Variability In Treatment Response Research Articles

Patients carrying pathogenic SCN8A variants with loss‐ and gain‐of‐function effects can be classified into five subgroups exhibiting varying developmental and epileptic components of encephalopathy

AbstractObjectivePhenotypic heterogeneity presents challenges in providing clinical care to patients with pathogenic SCN8A variants, which underly a wide disease spectrum ranging from neurodevelopmental delays without seizures to a continuum of mild to severe developmental and epileptic encephalopathies (DEEs). An important unanswered question is whether there are clinically important subgroups within this wide spectrum. Using both supervised and unsupervised machine learning (ML) approaches, we previously found statistical support for two and three subgroups associated with loss‐ and gain‐ of‐ function vari‐ants, respectively. Here, we test the hypothesis that the unsupervised subgroups (U1–U3) are distinguished by differential contributions of developmental and epileptic components.MethodsWe predicted that patients in the U1 and U2 subgroups would differ in timing of developmental delay and seizure onset, with earlier and concurrent onset of both features for the U3 subgroup. Standard statistical procedures were used to test these predictions, as well as to investigate clinically relevant associations among all five subgroups.ResultsTwo‐population proportion and Kruskal–Wallis tests supported the hypothesis of a reversed order of developmental delay and seizure onset for patients in U1 and U2, and nearly synchronous developmental delay/seizure onset for the U3 (termed DEE) subgroup. Association testing identified subgroup variation in treatment response, frequency of initial seizure type, and comorbidities, as well as different median ages of developmental delay onset for all five subgroups.SignificanceUnsupervised ML approaches discern differential developmental and epileptic components among patients with SCN8A‐related epilepsy. Patients in U1 (termed developmental encephalopathy) typically gain seizure control yet rarely experience improvements in development, whereas those in U2 (termed epileptic encephalopathy) have fewer if any developmental impairments despite difficulty in achieving seizure control. This understanding improves prognosis and clinical management and provides a framework to discover mechanisms underlying variability in clinical outcome of patients with SCN8A‐related disorders.

Obesity-Related Ciliopathies: Focus on Advances of Biomarkers.

Obesity-related ciliopathies, as a group of ciliopathies including Alström Syndrome and Bardet-Biedl Syndrome, exhibit distinct genetic and phenotypic variability. The understanding of these diseases is highly significant for understanding the functions of primary cilia in the human body, particularly regarding the relationship between obesity and primary cilia. The diagnosis of these diseases primarily relies on clinical presentation and genetic testing. However, there is a significant lack of research on biomarkers to elucidate the variability in clinical manifestations, disease progression, prognosis, and treatment responses. Through an extensive literature review, the paper focuses on obesity-related ciliopathies, reviewing the advancements in the field and highlighting the potential roles of biomarkers in the clinical presentation, diagnosis, and prognosis of these diseases.

Stratifying heart failure patients with graph neural network and transformer using Electronic Health Records to optimize drug response prediction.

Heart failure (HF) impacts millions of patients worldwide, yet the variability in treatment responses remains a major challenge for healthcare professionals. The current treatment strategies, largely derived from population based evidence, often fail to consider the unique characteristics of individual patients, resulting in suboptimal outcomes. This study aims to develop computational models that are patient-specific in predicting treatment outcomes, by utilizing a large Electronic Health Records (EHR) database. The goal is to improve drug response predictions by identifying specific HF patient subgroups that are likely to benefit from existing HF medications. A novel, graph-based model capable of predicting treatment responses, combining Graph Neural Network and Transformer was developed. This method differs from conventional approaches by transforming a patient's EHR data into a graph structure. By defining patient subgroups based on this representation via K-Means Clustering, we were able to enhance the performance of drug response predictions. Leveraging EHR data from 11627 Mayo Clinic HF patients, our model significantly outperformed traditional models in predicting drug response using NT-proBNP as a HF biomarker across five medication categories (best RMSE of 0.0043). Four distinct patient subgroups were identified with differential characteristics and outcomes, demonstrating superior predictive capabilities over existing HF subtypes (best mean RMSE of 0.0032). These results highlight the power of graph-based modeling of EHR in improving HF treatment strategies. The stratification of patients sheds light on particular patient segments that could benefit more significantly from tailored response predictions. Longitudinal EHR data have the potential to enhance personalized prognostic predictions through the application of graph-based AI techniques.

SingleNucleotide Polymorphisms as Biomarkers of Mepolizumab and Benralizumab Treatment Response in Severe Eosinophilic Asthma.

