Comprehensive characterization of stemness-related lncRNAs in triple-negative breast cancer identified a novel prognostic signature related to treatment outcomes, immune landscape analysis and therapeutic guidance: a silico analysis with in vivo experiments.

BACKGROUND: Cancer stem cells (CSCs) and long non-coding RNAs (lncRNAs) are known to play a crucial role in the growth, migration, recurrence, and drug resistance of tumor cells, particularly in triple-negative breast cancer (TNBC). This study aims to investigate stemness-related lncRNAs (SRlncRNAs) as potential prognostic indicators for TNBC patients. METHODS: Utilizing RNA sequencing data and corresponding clinical information from the TCGA database, and employing Weighted Gene Co-expression Network Analysis (WGCNA) on TNBC mRNAsi sourced from an online database, stemness-related genes (SRGs) and SRlncRNAs were identified. A prognostic model was developed using univariate Cox and LASSO-Cox analysis based on SRlncRNAs. The performance of the model was evaluated using Kaplan-Meier analysis, ROC curves, and ROC-AUC. Additionally, the study delved into the underlying signaling pathways and immune status associated with the divergent prognoses of TNBC patients. RESULTS: The research identified a signature of six SRlncRNAs (AC245100.6, LINC02511, AC092431.1, FRGCA, EMSLR, and MIR193BHG) for TNBC. Risk scores derived from this signature were found to correlate with the abundance of plasma cells. Furthermore, the nominated chemotherapy drugs for TNBC exhibited considerable variability between different risk score groups. RT-qPCR validation confirmed abnormal expression patterns of these SRlncRNAs in TNBC stem cells, affirming the potential of the SRlncRNAs signature as a prognostic biomarker. CONCLUSION: The identified signature not only demonstrates predictive power in terms of patient outcomes but also provides insights into the underlying biology, signaling pathways, and immune status associated with TNBC prognosis. The findings suggest the possibility of guiding personalized treatments, including immune checkpoint gene therapy and chemotherapy strategies, based on the risk scores derived from the SRlncRNA signature. Overall, this research contributes valuable knowledge towards advancing precision medicine in the context of TNBC.

Effectiveness of Tailor-Made Physiotherapy Protocol in Smartphone-Addicted Individuals With Text Neck Syndrome and Short Message Service (SMS) Thumb.

Background Smartphone usage has led to an increase in text neck syndrome (TNS) and short message service (SMS) thumb, causing neck, shoulder, and thumb pain, affecting daily activities. Limited treatment options are available for these conditions, and early intervention is crucial to prevent chronic pain and musculoskeletal issues. This study sought to determine the impact of a personalized physiotherapy treatment plan on alleviating TNS and SMS thumb in individuals who demonstrate excessive smartphone usage. Method The study utilized a single-group, pre- and post-study design with a sample size of 54 smartphone-addicted individuals. The intervention involved a personalized physiotherapy protocol for three weeks, and data was collected using a visual analog scale (VAS), Neck Disability Index (NDI), Smartphone Addiction Scale (SAS), Cornell Hand Discomfort Questionnaire (CHDQ), and range of motion (ROM). Results Descriptive statistics showed a significant reduction in mean scores from pre- to post-rehabilitation, indicating the potential effectiveness of the treatment. Hypothesis testing revealed significant improvements in VAS, NDI, and CHDQ scores post-rehabilitation, with a p-value of <0.05. Correlation analysis demonstrated moderate to strong correlations between pre- and post-rehabilitation scores for VAS, NDI, and CHDQ, with age showing minimal influence on treatment outcomes. Conclusion The findings emphasize the efficacy of personalized interventions in addressing smartphone-related musculoskeletal disorders and underscore the need for further research to optimize treatment protocols and long-term outcomes.

Dose-dependent multi-organ injury following lipopolysaccharide gas inhalation.

