti, Zn). At the same time, LIBS was also used for estimation of trace element and mineral content in hair (Ca, Cu, Fe, K, Mg, Na, Zn), blood (Al, Ca, Co, Cd, Cu, Fe, Mg, Mn, Ni, Pb, Si, Sn, Zn), cancer tissues (Ca, Cu, Fe, Mg, K, Na, Zn) and other tissues. Single studies revealed satisfactory correspondence between quantitative LIBS and ICP-OES/MS data on the level of As (81-93 %), Pb (94-98 %), Cd (50-94 %) in teeth, Cu (97-105 %), Fe (117 %), Zn (88-117 %) in hair, Ca (97-99 %), Zn (90-95 %), and Pb (61-82 %) in kidney stones. LIBS also estimated specific patterns of trace element and mineral content associated with multiple pathologies, including caries, cancer, skin disorders, and other systemic diseases including diabetes mellitus type 2, osteoporosis, hypothyroidism, etc. Data obtained from in situ tissue LIBS analysis were profitably used for discrimination between tissue types. CONCLUSIONS: Taken together, the existing data demonstrate the applicability of LIBS for medical studies, although further increase in its sensitivity, calibration range, cross-validation, and quality control is required.

Mathematical Modeling Evaluates How Vaccinations Affected the Course of COVID-19 Disease Progression.

The regulation policies implemented, the characteristics of vaccines, and the evolution of the virus continue to play a significant role in the progression of the SARS-CoV-2 pandemic. Numerous research articles have proposed using mathematical models to predict the outcomes of different scenarios, with the aim of improving awareness and informing policy-making. In this work, we propose an expansion to the classical SEIR epidemiological model that is designed to fit the complex epidemiological data of COVID-19. The model includes compartments for vaccinated, asymptomatic, hospitalized, and deceased individuals, splitting the population into two branches based on the severity of progression. In order to investigate the impact of the vaccination program on the spread of COVID-19 in Greece, this study takes into account the realistic vaccination program implemented in Greece, which includes various vaccination rates, different dosages, and the administration of booster shots. It also examines for the first time policy scenarios at crucial time-intervention points for Greece. In particular, we explore how alterations in the vaccination rate, immunity loss, and relaxation of measures regarding the vaccinated individuals affect the dynamics of COVID-19 spread. The modeling parameters revealed an alarming increase in the death rate during the dominance of the delta variant and before the initiation of the booster shot program in Greece. The existing probability of vaccinated people becoming infected and transmitting the virus sets them as catalytic players in COVID-19 progression. Overall, the modeling observations showcase how the criticism of different intervention measures, the vaccination program, and the virus evolution has been present throughout the various stages of the pandemic. As long as immunity declines, new variants emerge, and vaccine protection in reducing transmission remains incompetent; monitoring the complex vaccine and virus evolution is critical to respond proactively in the future.

Breast cancer patient-derived whole-tumor cell culture model for efficient drug profiling and treatment response prediction.

Breast cancer (BC) is a complex disease comprising multiple distinct subtypes with different genetic features and pathological characteristics. Although a large number of antineoplastic compounds have been approved for clinical use, patient-to-patient variability in drug response is frequently observed, highlighting the need for efficient treatment prediction for individualized therapy. Several patient-derived models have been established lately for the prediction of drug response. However, each of these models has its limitations that impede their clinical application. Here, we report that the whole-tumor cell culture (WTC) ex vivo model could be stably established from all breast tumors with a high success rate (98 out of 116), and it could reassemble the parental tumors with the endogenous microenvironment. We observed strong clinical associations and predictive values from the investigation of a broad range of BC therapies with WTCs derived from a patient cohort. The accuracy was further supported by the correlation between WTC-based test results and patients' clinical responses in a separate validation study, where the neoadjuvant treatment regimens of 15 BC patients were mimicked. Collectively, the WTC model allows us to accomplish personalized drug testing within 10 d, even for small-sized tumors, highlighting its potential for individualized BC therapy. Furthermore, coupled with genomic and transcriptomic analyses, WTC-based testing can also help to stratify specific patient groups for assignment into appropriate clinical trials, as well as validate potential biomarkers during drug development.

Multi-species meta-analysis identifies transcriptional signatures associated with cardiac endothelial responses in the ischaemic heart.