The most promising treatment options for severe uncontrolled asthma (SUA) have emerged in recent years with the development of monoclonal antibodies for blocking selective targets responsible for the underlying inflammation, such as mepolizumab and benralizumab. However, there is variability in treatment response that is not fully controlled. The variability of the response to mepolizumab and benralizumab could be influenced by single-nucleotide polymorphisms (SNPs), and it would be useful to detect these and use them as predictive biomarkers of response. We conducted a retrospective observational cohort study of 72 Caucasian patients recruited from a tertiary hospital with severe uncontrolled eosinophilic asthma treated with mepolizumab and benralizumab. Polymorphisms in the IL5 (rs4143832, rs17690122), RAD50 (rs11739623, rs4705959), IL1RL1 (rs1420101, rs17026974, rs1921622), GATA2 (rs4857855), IKZF2 (rs12619285), FCGR2A (rs1801274), FCGR2B (rs3219018, rs1050501), FCGR3A (rs10127939, rs396991), FCER1A (rs2251746, rs2427837), FCER1B (rs1441586, rs573790, rs569108), and ZNF415 (rs1054485) genes were analyzed by real-time polymerase chain reaction (PCR) using Taqman probes. The response was analyzed after 12 months of treatment. In patients under mepolizumab treatment, a treatment response defined as a reduction in exacerbations was associated with ZNF415 rs1054485-T (p = 0.042; OR = 5.33; 95% CI = 1.06-30.02), treatment response defined as a reduction in oral corticosteroids use was associated with the number of exacerbations in the previous year (p = 0.029; OR = 3.89; 95% CI = 1.24-14.92), and treatment response defined as improvement in lung function was associated with the age at the beginning of biological therapy (p = 0.002; OR = 1.10; 95% CI = 1.04-1.18), FCER1B rs569108-AA (p < 0.001; OR = 171.06; 95% CI = 12.94-6264.11), and FCER1A rs2427837-A (p = 0.021; OR = 8.61; 95% CI = 1.71-76.62). On the other hand, in patients under benralizumab treatment, treatment response, defined as a reduction in exacerbations, was associated with ZNF415 rs1054485-T (p = 0.073; OR = 1.3 × 108; 95% CI = 1.8 × 10-19-NA), FCER1B rs569108-AA (p = 0.050; OR = 11.51; 95% CI = 1.19-269.78), allergies (p = 0.045; OR = 4.02; 95% CI = 1.05-16.74), and sex (p = 0.028; OR = 4.78; 95% CI = 1.22-20.63); and treatment response defined as improvement in lung function was associated with polyposis (p = 0.027; OR = 9.16; 95% CI = 1.58-91.4), IKZF2 rs12619285-AA (p = 0.019; OR = 9.1; 95% CI = 1.7-75.78), IL5 rs4143832-T (p = 0.017; OR = 11.1; 95% CI = 1.9-112.17), and FCER1B rs1441586-C (p = 0.045; OR = 7.81; 95% CI = 1.16-73.45). The results of this study show the potential influence of the studied polymorphisms on the response to mepolizumab and benralizumab and the clinical benefit that could be obtained by defining predictive biomarkers of treatment response.

Radiomics in Oesogastric Cancer: Staging and Prediction of Preoperative Treatment Response: A Narrative Review and the Results of Personal Experience.

Oesophageal, gastroesophageal, and gastric malignancies are often diagnosed at locally advanced stage and multimodal therapy is recommended to increase the chances of survival. However, given the significant variation in treatment response, there is a clear imperative to refine patient stratification. The aim of this narrative review was to explore the existing evidence and the potential of radiomics to improve staging and prediction of treatment response of oesogastric cancers. The references for this review article were identified via MEDLINE (PubMed) and Scopus searches with the terms "radiomics", "texture analysis", "oesophageal cancer", "gastroesophageal junction cancer", "oesophagogastric junction cancer", "gastric cancer", "stomach cancer", "staging", and "treatment response" until May 2024. Radiomics proved to be effective in improving disease staging and prediction of treatment response for both oesophageal and gastric cancer with all imaging modalities (TC, MRI, and 18F-FDG PET/CT). The literature data on the application of radiomics to gastroesophageal junction cancer are very scarce. Radiomics models perform better when integrating different imaging modalities compared to a single radiology method and when combining clinical to radiomics features compared to only a radiomics signature. Radiomics shows potential in noninvasive staging and predicting response to preoperative therapy among patients with locally advanced oesogastric cancer. As a future perspective, the incorporation of molecular subgroup analysis to clinical and radiomic features may even increase the effectiveness of these predictive and prognostic models.

Immunotherapies: A Treasure Trove of Alzheimer's Disease.