Lipopolysaccharide (LPS) is widely used to establish various animal models, including models of acute lung injury, cardiomyocyte damage, and acute kidney injury. Currently, there is no consensus on the diagnosis and treatment of LPS-induced disease. We herein present a case series of four patients who developed dose-dependent multi-organ injury, including acute lung injury and acute kidney injury, after inhaling LPS gas in a sealed room. These patients exhibited varying degrees of multi-organ injury characterized by inflammatory cell infiltration and secretion of proinflammatory cytokines. One patient showed progressive symptoms even with active treatment, leading to mild pulmonary fibrosis. This study emphasizes the importance of early diagnosis and treatment of significant LPS exposure and suggests personalized treatment approaches for managing LPS poisoning.

Needs-based considerations for the role of low-dose aspirin along the CV risk continuum.

Cardiovascular disease (CVD) remains the leading cause of death worldwide. The risk of a cardiovascular (CV) event is not static and increases along a continuum, making identification and management complex. Aspirin has been the cornerstone of antiplatelet therapy in CV risk reduction and remains the only antiplatelet agent with current guideline recommendations throughout the CV risk continuum. In light of recent trials, the role of aspirin in CVD prevention in asymptomatic patients has been downgraded in clinical guidelines. However, a substantial proportion of asymptomatic patients have underlying conditions, such as advanced subclinical atherosclerosis that are associated with high CV risk. Advanced subclinical atherosclerosis has not been extensively investigated in patients in clinical trials but in the absence of significant bleeding risks, patients with subclinical atherosclerosis may particularly benefit from preventive aspirin therapy. Recent studies and clinical guidelines support the need for a personalized treatment approach for these patients, balancing their risk of future CV events against their relative bleeding risk. In this commentary, we first discussed various tools and strategies currently available for assessing CV and bleeding risks; we then provided two hypothetical cases to outline how these tools can be implemented for optimal management of patients with no prior CV events who, nonetheless, are susceptible to CVD. The first case details a young and apparently healthy patient with underlying advanced subclinical atherosclerosis; whereas the second case describes a patient with recently diagnosed type 2 diabetes mellitus who is at higher risk of CVD than their non-diabetic counterparts. For both cases, we considered patient clinical characteristics, CV and bleeding risks, as well as other risk factors to evaluate the appropriate treatment strategy and determine whether patients would obtain a net clinical benefit from low-dose aspirin therapy. These cases can serve as examples to guide clinical decision-making on the use of low-dose aspirin for primary CVD prevention and improve CVD management via a personalized approach.

A machine learning personalized treatment rule to optimize assignment to psychotherapies for grief among veterans.

BACKGROUND: Complex grief patterns are associated with significant suffering, functional impairments, health and mental health problems, and increased healthcare use. This burden may be even more pronounced among veterans. Behavioral Activation and Therapeutic Exposure (BATE-G) and Cognitive Therapy for Grief (CT-G) are two evidence-based interventions for grief. The goal of this study was to use a precision medicine approach to develop a personalized treatment rule to optimize assignment among these psychotherapies. METHODS: We analyzed data (N = 155) from a randomized clinical trial comparing BATE-G and CT-G. Outcome weighted learning was used to estimate an optimal personalized treatment rule. Baseline characteristics including demographics, social support, variables related to the death, and psychopathology dimensions were used as prescriptive factors of treatment assignment. RESULTS: The estimated rule assigned 72 veterans to CT-G and 56 to BATE-G. Assigning participants according to this rule was estimated to lead to markedly lower mean grief level following 6 months from treatment compared to assigning everyone to either BATE-G (Vdopt - VBATE-G = -18.57 [95 % CI: (-29.41, -7.72)]) or CT-G (Vdopt - VBATE-G = -20.89 [95 % CI: (-30.7, -11.07)]) regardless of their characteristics. LIMITATIONS: Participants were primarily male veterans, and identified with Black or White race. The estimated rule was not externally validated. CONCLUSION: The estimated rule used relatively simple, easily accessible, client characteristics to personalize assignment to treatment using a precision medicine approach based on machine learning and causal inference. Upon further validation, such a rule can be easily implemented in clinical practice to prescriptively maximize treatment benefits.

The cellular composition of chronic subdural hematoma.

