Clinical Landscape Research Articles

Clinical translation and landscape of silver nanoparticles.

Despite being clinically used for over a century, the benefits of silver nanoparticles are perennially under debate and dispute. In the last two decades, a revived interest in their therapeutic applications has resulted in a few new formulations transitioning into clinical trials. These metal nanomedicines are used in concrete applications that are defined by the physicochemical and biological features of the silver nanoconstructs, as well as their biodistribution profiles. Examples of these applications are topical antibacterial and antiviral therapies and wound healing, as these avoid concerns regarding the long-term accumulation of the nanomedicines in fenestrated organs after intravenous administration. Here, we discuss the current landscape of silver nanoparticles, and critically analyze the characteristics that endowed their transition and use in clinical settings.

Reshaped Local and Systemic Immune Responses Triggered by a Biomimetic Multifunctional Nanoplatform Coordinating Multi-Pathways for Cancer Therapy.

Immunotherapy has fundamentally transformed the clinical cancer treatment landscape; however, achieving intricate and multifaceted modulation of the immune systems remains challenging. Here, a multipathway coordination of immunogenic cell death (ICD), autophagy, and indoleamine 2,3-dioxygenase-1 (IDO1) was achieved by a biomimetic nano-immunomodulator assembled from a chemotherapeutic agent (doxorubicin, DOX), small interfering RNA (siRNA) molecules targeting IDO1 (siIDO1), and the zeolitic imidazolate framework-8 (ZIF-8). After being camouflaged with a macrophage membrane, the biomimetic nanosystem, named mRDZ, enriched in tumors, which allowed synergistic actions of its components within tumor cells. The chemotherapeutic intervention led to a compensatory upregulation in the expression of IDO1, consequently exerting an inhibitory effect on the reactive oxygen species (ROS) and autophagic responses triggered by DOX and ZIF-8. Precise gene silencing of IDO1 by siIDO1 alleviated its suppressive influence, thereby facilitating increased ROS production and improved autophagy, ultimately bolstering tumor immunogenicity. mRDZ exhibited strong capability to boost potent local and systemic antitumor immune responses with a feature of memory, which led to the effective suppression of the growth, lung metastasis, and recurrence of the tumor. Serving as an exemplary model for the straightforward and potent reshaping of the immune system against tumors, mRDZ offers valuable insights into the development of immunomodulatory nanomaterials for cancer therapy.

B-251 Comprehensive Proteomics Analysis Reveals an Exosomal Biomarker Signature Useful for Detection of Non-Small Cell Lung Cancer

Abstract Background Lung cancer is the second most commonly diagnosed lung cancer in the world, and Non-Small Cell Lung Cancer is the most prevalent subtype. Tissue biopsy is the gold standard for detecting lung cancer, but is highly invasive as it necessitates the extraction of a sample of tissue for histologic analysis. It also carries risks of bleeding and/or infection, and is inconvenient from a patient perspective. The development of a minimally invasive test, such as one utilizing a blood or urine sample, capable of providing accurate results for lung cancer detection and/or subtyping, would significantly enhance the clinical landscape and streamline patient care. Methods In this study we utilize A549 and H1299 human lung cancer cell lines, differing in cell type, location within the lung, and genetic composition (Kras & p53 status), along with two additional cancer cell lines (HeLa/cervical cancer and SCBO/bladder cancer), as controls. Cell lysate and exosome proteomics data were obtained using data independent acquisition- liquid chromatography mass spectrometry (DIA-LCMS) and analyzed using ProteoDisco 2.0, a custom-designed software application in R. Raw mass spectra data was subject to quantile normalization to mitigate external, non-biological differences between the samples. Differential protein expression was performed and Student's t-test was used to identify significantly different proteins across the sample types. A correlation coefficient matrix and Principal Component Analysis were used to assess global differences, and hierarchical clustering and heat maps allowed for visualizing of specific groups of proteins that separated all sample types. Results Over 1000 proteins were identified in each of the exosome samples, and >7500 proteins were detected in the lysates. Correlation coefficient matrix and PCA demonstrate that exosomal protein profiles, relative to cell lysates, are better at differentiating between the two lung cancer cell lines and controls. Surprisingly, exosomal proteomic patterns are different for the two lung cancers, implicating activation of different signaling pathways. Specifically, hierarchical clustering identified protein clusters showing enrichment for multiple biological processes: H1299 cells manifest enrichment of apical junction proteins and in epithelial-mesenchymal transition (EMT) ontology, while A549 cell lines show enrichment in proteins involved in oxidative phosphorylation. This combination of functional pathways can be used as a biomarker signature to distinguish between these two lung cancer subtypes, and from controls. Conclusions A short list of exosomal proteins, comprising apical junction, EMT, and oxidative phosphorylation constituents can detect lung cancer and further distinguish between subtypes represented by A549 and H1299 lung cancer cells. This biomarker signature has potential for detecting and subtyping lung cancer, to allow for early detection of disease, development of personalized treatment strategies, and result in improved clinical outcomes for this deadly disease.