Alzheimer's disease (AD) is a progressive neurodegenerative disease that falls under the umbrella of dementia and is characterized by the presence of enormously neurotoxic amyloid-beta (Aβ) plaques and neurofibrillary tangles (NFTs) of tau protein inside the brain. AD remains an intractable global health challenge with limited therapeutic options. Early diagnosis, enabled by biomarkers and neuroimaging, is pivotal for optimizing treatment outcomes. Immunotherapeutic strategies, including monoclonal antibodies, active vaccination, and passive immunization, have been developed to target hallmark AD pathology, such as amyloid-beta aggregation. Here we summarized the emerging role of immunotherapies in the early stages of AD, shedding light on recent breakthroughs and clinical progress. Challenges, including treatment response variability and safety concerns, are discussed alongside evolving approaches, such as personalized immunotherapy and combinatorial treatments. This concise review underscores the promise of immunotherapies as a transformative approach to AD intervention, offering hope for a brighter future in the quest to combat this devastating neurodegenerative disease.

Familial Arteriovenous Malformation in Extremity: A Case Report

Arteriovenous malformation (AVM) is a genetic vascular anomaly that can significantly affect daily activities. Its occurrence varies by race and gender, being more common in women. This report examines AVM in two siblings, aged 12 and 14. Clinical, radiological, and pathological evaluations revealed differing tumor sizes, expansions, and causes of vascular enlargement. Consequently, the siblings received different treatments: one underwent embolization, while the other had a wide excision. Both approaches resulted in favorable outcomes. AVM is a vascular neoplasm that may present at birth or be discovered later, often during routine check-ups or after trauma. The familial nature of AVM in this case emphasizes the variability in presentation and treatment response. Established diagnostic and therapeutic guidelines may not always be applicable, necessitating individualized treatment plans. This case highlights the importance of tailored treatment approaches for familial AVM, demonstrating successful outcomes with both embolization and wide excision

Dose-exposure-efficacy response of intravenous immunoglobulin G 10% in multifocal motor neuropathy.

Multifocal motor neuropathy is a rare chronic immune-mediated neuropathy with impaired grip strength representing a common symptom. While intravenous immunoglobulin G is an effective treatment for the disease, significant variation in treatment response has been observed but not well understood. This analysis characterized dose-exposure-response relationships in multifocal motor neuropathy, using grip strength as a clinical efficacy measure. Serum immunoglobulin G trough concentrations and grip strength data for the more affected hand from a Phase 3, randomized, double-blind, placebo-controlled, crossover trial of intravenous immunoglobulin 10% in 44 patients with multifocal motor neuropathy (NCT00666263) were used to develop a population pharmacokinetic-pharmacodynamic model. The model adequately described the observed pharmacokinetic and pharmacodynamic data and relationships between intravenous immunoglobulin 10% dose, serum immunoglobulin G trough levels, grip strength, and inter-patient variabilities in multifocal motor neuropathy. Model-based simulations for various dosing regimens (0.4-2.0 g/kg every 2-4 weeks) indicated that ≥1.6 g/kg/month would achieve clinically meaningful improvements in grip strength (≥4 kg) in ≥70% of patients. More frequent dosing at an equivalent monthly dose led to a more consistent response in grip strength. Furthermore, splitting the dose over multiple days for high doses (>1 g/kg) did not impact grip strength. These findings suggest that the majority of patients with multifocal motor neuropathy would respond rapidly to intravenous immunoglobulin 10% with a range of dosing regimens. Shorter dosing intervals may avoid the diminishing response seen with longer dosing intervals. Dose-splitting provided similar outcomes while offering flexibility and convenience.

Coexistence of BCR∷ABL1 translocation and JAK2V617F mutations in indian patients with myeloproliferative neoplasms: A case series.

BCR∷ABL1 translocation and JAK2V617F mutations are canonical variants of myeloproliferative neoplasms (MPNs). Traditionally considered mutually exclusive, they may rarely coexist. We report the clinicopathological profile and treatment outcomes of four MPN patients with coexistence of these disease-defining genetic variants. Both mutations were detected simultaneously in three patients who did not harbor tell-tale signs of CML and were evaluated for both BCR∷ABL1 and JAK2V617F based on clues from hemogram, peripheral-blood and bone-marrow examination. All were treated with imatinib and hydroxyurea and attained major molecular response after 2-7 months. In another patient, JAK2V617F was detected 15 years after the diagnosis of CML at the time of evaluation of loss of hematological and molecular response. She was treated with dasatinib but no hematologic or molecular response was attained after 6 months despite good compliance. In conclusion, BCR∷ABL1 and JAK2V617F may rarely coexist in MPN with variable temporal evolution, clinicopathological profile, and treatment response.