INTRODUCTION: The pathophysiology of chronic subdural hematoma (CSDH) remains to be fully understood. Basic knowledge of the composition and features of cells in the CSDH fluid may contribute to the understanding of the seemingly complex processes involved in CSDH formation and recurrence. This study is the first to examine the composition of cells and of cellular features in both systemic blood and subdural fluid from CSDH patients. We hypothesized that the cellular composition and features in the hematoma fluid may be; 1) different from that in the systemic blood; 2) different between patients with and without recurrence; 3) and different between the first and second operation in patients with recurrent CSDH. METHODS: Systemic blood and subdural hematoma fluid were collected from CSDH patients with and without recurrent CSDH at the time of primary and secondary surgery. Analyses of cells and cellular features included total number of white blood cells, erythroblasts, reticulocytes, platelets, neutrophilocytes, lymphocytes, monocytes, eosinophils, basophils, reticulocytes, immature granulocytes, mean corpuscular cell volume (MCV), mean corpuscular hemoglobin, mean corpuscular hemoglobin concentration, hemoglobin and hematocrit. RESULTS: Of the 85 included patients, 20 patients were operated for a recurrent CSDH within 90 days follow-up. All cells found in the systemic blood were present in the CSDH fluid, but the composition was different (p < 0.0001). MCV was higher in the hematoma fluid from the primary operation of patients later developing a recurrent CSDH compared to patients not developing recurrence (p = 0.009). Also, the percentage distribution of inflammatory cells in hematoma fluid from patients with recurrent CSDH was different between the first and second operation (p = 0.0017). CONCLUSION: This study is the first to investigate the cellular composition of CSDH fluid. Compared to systemic blood and to a reference distribution, an increased number of immune cells were present in the hematoma fluid, supporting an inflammatory component of the CSDH pathophysiology. MCV was higher in the subdural fluid at time of the first operation of CSDH patients later developing recurrence. CLINICAL TRIAL REGISTRATION: The study was approved by the Scientific Ethical Committee of the Capital Region of Denmark (Journal no. H-20051073.

Insights Into Colorectal Carcinoma: A Comprehensive Review of MicroRNA Expression Patterns.

Colorectal carcinoma (CRC) remains a significant contributor to cancer-related morbidity and mortality worldwide. MicroRNAs (miRNAs) have emerged as crucial regulators of gene expression and play critical roles in various biological processes, including carcinogenesis. This comprehensive review aims to elucidate the role of miRNAs in CRC by analyzing their expression patterns and functional implications. An extensive literature review identified dysregulated miRNAs associated with different stages of CRC progression, from initiation to metastasis. These miRNAs modulate key signaling pathways in tumor growth, invasion, and metastasis. Furthermore, we discuss the potential of miRNAs as diagnostic biomarkers and therapeutic targets in CRC management. Future research directions include elucidating the functional significance of dysregulated miRNAs using advanced experimental models and computational approaches and exploring the therapeutic potential of miRNA-based interventions in personalized treatment strategies for CRC patients. Collaboration among researchers, clinicians, and industry partners will be essential to translate these findings into clinically impactful interventions that improve patient outcomes in CRC.

Genetic Signature of Human Pancreatic Cancer and Personalized Targeting.

Pancreatic cancer is a highly lethal disease with a 5-year survival rate of around 11-12%. Surgery, being the treatment of choice, is only possible in 20% of symptomatic patients. The main reason is that when it becomes symptomatic, IT IS the tumor is usually locally advanced and/or has metastasized to distant organs; thus, early diagnosis is infrequent. The lack of specific early symptoms is an important cause of late diagnosis. Unfortunately, diagnostic tumor markers become positive at a late stage, and there is a lack of early-stage markers. Surgical and non-surgical cases are treated with neoadjuvant and/or adjuvant chemotherapy, and the results are usually poor. However, personalized targeted therapy directed against tumor drivers may improve this situation. Until recently, many pancreatic tumor driver genes/proteins were considered untargetable. Chemical and physical characteristics of mutated KRAS are a formidable challenge to overcome. This situation is slowly changing. For the first time, there are candidate drugs that can target the main driver gene of pancreatic cancer: KRAS. Indeed, KRAS inhibition has been clinically achieved in lung cancer and, at the pre-clinical level, in pancreatic cancer as well. This will probably change the very poor outlook for this disease. This paper reviews the genetic characteristics of sporadic and hereditary predisposition to pancreatic cancer and the possibilities of a personalized treatment according to the genetic signature.