Living systematic review and comprehensive network meta-analysis of ALS clinical trials: study protocol.

Amyotrophic lateral sclerosis (ALS) is a fatal neurogenerative disease with no effective treatment to date. Despite numerous clinical trials, the majority of studies have been futile in their effort to significantly alter the course of the disease. However, these studies may still provide valuable information for identifying patient subgroups and generating new hypotheses for future research. Additionally, synthesising evidence from these studies may help overcome the limitations of individual studies. Network meta-analysis may refine the assessment of efficacy in specific patient subgroups, evaluate intervention characteristics such as mode of administration or biological mechanisms of action, and rank order promising therapeutic areas of interest. Therefore, we aim to synthesise the available evidence from ALS clinical trials. We will conduct a systematic review to identify all clinical trials that assessed disease-modifying pharmaceutical therapies, cell therapies, or supplements in patients with ALS. Outcomes of interest are clinical disease progression outcomes and survival. We will conduct this search in the period Q4 2024 in three databases: PubMed, Embase and ClinicalTrials.gov for studies from 1999 to 2023. Individual patient data and aggregate data will be collected and subsequentially synthesised in meta-analytical models. The final model will be presented as an open-source web application with biannual updates of the underlying data, thereby providing a 'living' overview of the ALS clinical trial landscape. No ethics approvals are required. Findings will be presented at relevant conferences and submitted to peer-reviewed journals. Data will be stored anonymously in secure repositories.

How Is Artificial Intelligence Changing the Clinical Trials Landscape?

How Is Artificial Intelligence Changing the Clinical Trials Landscape?

09O The clinical and molecular landscape of genetic neuromuscular disorders in Senegal, West Africa

09O The clinical and molecular landscape of genetic neuromuscular disorders in Senegal, West Africa

Parenteral nutrition in advanced cancer: Exploring the clinical landscape

Parenteral nutrition in advanced cancer: Exploring the clinical landscape

8742 Exploring the Clinical Landscape of Papillary Thyroid Microcarcinoma with Lymph Node Metastasis: A Single-Institution Case Series and Implications for Treatment Decisions

8742 Exploring the Clinical Landscape of Papillary Thyroid Microcarcinoma with Lymph Node Metastasis: A Single-Institution Case Series and Implications for Treatment Decisions

The role of molecular biomarkers in recurrent glioblastoma trials: an assessment of the current trial landscape of genome-driven oncology

For glioblastoma patients, the efficacy-targeted therapy is limited to date. Most of the molecular therapies previously studied are lacking efficacy in this population. More trials are needed to study the actual actionability of biomarkers in (recurrent) glioblastoma. This study aimed to assess the current clinical trial landscape to assess the role of molecular biomarkers in trials on recurrent glioblastoma treatment. The database ClinicalTrials.gov was used to identify not yet completed clinical trials on recurrent glioblastoma in adults. Recruiting studies were assessed to investigate the role of molecular criteria, which were retrieved as detailed as possible. Primary outcome was molecular criteria used as selection criteria for study participation. Next to this, details on moment and method of testing, and targets and drugs studied, were collected. In 76% (181/237) of the included studies, molecular criteria were not included in the study design. Of the remaining 56 studies, at least one specific genomic alteration as selection criterium for study participation was required in 33 (59%) studies. Alterations in EGFR, CDKN2A/B or C, CDK4/6, and RB were most frequently investigated, as were the corresponding drugs abemaciclib and ribociclib. Of the immunotherapies, CAR-T therapies were the most frequently studied therapies. Previously, genomics studies have revealed the presence of potentially actionable alterations in glioblastoma. Our study shows that the potential efficacy of targeted treatment is currently not translated into genome-driven trials in patients with recurrent glioblastoma. An intensification of genome-driven trials might help in providing evidence for (in)efficacy of targeted treatments.