AIM: Myocardial infarction remains the leading cause of heart failure. The adult human heart lacks the capacity to undergo endogenous regeneration. New blood vessel growth is integral to regenerative medicine necessitating a comprehensive understanding of the pathways that regulate vascular regeneration. We sought to define the transcriptomic dynamics of coronary endothelial cells following ischaemic injuries in the developing and adult mouse and human heart and to identify new mechanistic insights and targets for cardiovascular regeneration. METHODS AND RESULTS: We carried out a comprehensive meta-analysis of integrated single-cell RNA-sequencing data of coronary vascular endothelial cells from the developing and adult mouse and human heart spanning healthy and acute and chronic ischaemic cardiac disease. We identified species-conserved gene regulatory pathways aligned to endogenous neovascularization. We annotated injury-associated temporal shifts of the endothelial transcriptome and validated four genes: VEGF-C, KLF4, EGR1, and ZFP36. Moreover, we showed that ZFP36 regulates human coronary endothelial cell proliferation and defined that VEGF-C administration in vivo enhances clonal expansion of the cardiac vasculature post-myocardial infarction. Finally, we constructed a coronary endothelial cell meta-atlas, CrescENDO, to empower future in-depth research to target pathways associated with coronary neovascularization. CONCLUSION: We present a high-resolution single-cell meta-atlas of healthy and injured coronary endothelial cells in the mouse and human heart, revealing a suite of novel targets with great potential to promote vascular regeneration, and providing a rich resource for therapeutic development.

Macrophages trigger cardiomyocyte proliferation by increasing epicardial vegfaa expression during larval zebrafish heart regeneration.

Cardiac injury leads to the loss of cardiomyocytes, which are rapidly replaced by the proliferation of the surviving cells in zebrafish, but not in mammals. In both the regenerative zebrafish and non-regenerative mammals, cardiac injury induces a sustained macrophage response. Macrophages are required for cardiomyocyte proliferation during zebrafish cardiac regeneration, but the mechanisms whereby macrophages facilitate this crucial process are fundamentally unknown. Using heartbeat-synchronized live imaging, RNA sequencing, and macrophage-null genotypes in the larval zebrafish cardiac injury model, we characterize macrophage function and reveal that these cells activate the epicardium, inducing cardiomyocyte proliferation. Mechanistically, macrophages are specifically recruited to the epicardial-myocardial niche, triggering the expansion of the epicardium, which upregulates vegfaa expression to induce cardiomyocyte proliferation. Our data suggest that epicardial Vegfaa augments a developmental cardiac growth pathway via increased endocardial notch signaling. The identification of this macrophage-dependent mechanism of cardiac regeneration highlights immunomodulation as a potential strategy for enhancing mammalian cardiac repair.

PANACEA resilient and secure toolkit for healthcare infrastructures.

Healthcare organizations are frequently subject to cybersecurity incidents. The outbreak of a pandemic such as COVID-19 has shown the need for specific operational and organizational measures to be in place in order to reduce the risk of successful cyberattacks. Time will be key: preparation is needed to ensure quick secure set-up of additional resources (IT, staff, medical devices) when the next emergency will hit. The PANACEA Solution Toolkit is a suite of complementary tools to provide Health Care Organizations (HCO) with assessment, guidance, technical and organizational "infrastructure" to address the cybersecurity challenges. It provides support for fortifying health organizations against cyber threats on multiple different levels (technical, behavioral, organizational, strategical) and across a diverse set of workflows and scenarios. In order to determine whether the toolkit satisfies the specific business and users' requirements in the selected use cases, a detailed validation plan and execution roadmap is established taking into account the constraints of the current emergent situation.

Emerging and Established Trends to Support Secure Health Information Exchange.

This work aims to provide information, guidelines, established practices and standards, and an extensive evaluation on new and promising technologies for the implementation of a secure information sharing platform for health-related data. We focus strictly on the technical aspects and specifically on the sharing of health information, studying innovative techniques for secure information sharing within the health-care domain, and we describe our solution and evaluate the use of blockchain methodologically for integrating within our implementation. To do so, we analyze health information sharing within the concept of the PANACEA project that facilitates the design, implementation, and deployment of a relevant platform. The research presented in this paper provides evidence and argumentation toward advanced and novel implementation strategies for a state-of-the-art information sharing environment; a description of high-level requirements for the transfer of data between different health-care organizations or cross-border; technologies to support the secure interconnectivity and trust between information technology (IT) systems participating in a sharing-data "community"; standards, guidelines, and interoperability specifications for implementing a common understanding and integration in the sharing of clinical information; and the use of cloud computing and prospectively more advanced technologies such as blockchain. The technologies described and the possible implementation approaches are presented in the design of an innovative secure information sharing platform in the health-care domain.

Cyber-attacks and threats for healthcare - a multi-layer thread analysis.

Due to the advent of novel technologies and digital opportunities allowing to simplify user lives, healthcare is increasingly evolving towards digitalization. This represent a great opportunity on one side but it also exposes healthcare organizations to multiple threats (both digital and not) that may lead an attacker to compromise the security of medial processes and potentially patients' safety. Today technical cybersecurity countermeasures are used to protect the confidentiality, integrity and availability of data and information systems - especially in the healthcare domain. This paper will report on the current state of the art about cyber security in the Healthcare domain with particular emphasis on current threats and methodologies to analyze and manage them. In addition, it will introduce a multi-layer attack model providing a new perspective for attack and threat identification and analysis.