Risk-Tailoring Radiotherapy for Endometrial Cancer: A Narrative Review.

Endometrial cancer is the most common gynecologic cancer in the United States and it contributes to the second most gynecologic cancer-related deaths. With upfront surgery, the specific characteristics of both the patient and tumor allow for risk-tailored treatment algorithms including adjuvant radiotherapy and systemic therapy. In this narrative review, we discuss the current radiation treatment paradigm for endometrial cancer with an emphasis on various radiotherapy modalities, techniques, and dosing regimens. We then elaborate on how to tailor radiotherapy treatment courses in combination with other cancer-directed treatments, including chemotherapy and immunotherapy. In conclusion, this review summarizes ongoing research that aims to further individualize radiotherapy regimens for individuals in an attempt to improve patient outcomes.

The Impact of Adjunct Medical Therapy on Survival after Spine Metastasis: A Systematic Review and Pooled Data Analysis.

Targeted therapy has greatly improved the outlook for patients with spinal metastatic cancers. Scoring systems like the Tokuhashi or Tomita scores are commonly used to predict prognosis and inform surgical decisions, but they are outdated and fail to consider recent advancements. We aimed to investigate the current state of the literature and treatment options pertaining to advancements in targeted therapy compared to other forms of medical management for metastatic spinal tumors. This study represents the first comprehensive systematic review that encompasses the most common primary cancers that metastasize to the spine and evaluates the median overall survival (mOS) across five different medical treatment modalities as well as surgical intervention. Additionally, our study analyzes the tumor receptor status in conjunction with these treatments. A PubMed search was conducted, and according to the PRISMA guidelines, 28 articles out of 1834 met the inclusion criteria. The pooled data analysis highlighted the superior efficacy of targeted therapy, evidenced by a significant improvement in the mOS and lower hazard ratios in patients with lung and breast cancers who received targeted therapy compared to those who did not. Our study provides valuable insights into the recent advancements in the medical management of metastatic spinal tumors. Future indications include incorporating this literature into personalized treatment approaches for metastatic spinal tumors.

Nanomaterial Delivery Vehicles for the Development of Neoantigen Tumor Vaccines for Personalized Treatment.

Tumor vaccines have been considered a promising therapeutic approach for treating cancer in recent years. With the development of sequencing technologies, tumor vaccines based on neoantigens or genomes specifically expressed in tumor cells, mainly in the form of peptides, nucleic acids, and dendritic cells, are beginning to receive widespread attention. Therefore, in this review, we have introduced different forms of neoantigen vaccines and discussed the development of these vaccines in treating cancer. Furthermore, neoantigen vaccines are influenced by factors such as antigen stability, weak immunogenicity, and biosafety in addition to sequencing technology. Hence, the biological nanomaterials, polymeric nanomaterials, inorganic nanomaterials, etc., used as vaccine carriers are principally summarized here, which may contribute to the design of neoantigen vaccines for improved stability and better efficacy.

Case report: Avoiding intolerance to antipsychotics through a personalized treatment approach based on pharmacogenetics.