Clinical Features, Genetic Landscape and Management of Behçet's Syndrome: A Comprehensive Review

Behçet's syndrome is a systemic inflammatory disorder of unknown origin, presenting with diverse symptoms such as recurrent oral and genital ulcers, skin lesions, and uveitis, and can impact multiple organ systems. Diagnosis relies primarily on clinical evaluation due to the lack of specific diagnostic tests. Management requires a multidisciplinary approach to control inflammation and alleviate symptoms, utilizing treatments like corticosteroids, immunosuppressive agents, and biological therapies. The higher prevalence of Behçet's syndrome along the Silk Road points to significant environmental and genetic influences. Despite progress in understanding its clinical manifestations and treatment options, the underlying mechanisms of the disease remain unclear. Future research is crucial to uncover the disease's pathophysiology and refine treatment strategies, aiming to prevent severe complications such as blindness and neurological impairment. This comprehensive review explores the clinical features, genetic background, and management strategies for Behçet's syndrome, highlighting the potential of precision medicine to improve patient care.

Access for ALL in ALS: A large-scale, inclusive, collaborative consortium to unlock the molecular and genetic mechanisms of amyotrophic lateral sclerosis.

Recent progress in therapeutics for amyotrophic lateral sclerosis (ALS) has spurred development and imbued the field of ALS with hope for more breakthroughs, yet substantial scientific gaps persist. This unmet need remains a stark reminder that innovative paradigms are needed to invigorate ALS research. To move toward more informative, targeted, and personalized drug development, the National Institutes of Health (NIH) established a national ALS clinical research consortium called Access for ALL in ALS (ALL ALS). This new consortium is a multi-institutional effort that aims to organize the ALS clinical research landscape in the United States. ALL ALS is operating in partnership with several stakeholders to operationalize the recommendations of the Accelerating Access to Critical Therapies for ALS Act (ACT for ALS) Public Private Partnership. ALL ALS will provide a large-scale, centralized, and readily accessible infrastructure for the collection and storage of a wide range of data from people living with ALS (symptomatic cohort) or who may be at risk of developing ALS (asymptomatic ALS gene carriers). Importantly, ALL ALS is designed to encourage community engagement, equity, and inclusion. The consortium is prioritizing the enrollment of geographically, ethnoculturally, and socioeconomically diverse participants. Collected data include longitudinal clinical data and biofluids, genomic, and digital biomarkers that will be harmonized and linked to the central Accelerating Medicines Partnership for ALS (AMP ALS) portal for sharing with the research community. The aim of ALL ALS is to deliver a comprehensive, inclusive, open-science dataset to help researchers answer important scientific questions of clinical relevance in ALS.

Evidence map of traditional Chinese exercises.

This study aimed to assess and visually depict the clinical evidence landscape of traditional Chinese exercises and identify any research gaps and future research needs. We comprehensively searched seven Chinese and English databases to identify randomized controlled trials (RCTs) and systematic reviews (SRs) evaluating the effects of traditional Chinese exercises from their inception until May 2023. The quality of evidence was assessed via the GRADE approach, and the research topics, intervention effects, and strength of evidence were graphically displayed. This evidence map includes 2,017 studies, comprising 1,822 RCTs and 195 SRs. These studies were conducted globally in various countries. Among the traditional Chinese exercises, Tai Chi and Baduanjin have received the most research attention, with a growing number of publications. When traditional Chinese exercises were compared with the control groups, 88.2% of the included SRs reported significantly positive effects, 4.1% reported unclear effects, and 7.7% reported no significant differences. The findings suggested that traditional Chinese exercises could benefit patients with osteoarthritis, osteoporosis, hypertension, coronary heart disease, diabetes, chronic obstructive pulmonary disease, stroke, Parkinson's disease, anxiety, and depression. However, the overall quality of the evidence was suboptimal, with 11.3% rated as moderate, 45.6% as low, and 43.1% as critically low. This evidence map visually represents valuable information on traditional Chinese exercises. While most studies have reported significant benefits, the overall quality of evidence is low.