Assessment of ocrelizumab impact on neurofilament levels in multiple sclerosis patients

Abstract Background Multiple sclerosis (MS) is a debilitating neurological disease characterized by inflammation, demyelination, and neurodegeneration in the central nervous system. Despite extensive research, the pathology of MS remains incompletely understood. Ocrelizumab (OCRE), a monoclonal antibody targeting CD20-positive B cells, has shown efficacy in relapsing (RR) and primary progressive (PP) MS. Neurofilaments (Nf) are emerging biomarkers of neuroaxonal injury, reflecting disease activity and treatment response in MS. This study aimed to assess the impact of OCRE on serum Nf levels (NfLs) in RRMS and PPMS patients and explore factors influencing treatment response. Methods A prospective study included 23 RRMS and PPMS patients initiating OCRE and 23 healthy controls. Serum NfLs were quantified using ELISA. Statistical analyses evaluated changes in NfLs and factors influencing treatment response. Results MS patients exhibited significantly higher NfLs than controls. OCRE treatment led to a significant reduction in NfLs after one cycle. Age and gender influenced treatment response, with older patients and females experiencing greater NfL reduction. Disability level and disease duration did not significantly affect NfLs reduction. Both RRMS and PPMS patients showed decreased NfLs levels with OCRE treatment. Conclusions In conclusion, OCRE demonstrated efficacy in reducing NfLs levels in RRMS and PPMS patients after one cycle, with potential age and gender-related variations in treatment response. Larger longitudinal studies are needed to further elucidate OCRE’s mechanisms and implications for personalized MS treatment.

A Study on Optimal Frequency and Duration of PRP in Androgenic Alopecia

Background: Platelet-rich plasma (PRP) therapy has emerged as a promising treatment for androgenetic alopecia (AA), addressing the need for effective hair restoration with minimal invasiveness. However, questions remain regarding the optimal frequency and duration of PRP treatment. Objective: This study aimed to assess the impact of PRP therapy on hair density and diameter in AGA patients, considering variations in treatment response across different AGA grades and alopecia durations. Method: A 6-month open-labeled pilot study was conducted on 30 male participants with AGA Grades III-VII. PRP was administered every 15 days for six sessions, and hair parameters were evaluated using trichoscan. Results: The study demonstrated a significant increase in both hair diameter and density over six months of platelet-rich plasma (PRP) therapy for androgenetic alopecia (AGA). Initially, the mean hair diameter was 0.055 mm, rising to 0.075 mm by the study's end, with a substantial increase of 0.021 mm at six months, equating to a 39.85% improvement. Similarly, hair density increased notably from 6.13 to 8.43 hairs per 10 mm², with the most significant rise at the six-month mark, showing a mean increase of 2.3 hairs per 10 mm², reflecting a 39.73% enhancement. All AGA grades experienced increased hair diameter and density, with Grade 5 showing the highest diameter increase (0.03 mm), and Grade 4A exhibiting the highest density increase (3.0 hairs per 10 mm²). Statistical analysis confirmed significant improvements across all grades (p = 0.0446 for diameter; p = 0.0196 for density). Additionally, patients with alopecia durations up to five years experienced the highest improvements in both diameter (0.026 mm) and density (2.68 hairs per 10 mm²), while longer durations showed lower enhancements (p = 0.0485 for diameter; p = 0.0096 for density). Conclusion: PRP therapy demonstrated efficacy across all AGA grades and durations, suggesting its potential as a promising treatment option for AGA. Further research is needed to validate these findings and establish PRP therapy as a standard AGA treatment.

IMG-11. RADIOGENOMIC ANALYSIS INFORMS ON IMMUNOLOGICAL PROFILES, PROGNOSIS, AND TREATMENT RESPONSE IN PEDIATRIC LOW-GRADE GLIOMA