Introduction: The standard approach to treatment in psychiatry is known as "treatment as usual" (TAU), in which the same types of treatment are administered to a group of patients. TAU often requires numerous dose adjustments and medication changes due to ineffectiveness and/or the occurrence of adverse drug reactions (ADRs). This process is not only time-consuming but also costly. Antipsychotic medications are commonly used to treat various psychiatric disorders such as schizophrenia and mood disorders. Some of the inter-individual differences in efficacy and ADRs observed in psychopharmacotherapy can be explained by genetic variability in the pharmacokinetics and pharmacodynamics of antipsychotics. A better understanding of (in)efficacy and possible ADRs can be achieved by pharmacogenetic analysis of genes involved in the metabolism of antipsychotics. Most psychotropic drugs are metabolized by genetically variable CYP2D6, CYP1A2, CYP3A4, and CYP2C19 enzymes. To demonstrate the utility of pharmacogenetic testing for tailoring antipsychotic treatment, in this paper, we present the case of a patient in whom a pharmacogenetic approach remarkably altered an otherwise intolerant or ineffective conventional TAU with antipsychotics. Methods: In this case report, we present a 60-year-old patient with psychotic symptoms who suffered from severe extrapyramidal symptoms and a malignant neuroleptic syndrome during treatment with risperidone, fluphenazine, aripiprazole, brexpiprazole, and olanzapine. Therefore, we performed a pharmacogenetic analysis by genotyping common functional variants in genes involved in the pharmacokinetic pathways of prescribed antipsychotics, namely, CYP2D6, CYP3A4, CYP3A5, CYP1A2, ABCB1, and ABCG2. Treatment recommendations for drug-gene pairs were made according to available evidence-based pharmacogenetic recommendations from the Dutch Pharmacogenetics Working Group (DPWG) or Clinical Pharmacogenetics Implementation Consortium (CPIC). Results: Pharmacogenetic testing revealed a specific metabolic profile and pharmacokinetic phenotype of the patient, which in retrospect provided possible explanations for the observed ADRs. Based on the pharmacogenetic results, the choice of an effective and safe medication proved to be much easier. The psychotic symptoms disappeared after treatment, while the negative symptoms persisted to a lesser extent. Conclusion: With the case presented, we have shown that taking into account the pharmacogenetic characteristics of the patient can explain the response to antipsychotic treatment and associated side effects. In addition, pharmacogenetic testing enabled an informed choice of the most appropriate drug and optimal dose adjustment. This approach makes it possible to avoid or minimize potentially serious dose-related ADRs and treatment ineffectiveness. However, due to the complexity of psychopathology and the polypharmacy used in this field, it is of great importance to conduct further pharmacokinetic and pharmacogenetic studies to better assess gene-drug and gene-gene-drug interactions.

Neuropsychiatric Aspects of Sotos Syndrome: Explorative Review Building Multidisciplinary Bridges in Clinical Practice.

Background: Sotos syndrome is a genetic disorder caused by NSD1 gene (nuclear receptor binding SET domain containing protein 1) variants and characterized by overgrowth, macrocephaly, learning disabilities, and co-occurring neuropsychiatric symptoms. Methods: Literature sources published in 2002-2023 were selected and analyzed from PubMed and Google Scholar databases. Results: Neuropsychiatric symptoms are observed among children and adolescents with Sotos syndrome. The majority have intellectual disabilities or borderline intellect. Verbal IQ is higher than performance IQ. Individuals display difficulties in expressing language. Aggression is reported by parents. Children express autistic behavior, ADHD, anxiety based on phobias, and early bedtime-wake times. Conclusions: Sotos syndrome is associated with neuropsychiatric disorders in children. Slow intellectual and language development, aggressive outbursts, anxiety, autism spectrum disorder, and hyperactivity are present in the newest studies. Comprehensive assistance is needed for Sotos syndrome patients in responding to areas of difficulty. There is still a lack of research on the developmental characteristics of these children and the possibilities of improving psychosocial adaptation by providing multidisciplinary long-term medical, educational, and social care.

Prognostic Cell Death Index for Lung Adenocarcinoma: A Comprehensive Transcriptome-Based Analysis of Twelve Programmed Cell Death Pattern Genes.