Clinical application and immune infiltration landscape of stemness-related genes in heart failure.

Heart failure (HF) is the leading cause of morbidity and mortality worldwide. Stemness refers to the self-renewal and differentiation ability of cells. However, little is known about the heart's stemness properties. Thus, the current study aims to identify putative stemness-related biomarkers to construct a viable prediction model of HF and characterize the immune infiltration features of HF. HF datasets from the Gene Expression Omnibus (GEO) database were adopted as the training and validation cohorts while stemness-related genes were obtained from GeneCards and previously published papers. Feature selection was performed using two machine learning algorithms. Nomogram models were then constructed to predict HF risk based on the selected key genes. Moreover, the biological functions of the key genes were evaluated using Gene Ontology (GO) and Kyoto Encyclopedia of Genes Genomes (KEGG) pathway analyses, and gene set variation analysis (GSVA) and enrichment analysis (GSEA) were performed between the high- and low-risk groups. The immune infiltration landscape in HF was investigated, and the interaction network of key genes was analysed to predict potential targets and molecular mechanisms. Seven key genes, namely SMOC2, LUM, FNDC1, SCUBE2, CD163, BLM and S1PR3, were included in the proposed nomogram. This nomogram showed good predictive performance for HF diagnosis in the training and validation sets. GO and KEGG analyses revealed that the key genes were primarily associated with ageing, inflammatory processes and DNA oxidation. GSEA and GSVA identified various inflammatory and immune signalling pathways that were enriched between the high- and low-risk groups. The infiltration of 15 immune cell subsets suggests that adaptive immunity has an important role in HF. Our study identified a clinically significant stemness-related signature for predicting HF risk, with the potential to improve early disease diagnosis, optimize risk stratification and provide new strategies for treating patients with HF.

Energy metabolism-related GLUD1 contributes to favorable clinical outcomes of IDH-mutant glioma

BackgroundGlioma is the most common brain tumor. IDH mutations occur frequently in glioma, indicating a more favorable prognosis. We aimed to explore energy metabolism-related genes in glioma to promote the research and treatment.MethodsDatasets were obtained from TCGA and GEO databases. Candidate genes were screened by differential gene expression analysis, then functional enrichment analysis was conducted on the candidate genes. PPI was also carried out to help determine the target gene. GSEA and DO analysis were conducted in the different expression level groups of the target gene. Survival analysis and immune cell infiltrating analysis were performed as well.ResultsWe screened 34 candidate genes and selected GLUD1 as the target gene. All candidate genes were significantly enriched in 10 KEGG pathways and 330 GO terms. GLUD1 expression was higher in IDH-mutant samples than IDH-wildtype samples, and higher in normal samples than tumor samples. Low GLUD1 expression was related to poor prognosis according to survival analysis. Most types of immune cells were negatively related to GLUD1 expression, but monocytes and activated mast cells exhibited significantly positive correlation with GLUD1 expression. GLUD1 expression was significantly related to 119 drugs and 6 immune checkpoint genes. GLUD1 was able to serve as an independent prognostic indicator of IDH-mutant glioma.ConclusionIn this study, we identified an energy metabolism-related gene GLUD1 potentially contributing to favorable clinical outcomes of IDH-mutant glioma. In glioma, GLUD1 related clinical outcomes and immune landscape were clearer, and more valuable information was provided for immunotherapy.

A novel encryption protocol for facilitating de-identification of genomics health data

The exponential growth and affordability of genomics sequencing in the clinical landscape in recent years have intensified a challenge facing privacy experts. They grapple with how to evaluate and mitigate the significant risk of genomics data being used to re-identify individuals. The lack of clear genomics guidance in HIPAA has invited a wide spectrum of expert opinion from advocating for conservative limitations to be placed on genomics data sharing to ‘security’-based arguments that carefully calibrated technical, administrative, and legal safeguards may provide adequate protection in many cases. The need to weigh privacy concerns against the extraordinary value that genomics data offers to cancer and rare disease clinical research is compounded by the reality that conventional data modifications, such as redaction, aggregation, and perturbation, often critically undermine these important use cases. We present an innovative solution for de-identifying genomics data according to a conservative interpretation of HIPAA while still preserving maximal utility for clinical purposes. Our solution rejects the notion that privacy can be achieved directly via security. Instead, we introduce a reversible encryption protocol designed to be applied to specific combinations of genetic variants and their locations on the genome. The encrypted genomic data is fully de-identified, allowing researchers to perform analyses on the encrypted data in a secure Clean Room environment. The environment host is then able to decrypt and deliver variant-level summary statistics and aggregated outputs from the analysis to the recipient. As information in this format no longer links to patient-level data the solution remains de-identified end-to-end.