Abstract BACKGROUND Pediatric low-grade gliomas (pLGGs) have variable prognosis and treatment responses. Complete resection cannot be achieved for all tumors, especially for highly infiltrative or deep-seated tumors, necessitating additional therapy, from chemotherapy to targeted inhibitors. We integrated imaging-derived phenotypes with genotypic traits from transcriptional analysis, offering an in-depth characterization of pLGG immune microenvironment, progression risk, and likelihood of multiple treatments. METHODS Analyzing 549 treatment-naïve pLGGs with multiparametric MRI and RNA sequencing, we identified distinct immunological groups using XCell scores based on immune cell infiltration. We developed a radiomic signature using conventional MRI and machine learning techniques (support vector machines with a linear kernel and nested cross-validation) to distinguish the ‘immune-hot’ group, and incorporated diffusion MRI to improve signature accuracy. Additionally, a clinicoradiomic model predicting tumor progression risk and treatment response was trained, integrating clinical and radiomic data. Transcriptomic analysis was conducted to identify pathways correlated with clinicoradiomic risk, predictive of pLGG progression. RESULTS Three immunological groups were revealed, the ‘immune-hot’ group characterized by poor prognosis due to a high concentration of pro-tumorigenic M2-polarized macrophages, despite a higher preponderance of T-lymphocytes. The radiomic signature effectively distinguished the ‘immune-hot’ group with balanced accuracies of 76.8%/86.0% in discovery/replication sets, improved by diffusion MRI to 81.5%/84.4%. The clinicoradiomic model showed concordance indices of 0.71 (discovery) and 0.77 (replication), predicting patient progression risk. Significant differences (p=0.0010) were found in clinicoradiomic risk scores between patients undergoing one versus multiple treatments post-diagnosis, linking higher scores to a likelihood of multiple treatments. Transcriptomic pathways associated with higher clinicoradiomic risk highlighted the importance of fatty acid oxidation, a tumor-promoting mechanism that drives adaptive resistance to cytolytic immune cell effectors. CONCLUSIONS This first large-scale radiogenomic analysis in pLGGs aids in prognostication, assessing progression risk, predicting treatment response to standard-of-care therapies, and stratification of patients to identify potential candidates for novel therapies targeting aberrantly regulated pathways.

Fibrinogen-albumin ratio predicts treatment response in phospholipase A2 receptor-associated membranous nephropathy with nephrotic syndrome

Background The M-type phospholipase A2 receptor (PLA2R)-associated primary membranous nephropathy (PMN) is an immune-related disease in adults with increasing morbidity and variable treatment response, in which inflammation may contribute to the multifactorial immunopathogenesis. The relationship between fibrinogen-albumin ratio (FAR), serving as a novel inflammatory biomarker, and PMN is still unclear. Therefore, this study aims to clarify the association between FAR and disease activity and therapy response of PMN. Methods 110 biopsy-proven phospholipase A2 receptor (PLA2R) -associated PMN participants with nephrotic syndrome from January 2017 to December 2021 were recruited in the First Affiliated Hospital of Nanjing Medical University. The independent risk factors of non-remission (NR) and the predictive ability of FAR were explored by Cox regression and receiver-operating characteristic (ROC) curve analysis. According to the optimal cutoff value, study patients were categorized into the low-FAR group (≤the cutoff value) and the high-FAR group (>the cutoff value). Spearman’s correlations were used to examine the associations between FAR and baseline clinicopathological characteristics. Kaplan-Meier method was used to assess the effects of FAR on remission. Results In the entire study cohort, 78 (70.9%) patients reached complete or partial remission (CR or PR). The optimal cutoff value of FAR for predicting the remission outcome (CR + PR) was 0.233. The Kaplan-Meier survival analysis demonstrated that the high-FAR group (>0.233) had a significantly lower probability to achieve CR or PR compared to the low-FAR group (≤0.233) (Log Rank test, p = 0.021). Higher levels of FAR were identified as an independent risk factor for NR, and the high-FAR group was associated with a 2.27 times higher likelihood of NR than the low-FAR group (HR 2.27, 95% CI 1.01, 5.13, p = 0.048). These relationships remained robust with further analysis among calcineurin inhibitors (CNIs)-receivers. In the multivariate Cox regression model, the incidence of NR was 4.00 times higher in the high-FAR group than in the low-FAR group (HR 4.00, 95% CI 1.41, 11.31, p = 0.009). Moreover, ROC analysis revealed the predictive value of FAR for CR or PR with a 0.738 area under curve (AUC), and the AUC of anti-PLA2R Ab was 0.675. When combining FAR and anti-PLA2R Ab, the AUC was boosted to 0.766. Conclusions FAR was significantly correlated with proteinuria and anti-PLA2R Ab in PMN. As an independent risk factor for NR, FAR might serve as a potential inflammation-based prognostic tool for identifying cases with poor treatment response, and the best predictive cutoff value for outcomes was 0.233.

Assessing biomarkers of remission in female patients with anorexia nervosa (REMANO): a protocol for a prospective cohort study with a nested case–control study using clinical, neurocognitive, biological, genetic, epigenetic and neuroimaging markers in a French specialised inpatient unit

BackgroundAnorexia nervosa (AN) is a severe psychiatric disorder associated with frequent relapses and variability in treatment responses. Previous literature suggested that such variability is influenced by premorbid vulnerabilities such as...

Comparative Analysis of Gender-Based Differences in Behavioral Mastery, Goals, and Characteristics in Autistic Individuals: An Applied Behavior Analysis Study.