OBJECTIVE: Lung adenocarcinoma (LUAD) is a prominent contributor to global cancer mortality, characterized by constrained prognosis. This study aimed to develop a novel prognostic indicator, the Cell Death Index (CDI), utilizing twelve programmed cell death (PCD) pattern genes, to predict the immune infiltration and prognosis in LUAD patients. METHODS: We collected PCD-related genes and identified prognostic PCD genes in the Cancer Genome Atlas (TCGA)-LUAD dataset, and made rigorous validation in the Clinical Proteomic Tumor Analysis Consortium (CPTAC)-LUAD cohorts. CDI was calculated using a multivariable Cox regression model. Functional enrichment and tumor microenvironment were evaluated. Drug sensitivity prediction and nomogram development were performed to assess CDI's potential value. RESULTS: The results revealed 10 PCD genes (ERO1A, CDK5R1, TRIM6, DNASE2B, ITPRIP, MRGPRX2, FGA, NDUFA13, NLRP2, and CD68) significantly associated with LUAD prognosis. The CDI was constructed and showed high accuracy in predicting patient survival with C-index values of 0.801 and 0.794 in the prognosis cohort and validation cohort, respectively. CDI is also indicative of variations in biological functions, tumor microenvironment, and immune cell infiltration including neutrophils, activated mast cells, activated dendritic cells, M0 macrophages, resting natural killer cells, γδT cells, and activated memory CD4+T cells. Furthermore, drug sensitivity analysis indicated potential targeted strategies. CONCLUSIONS: The CDI, based on PCD genes, serves as a robust prognostic tool for LUAD, offering profound insights into tumor biology, immune response, and personalized treatment strategies. This study underscores the pivotal role of PCD mechanisms in LUAD pathogenesis and identifies potential therapeutic targets.

Racial and socioeconomic disparities in triple-negative breast cancer treatment.

INTRODUCTION: Triple-negative breast cancer (TNBC) continues to be a significant concern, especially among minority populations, where treatment disparities are notably pronounced. Addressing these disparities, especially among African American women and other minorities, is crucial for ensuring equitable healthcare. AREAS COVERED: This review delves into the continuum of TNBC treatment, noting that the standard of care, previously restricted to chemotherapy, has now expanded due to emerging clinical trial results. With advances like PARP inhibitors, immunotherapy, and antibody-drug conjugates, a more personalized treatment approach is on the horizon. The review highlights innovative interventions tailored for minorities, such as utilizing technology like text messaging, smartphone apps, and targeted radio programming, coupled with church-based behavioral interventions. EXPERT OPINION: Addressing TNBC treatment disparities demands a multifaceted approach, blending advanced medical treatments with culturally sensitive community outreach. The potential of technology, especially in the realm of promoting health awareness, is yet to be fully harnessed. As the field progresses, understanding and integrating the socio-economic, biological, and access-related challenges faced by minorities will be pivotal for achieving health equity in TNBC care.

Perspectives on the impact of vortioxetine on the treatment armamentarium of major depressive disorder.

INTRODUCTION: Major Depressive Disorder (MDD) is a mental health issue that significantly affects patients' quality of life and functioning. Despite available treatments, many patients continue to suffer due to incomplete symptom resolution and side effects. AREAS COVERED: This manuscript examines Vortioxetine's role in Major Depressive Disorder (MDD) treatment, highlighting its potential to reshape therapeutic strategies due to its unique Multimodal action and proven broad-spectrum efficacy in multiple depressive domains. A detailed examination of Vortioxetine's pharmacological aspects, including indications, dosage, pharmacodynamics, and pharmacokinetics, is provided, emphasizing its safety and effectiveness. The discussion extends to Vortioxetine's role in acute-phase treatment and maintenance of MDD and its profound impact on specialized depression domains. EXPERT OPINION: Vortioxetine is distinguished for its novel multimodal serotonin modulation mechanism, showcasing significant promise as an innovative treatment for MDD. Its efficacy, which is dose-dependent, along with a commendable tolerability profile, positions it as a potential leading option for initial treatment strategies. The discourse on dosage titration, particularly the strategy of initiating treatment at lower doses followed by gradual escalation, underscores the approach toward minimizing initial adverse effects while optimizing therapeutic outcomes, aligning with the principles of personalized medicine in psychiatric care.