Navigating the clinical landscape: Update on the diagnostic and prognostic biomarkers in multiple myeloma.

Multiple myeloma, a complex hematologic malignancy, has devastating consequences for patients, including dramatic bone loss, severe bone pain, and pathological fractures that markedly decrease the quality of life and impact the survival of affected patients. This necessitates a refined understanding of biomarkers for accurate diagnosis and prognosis of such severe malignancy. Therefore, this article comprehensively covers current research, elucidating the diverse spectrum of biomarkers employed in clinical settings. From traditional serum markers to advanced molecular profiling techniques, the review provides a thorough examination of their utility and limitations. Through this scoping review, emphasis is placed on the evolving landscape of personalized medicine, where biomarkers play a pivotal role in tailoring therapeutic strategies. The integration of genomic, proteomic, next generation sequencing and flow cytometric data further enriches the discussion, unravelling the molecular intricacies underlying disease progression. The updated criteria allow for the treatment of people who clearly would benefit from therapy and might live longer if treated before significant organ damage occurs. Navigating through the evolving diagnostic and prognostic paradigms in multiple myeloma, this article equips clinicians and researchers with crucial insights for optimizing patient care and advancing future therapeutic approaches.

1288P Clinical impact and landscape of heterogeneous ALK resistance mutations (muts) after comprehensive genomic profiling (CGP)

1288P Clinical impact and landscape of heterogeneous ALK resistance mutations (muts) after comprehensive genomic profiling (CGP)

Onconephrology Fellowship Training: Current Status and Future Outlook.

Onconephrology, an emerging discipline nestled at the intersection of nephrology and oncology, has experienced remarkable growth over the past 15 years. This evolution has been punctuated by pivotal events, including establishing the American Society of Onconephrology, dedicated forums, and journals, highlighting its increasing significance. The clinical landscape of onconephrology is diverse, encompassing AKI in patients with cancer, toxicity from anticancer treatments, and a spectrum of electrolyte disorders, necessitating close collaboration between nephrologists and oncologists. However, trainees and mentors encounter various challenges surrounding its status as a distinct subspecialty. To overcome these barriers, there is a pressing need for streamlined training pathways, enhanced interdisciplinary collaboration, and targeted research efforts to elucidate the effect of onconephrology on patient outcomes. By addressing these challenges head-on, the field of onconephrology can continue its trajectory of growth and better serve patients with cancer with complex kidney needs.

A Review of Current Approaches to Pain Management in Knee Osteoarthritis with a Focus on Italian Clinical Landscape.

The global cases of knee osteoarthritis (KOA) are projected to increase by 74.9% by 2050. Currently, over half of patients remain dissatisfied with their pain relief. This review addresses unmet needs for moderate-to-severe KOA pain; it offers evidence and insights for improved management. Italian experts from the fields of rheumatology, physical medicine and rehabilitation, orthopedics, primary care, and pain therapy have identified several key issues. They emphasized the need for standardized care protocols to address inconsistencies in patient management across different specialties. Early diagnosis is crucial, as cartilage responds better to early protective and structural therapies. Faster access to physiatrist evaluation and reimbursement for physical, rehabilitative, and pharmacological treatments, including intra-articular (IA) therapy, could reduce access disparities. Concerns surround the adverse effects of oral pharmacological treatments, highlighting the need for safer alternatives. Patient satisfaction with corticosteroids and hyaluronic acid-based IA therapies reduces over time and there is no consensus on the optimal IA therapy protocol. Surgery should be reserved for severe symptoms and radiographic KOA evidence, as chronic pain post-surgery poses significant societal and economic burdens. The experts advocate for a multidisciplinary approach, promoting interaction and collaboration between specialists and general practitioners, to enhance KOA care and treatment consistency in Italy.

The clinical landscape of HPV vaccination in preventing and treating cutaneous squamous cell carcinoma

The clinical landscape of HPV vaccination in preventing and treating cutaneous squamous cell carcinoma