Introduction It is widely recognized that the prevalence and diagnosis of autism spectrum disorder (ASD) are more common in males than in females. Despite this, there is a significant gap in the body of autism research that investigates gender differences for treatment effects of applied behavior analysis (ABA) across a variety of measured variables. This research aims to comprehensively evaluate gender distinctions concerning target behavioral objectives, goals, and deficit variables. Materials and methods This study analyzed retrospective data from 100 participants, including 89 juveniles and four adults, with seven cases lacking age documentation, who underwent a three-month ABAprogram from March 19 to June 11, 2023. The ABA program included various methodologies such as functional analysis, discrete trial training, mass trials, and naturalistic training. Data on outcome measures, including target behavioral proficiency, age, average trials to proficiency, average teaching days to proficiency, open behavioral objectives, and target trends, were collected using the "Catalyst"software (Catalyst Software Corporation, New York, NY). Participant demographics were summarized using statistical analyses for categorical (gender and race/ethnicity) and continuous variables (percentage of mastered behavioral objectives, age, average trials, average teaching days, open objectives, percentage of failed objectives during maintenance, percentage of objectives with upward, downward, and flat trends). These statistics included mean, standard deviation, median, and rangeand were analyzed inferentially using nine separate two-sample independent t-tests and corresponding effect sizes using Cohen's d. Results There were no statistically significant disparities based on gender (p > 0.05) across all nine variables examined: Percentage of Targets Mastered, Age, Average Trials to Mastery, Average Teaching Days to Mastery, Open Targets, Percentage of Targets Failed in Maintenance, Percentage of Targets Trending Up, Percentage of Targets Trending Down, and Percentage of Targets Trending Flat, and wide confidence intervals were detected. Conclusions Non-significant gender differences in response to ABA treatments regarding these nine behavioral goals, mastery, and deficitvariables may be relevant. They suggest that ABA treatments could be equally beneficial for both male and female autistic individuals. These results should be interpreted cautiously. The general pattern observed, characterized by broad confidence intervals, carries a degree of statistical uncertainty, which may suggest substantial gender differences. These results might question the prevailing beliefs about the variation in treatment response based on gender. This could profoundly impact clinical practices, implying that healthcare professionals should not favor one gender over another when suggesting ABA therapies. Instead, the treatment advice should be tailored to each child's unique requirements and traits, regardless of gender. The investigators expect these results to encourage additional research in this field. Comprehending the elements that affect treatment response is vital for improving treatment results and customizing care.

Future for cardiogenic shock research.

To discuss future research themes and study design in cardiogenic shock. Cardiogenic shock research faces multiple challenges, hindering progress in understanding and treating this life-threatening condition. Cardiogenic shock's heterogeneous nature poses challenges in patient selection for clinical trials, potentially leading to variability in treatment responses and outcomes. Ethical considerations arise due to the acuity and severity of the condition, posing challenges in obtaining informed consent and conducting randomized controlled trials where time to treatment is pivotal. This review discusses research in this area focusing on the importance of phenotyping patients with cardiogenic shock, based on artificial intelligence, machine learning, and unravel new molecular mechanisms using proteomics and metabolomics. Further, the future research focus in mechanical circulatory support and targeting inflammation is reviewed. Finally, newer trial designs including adaptive platform trials are discussed.

Comparative analysis of the tumor microbiome, molecular profiles, and immune cell abundances by HPV status in mucosal head and neck cancers and their impact on survival

ABSTRACT Head and Neck Squamous Cell Carcinoma (HNSCC) comprises a diverse group of tumors with variable treatment response and prognosis. The tumor microenvironment (TME), which includes microbiome and immune cells, can impact outcomes. Here, we sought to relate the presence of specific microbes, gene expression, and tumor immune infiltration using tumor transcriptomics from The Cancer Genome Atlas (TCGA) and associate these with overall survival (OS). RNA sequencing (RNAseq) from HNSCC tumors in TCGA was processed through the exogenous sequences in tumors and immune cells (exotic) pipeline to identify and quantify low-abundance microbes. The detection of the Papillomaviridae family of viruses assessed HPV status. All statistical analyses were performed using R. A total of 499 RNAseq samples from TCGA were analyzed. HPV was detected in 111 samples (22%), most commonly Alphapapillomavirus 9 (90.1%). The presence of Alphapapillomavirus 9 was associated with improved OS [HR = 0.60 (95%CI: 0.40–0.89, p = .01)]. Among other microbes, Yersinia pseudotuberculosis was associated with the worst survival (HR = 3.88; p = .008), while Pseudomonas viridiflava had the best survival (HR = 0.05; p = .036). Microbial species found more abundant in HPV- tumors included several gram-negative anaerobes. HPV- tumors had a significantly higher abundance of M0 (p < .001) and M2 macrophages (p = .035), while HPV+ tumors had more T regulatory cells (p < .001) and CD8+ T-cells (p < .001). We identified microbes in HNSCC tumor samples significantly associated with survival. A greater abundance of certain anaerobic microbes was seen in HPV tumors and pro-tumorigenic macrophages. These findings suggest that TME can be used to predict patient outcomes and may help identify mechanisms of resistance to systemic therapies.