In-vitro assays for immuno-oncology drug efficacy assessment and screening for personalized cancer therapy: scopes and challenges.

INTRODUCTION: Immunotherapies have revolutionized cancer treatment, but often fail to produce desirable therapeutic outcomes in all patients. Due to the inter-patient heterogeneity and complexity of the tumor microenvironment, personalized treatment approaches are gaining demand. Researchers have long been using a range of in-vitro assays including 2D models, organoid co-cultures, and cancer-on-a-chip platforms for cancer drug screening. A comparative analysis of these assays with their suitability, high-throughput capacity, and clinical translatability is required for optimal translational use. AREAS COVERED: The review summarized in-vitro platforms with their comparative advantages and limitations including construction strategies, and translational potential for immuno-oncology drug efficacy assessment. We also discussed end-point analysis strategies so that researchers can contextualize their usefulness and optimally design experiments for personalized immunotherapy efficacy prediction. EXPERT OPINION: Researchers developed several in-vitro platforms that can provide information on personalized immunotherapy efficacy from different angles. Image-based assays are undoubtedly more suitable to gather a wide range of information including cellular morphology and phenotypical behaviors but need significant improvement to overcome issues including background noise, sample preparation difficulty, and long duration of experiment. More studies and clinical trials are needed to resolve these issues and validate the assays before they can be used in real-life scenarios.

Oncotype DX in Breast Cancer Management: Insights and Outcomes From the United Arab Emirates.

Introduction Breast cancer remains the most significant cancer affecting women worldwide, with an increasing incidence, especially in developing regions. The introduction of genomic tests like Oncotype DX has revolutionized personalized treatment, allowing for more tailored approaches to therapy. This study focuses on the United Arab Emirates (UAE), where breast cancer is the leading cause of cancer-related deaths among women, aiming to assess the predictive accuracy of the Oncotype DX test in categorizing patients based on recurrence risk. Materials and methods A retrospective cohort study was conducted on 95 breast cancer patients diagnosed at Tawam Hospital between 2013 and 2017 who underwent Oncotype DX testing. Data on patient demographics, tumor characteristics, treatment details, and Oncotype DX scores were collected. Survival analysis was performed using the Kaplan-Meier method, with the chi-square goodness of fit test assessing the model's adequacy. Results The cohort's age range was 27-71 years, with a mean age of 50, indicating a significant concentration of cases in the early post-menopausal period. The Oncotype DX analysis classified 55 patients (57.9%) as low risk, 29 (30.5%) as medium risk, and 11 (11.6%) as high risk of recurrence. The majority, 73 patients (76.8%), did not receive chemotherapy, highlighting the test's impact on treatment decisions. The survival analysis revealed no statistically significant difference in recurrence rates across the Oncotype DX risk categories (p = 0.268231). Conclusion The Oncotype DX test provides a valuable genomic approach to categorizing breast cancer patients by recurrence risk in the UAE. While the test influences treatment decisions, particularly the use of chemotherapy, this study did not find a significant correlation between Oncotype DX risk categories and actual recurrence events. These findings underscore the need for further research to optimize the use of genomic testing in the UAE's diverse patient population and enhance personalized treatment strategies in breast cancer management.

Exploring the application and future outlook of Artificial intelligence in pancreatic cancer.

Pancreatic cancer, an exceptionally malignant tumor of the digestive system, presents a challenge due to its lack of typical early symptoms and highly invasive nature. The majority of pancreatic cancer patients are diagnosed when curative surgical resection is no longer possible, resulting in a poor overall prognosis. In recent years, the rapid progress of Artificial intelligence (AI) in the medical field has led to the extensive utilization of machine learning and deep learning as the prevailing approaches. Various models based on AI technology have been employed in the early screening, diagnosis, treatment, and prognostic prediction of pancreatic cancer patients. Furthermore, the development and application of three-dimensional visualization and augmented reality navigation techniques have also found their way into pancreatic cancer surgery. This article provides a concise summary of the current state of AI technology in pancreatic cancer and offers a promising outlook for its future applications.