MYC as a driver of stochastic chromatin networks: implications for the fitness of cancer cells.

The relationship between stochastic transcriptional bursts and dynamic 3D chromatin states is not well understood. Using an innovated, ultra-sensitive technique, we address here enigmatic features underlying the communications between MYC and its enhancers in relation to the transcriptional process. MYC thus interacts with its flanking enhancers in a mutually exclusive manner documenting that enhancer hubs impinging on MYC detected in large cell populations likely do not exist in single cells. Dynamic encounters with pathologically activated enhancers responsive to a range of environmental cues, involved <10% of active MYC alleles at any given time in colon cancer cells. Being the most central node of the chromatin network, MYC itself likely drives its communications with flanking enhancers, rather than vice versa. We submit that these features underlie an acquired ability of MYC to become dynamically activated in response to a diverse range of environmental cues encountered by the cell during the neoplastic process.

Author Correction: WNT signaling and AHCTF1 promote oncogenic MYC expression through super-enhancer-mediated gene gating.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Repeated leftover serosurvey of SARS-CoV-2 IgG antibodies, Greece, March and April 2020.

A serosurvey of IgG antibodies against severe acute respiratory coronavirus 2 (SARS-CoV-2) was performed during March and April 2020. Among 6,586 leftover sera, 24 (0.36%) were positive, with higher prevalence in females, older individuals and residents of large urban areas. Seroprevalence was estimated at 0.02% and 0.25%, respectively, in March and April, infection fatality rate at 2.66% and 0.54%. Our findings confirm low COVID-19 incidence in Greece and possibly the effectiveness of early measures.

Programmed death-ligand 1 gene expression is a prognostic marker in early breast cancer and provides additional prognostic value to 21-gene and 70-gene signatures in estrogen receptor-positive disease.

Gene and protein expression of programmed death-ligand 1 (PD-L1) are prognostic in early breast cancer (BC), but their prognostic information is inconsistent at least in some biological subgroups. The validated prognostic gene signatures (GS) in BC are mainly based on proliferation and estrogen receptor (ER)-related genes. Here, we aimed to explore the prognostic capacity of PD-L1 expression at the protein vs mRNA levels and to investigate the prognostic information that PD-L1 can potentially add to routinely used GS. Gene expression data were derived from two early BC cohorts (cohort 1: 562 patients; cohort 2: 1081 patients). Tissue microarrays from cohort 1 were immunohistochemically (IHC) stained for PD-L1 using the SP263 clone. GS scores (21-gene, 70-gene) were calculated, and likelihood-ratio (LR) tests and concordance indices were used to evaluate the additional prognostic information for each signature. The immune cell composition was also evaluated using the CIBERSORT in silico tool. PD-L1 gene and protein expressions were independently associated with better prognosis. In ER+/HER2- patients, PD-L1 gene expression provided significant additional prognostic information beyond that of both 21-GS [LR-Δχ2  = 15.289 and LR-Δχ2  = 8.812, P < 0.01 for distant metastasis-free interval (DMFI) in cohorts 1 and 2, respectively] and 70-GS score alone (LR-Δχ2  = 18.198 and LR-Δχ2  = 8.467, P < 0.01 for DMFI in cohorts 1 and 2, respectively). PD-L1 expression was correlated with IHC-determined CD3+ cells (r = 0.41, P < 0.001) and with CD8+ (r = 0.62, P < 0.001) and CD4+ memory activated (r = 0.66, P < 0.001) but not with memory resting (r = -0.063, P = 0.14) or regulatory (r = -0.12, P < 0.01) T cells in silico. PD-L1 gene expression represents a promising favorable prognostic marker and can provide additional prognostic value to 21- and 70-gene scores in ER+/HER2- BC.

WNT signaling and AHCTF1 promote oncogenic MYC expression through super-enhancer-mediated gene gating.

WNT signaling activates MYC expression in cancer cells. Here we report that this involves an oncogenic super-enhancer-mediated tethering of active MYC alleles to nuclear pores to increase transcript export rates. As the decay of MYC transcripts is more rapid in the nucleus than in the cytoplasm, the oncogenic super-enhancer-facilitated export of nuclear MYC transcripts expedites their escape from the nuclear degradation system in colon cancer cells. The net sum of this process, as supported by computer modeling, is greater cytoplasmic MYC messenger RNA levels in colon cancer cells than in wild type cells. The cancer-cell-specific gating of MYC is regulated by AHCTF1 (also known as ELYS), which connects nucleoporins to the oncogenic super-enhancer via ß-catenin. We conclude that WNT signaling collaborates with chromatin architecture to post-transcriptionally dysregulate the expression of a canonical cancer driver.