Advancements in the use of nanopharmaceuticals for cancer treatment.

Advances in nanotechnology make it possible to specifically target therapies to cancer cells and neoplasms, guide the surgical resection of tumors, and optimize the effectiveness of radiological treatments. This research article provides a concise synthesis of current knowledge in the field of galenic pharmacy focused on targeted drug delivery in oncology. This research article synthesizes current knowledge in galenic pharmacy, focusing on targeted drug delivery in oncology and reviewing recent advancements in nanopharmaceuticals for cancer treatment. The data for this review are derived from a comprehensive analysis of the most cited scientific literature (Pubmed). Recent studies, clinical trials, and technological breakthroughs related to nanopharmaceuticals have been rigorously examined. This diverse source ensures a comprehensive representation of the latest developments in the field. The results highlight the emergence of nanopharmaceuticals as a promising approach to cancer treatment. The most common in oncology remain liposomes, nanopolymers, and nanocrystals. From a galenic point of view, these three forms offer a wide range of improvements compared to conventional forms such as improvement in solubility as well as stability. The same observation is in the clinic where treatment response rates are significantly improved. The most advantageous form will depend on the specific characteristics of each patient and each type of cancer. The precise design of nanocarriers allows for targeted drug delivery, enhancing therapeutic efficacy while reducing side effects. Concrete examples of clinical applications are presented, illustrating the practical potential of these advancements. In conclusion, this review provides a holistic overview of recent developments in galenic pharmacy for targeted drug delivery in oncology. The stability of nanocarriers is a crucial challenge because it conditions the effectiveness and safety of the drugs transported. Environmental and biological variations encountered in the body can compromise this stability, jeopardizing the therapeutic effectiveness and safety of treatments. Likewise, personalized approaches are essential to address interindividual variations in treatment response, as well as patients' pharmacogenomic profiles, in order to optimize therapeutic effectiveness and minimize adverse effects.

Abstract PO1-15-07: Subtyping-directed precision treatment refines traditional one-size-fits-all therapy in HR+/HER2- breast cancer: a sub-study of the MULAN umbrella trial

Abstract Background: The standard approach of using one-size-fits-all endocrine therapy for hormone receptor-positive and HER2-negative (HR+/HER2-) breast cancers has faced significant challenges due to variations in treatment response among individuals. Consequently, there is still an urgent need to understand the molecular biology of HR+/HER2- breast cancer and explore precision treatment strategy. Methods: We established a multiomics cohort (n = 351), multicenter real-world clinical cohorts (n = 643), a prospective clinical cohort (MULAN trial), and a drug-testing platform containing patient-derived organoids (n = 126) and patient-derived tumor fragments (n = 49) of HR+/HER2- breast cancers. Integrating "bench" and “bedside” data, we conducted comprehensive preclinical and clinical translational research on precision strategies in HR+/HER2- breast cancer. Results: We implemented a comprehensive classification system for HR+/HER2- breast cancer, comprising four distinct subtypes. We further demonstrated the efficacy and mechanisms of subtyping-directed precision treatment strategies through clinical cohort studies, omics analysis and functional assays: endocrine therapy alone for the canonical luminal subtype; the addition of CDK4/6 inhibitor and PARP inhibitor for the proliferative subtype; the immunotherapy for the immunogenic subtype; and tyrosine kinase inhibitors for the receptor tyrosine kinase-driven subtype. Using clinically applicable subtyping methods, we validated that matched precision treatment strategies outperformed unmatched approaches in a real-world cohort, almost doubling the median progression-free survival time for patients with refractory advanced HR+/HER2- breast cancer (9.83 months [95% CI, 5.74-13.93] vs 4.77 months [95% CI, 3.35-6.18]; hazard ratio 0.64 [95% CI, 0.41-0.99]). Importantly, the first-stage analysis of the MULAN phase II umbrella clinical trial (NCT04355858) verified the higher objective response rate (88.9%, 95%CI: 51.7%-99.7%) of the subtyping-directed precision treatment. Conclusion: Our study emphasizes the superiority of subtyping-directed precision treatment strategies for HR+/HER2- breast cancer, refines traditional “one-size-fits-all” therapy, and facilitates the translation of precision treatment strategies from bench to bedside. Overall study design Part 1 Subtype Molecular Characteristics: Molecular features of the four subtypes of HR+/HER2- breast cancer. Part 2 Multidimensional Efficacy Validation: Integrating data from a multiomics cohort, real-world study, drug testing platform and prospective clinical research to validate the subtyping-directed precision treatment strategy in HR+/HER2- breast cancer. Part 3 Subtyping-directed Precision Treatment Strategy: Integrating clinical cohort studies, omics analysis and functional assays revealed the heterogeneity of treatment response in HR+/HER2- breast cancer, and proposed a subtyping-directed precision treatment strategy. CIN, chromosomal instability; RTK, receptor tyrosine kinase; CNA, copy-number alteration; ER, estrogen receptor; HR, hormone receptor; HER2, human epidermal growth factor receptor 2. Citation Format: Xiu-Zhi Zhu, Xi Jin, Hu-Yun-Long Zhang, Xiyu Liu, Yi-Fan Zhou, Yi-Yu Chen, Tong Fu, Ming-Liang Jin, Ya-Xin Zhao, Yi-Fan Xie, Ruo-Xi Wang, Zhong-Hua Wang, Lei Fan, Yi-Zhou Jiang, Zhi-Ming Shao. Subtyping-directed precision treatment refines traditional one-size-fits-all therapy in HR+/HER2- breast cancer: a sub-study of the MULAN umbrella trial [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO1-15-07.

Abstract PO4-06-04: Understanding metastasis mixed-treatment responses through genomic analyses

Abstract Background Early-stage and metastatic breast cancer (MBC) exhibit genomic heterogeneity, with inter-patient variability between primary tumors, intra-patient variability of primary tumors versus metastasis, and even between different metastatic sites within the same patient. Response to therapy in MBC can also be heterogeneous, termed "mixed response", with different degrees of responsiveness to the same drug(s) across metastatic sites within the same patient. Whether this treatment response variability is influenced by factors such as intrinsic characteristics of metastatic lesions and/or the microenvironment is unknown. Through genomic analysis, we aim to identify genomic features that may explain mixed clinical responses across metastatic sites, which will also provide valuable insights into treatment sensitivity and resistance. Methods Eligible patients with MBC were identified from the UNC Rapid Autopsy Program (RAP) with primary tumors and multiple metastases (≥ 2 different sites) with RNA sequencing data. An independent radiologist retrospectively reviewed imaging studies to identify patients with mixed radiographic responses to a defined line of therapy. The response to treatment was categorized for each metastasis, defined as a complete or partial response, as stabilization ≥ 6 months. Tumor measurements were performed for each patient at different time points. We performed supervised learning with linear regression incorporating "RNA sequencing-based gene expression signatures" as a fixed effect and "patient" as a random effect. We performed two different analyses: (1) Using all tumors and (2) using Basal-like tumors only. We finally selected significant signatures with a p-value &amp;gt;0.05. Results Ten patients with mixed response were identified, and 33 metastases were used for the analysis; 3 had de novo stage IV disease, 5 had triple-negative (TNBC), 4 HER2+, and 4 hormone receptor+ (HR+/HER2-) disease. Of 33 metastases, 6 were brain, 8 liver, 7 lung, and 12 “other”. Regarding intrinsic subtype, 15 metastatic tumors were Basal-like, 3 HER2-Enriched (HER2E), 6 Luminal A, and 9 Luminal B. In this dataset, 6 metastatic lesions showed response and 27 non-response. When analyzing all 33 metastases, KRAS high expression, KRAS amplicon, 16q23 amplicon, and apocrine features correlated with response independently of metastatic site. Higher T reg and CDKN2A gene expression levels were associated with non-response in metastasis. Within Basal-like subtype metastases only (N=15), CD8 T cells, PI3K pathway, KRAS gene and amplicon, 16q23 amplicon, and Basal-like-associated 5q11 loss correlated with response. However, T reg cells, higher levels of CDKN2A gene, and stem-cell-like features were associated with treatment non-response. Conclusions By examining matched metastases with discordant responsiveness to treatment within individual patients, this genomic analysis provides valuable insight into treatment sensitivity and resistance. Higher T reg cells and CDKN2A gene expression values correlate with non-response, while the KRAS gene, KRAS amplicon, and the 16q23 amplicon were associated with response. These results suggest that the molecular tumor and microenvironment features of metastases may contribute to sensitivity and resistance to therapy in MBC. Further validation and exploration are needed in larger multi-metastatic cohorts to fully understand the clinical implications of these findings. Citation Format: Susana Garcia-Recio, Paola Zagami, Amy Wheless, Kerry Thomas, Lisa Carey, Charles M Perou. Understanding metastasis mixed-treatment responses through genomic analyses [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO4-06-04.