Biomarkers Of Treatment Response Research Articles

Sintilimab combined with anlotinib and chemotherapy as second-line or later therapy in extensive-stage small cell lung cancer: a phase II clinical trial

Treatment options for patients with relapsed extensive-stage small cell lung cancer (ES-SCLC) remain scarce. This study aims to evaluate the efficacy and safety of combining anlotinib and sintilimab plus chemotherapy as a second line or later therapy for ES-SCLC patients. This is a phase II clinical trial (ChiCTR2100049390) conducting at Shandong Cancer Hospital. Patients with ES-SCLC and received at least one prior systemic treatment were enrolled. The trial design involved a combination therapy (sintilimab, anlotinib, and nab-paclitaxel) administered over six 21-day cycles, followed by maintenance sintilimab therapy. The primary endpoint was objective response rate (ORR). Circulating tumor DNA sequencing was employed for exploratory analysis. From July 2021 to April 2023, 25 eligible patients were enrolled. The confirmed ORR was 60% (95% CI: 38.7–78.9%) and the DCR was 76% (95% CI: 54.9–90.6%). The mPFS was 6.0 months (95% CI: 5.4–9.7), and the 6-month PFS rate was 49.2%. The mOS was 13.4 months (95% CI: 11.8-NR), with a 12-month survival rate of 62.2%. Treatment-related adverse events (TRAEs) of any grade occurred in 80% of patients, with the most common being fatigue (40%) and nausea (32%). TRAEs of Grade 3 or higher were reported in 12% of patients. ctDNA analysis indicated that low on-treatment blood tumor mutation burden was associated with longer PFS and OS and a potential role of KMT2D mutation in treatment resistance. This combination therapy shows promising efficacy and a manageable safety profile as a second-line or later treatment for ES-SCLC, with genomic insights providing potential biomarkers for treatment response.

Impact of oxaliplatin and trastuzumab combination therapy on tumor markers and T lymphocyte subsets for advanced gastric cancer

BACKGROUND Advanced gastric cancer (AGC) remains a challenging malignancy with poor prognosis. The combination of oxaliplatin and trastuzumab has shown promising results in AGC treatment. This study aimed to investigate the effects of oxaliplatin and trastuzumab combination therapy on serum tumor markers and T lymphocyte subsets in patients with AGC and to explore their potential as predictive biomarkers for treatment response. AIM To investigate the impact of oxaliplatin and trastuzumab combination therapy on serum markers and T cell subsets in patients with AGC. METHODS This prospective study enrolled 60 patients with AGC. All patients received oxaliplatin (130 mg/m2, every 3 weeks) and trastuzumab (8 mg/kg loading dose, followed by 6 mg/kg every 3 weeks) for six cycles. Serum carcinoembryonic antigen (CEA), cancer antigen 19-9 (CA19-9), and cancer antigen 72-4 (CA72-4) were measured before and after treatment. T-lymphocyte subsets, including CD3+, CD4+, CD8+, and CD4+ /CD8+ ratios, were also evaluated. The clinical response was assessed using the Response Evaluation Criteria in Solid Tumors version 1.1. RESULTS After six cycles of treatment, the CEA, CA19-9, and CA72-4 serum levels significantly decreased compared to baseline levels (P < 0.001). The percentages of CD3+ and CD4+ T lymphocytes increased significantly (P < 0.05), whereas the percentage of CD8+ T lymphocytes decreased (P < 0.05). The CD4+/CD8+ ratio also significantly increased after treatment (P < 0.05). Patients with a higher decrease in serum tumor markers (≥ 50% reduction) and a higher increase in CD4+/CD8+ ratio (≥ 1.5-fold) showed better clinical response rates (P < 0.05). CONCLUSION Oxaliplatin and trastuzumab combination therapy effectively reduced serum tumor marker levels and modulated T lymphocyte subsets in patients with AGC. Combination therapy not only has a direct antitumor effect, but also enhances the immune response in patients with AGC. Serum tumor markers and T lymphocyte subsets may serve as potential predictive biomarkers for treatment response in patients with AGC receiving combination therapy.

Plasma ctDNA as a treatment response biomarker in metastatic cancers: evaluation by the RECIST working group.

Early indicators of metastatic cancer response to therapy are important for evaluating new drugs and stopping ineffective treatment. The Response Evaluation Criteria in Solid Tumors (RECIST) based on repeat cancer imaging are widely adopted in clinical trials, are used to identify active regimens that may change practice, and contribute to regulatory approvals. However, these criteria do not provide insight before 6 - 12 weeks of treatment and typically require that patients have measurable disease. Recent data suggests that measuring on-treatment changes in the amount or proportion of circulating tumor DNA (ctDNA) in peripheral blood plasma may accurately identify responding and non-responding cancers at earlier time points. Over the past year, the RECIST working group has evaluated current evidence for plasma ctDNA kinetics as a treatment response biomarker in metastatic cancers and early endpoint in clinical trials, to identify areas of focus for future research and validation. Here, we outline the requirement for large standardized trial datasets, greater scrutiny of optimal ctDNA collection time points and assay thresholds, and consideration of regulatory body guidelines and patient opinions. In particular, clinically-meaningful changes in plasma ctDNA abundance are likely to differ by cancer type and therapy class, and must be assessed before ctDNA can be considered as a potential pan-cancer response evaluation biomarker. Despite the need for additional data, minimally-invasive on-treatment ctDNA measurements hold promise to build upon existing response assessments such as RECIST, and offer opportunities for developing novel early endpoints for modern clinical trials.

Altered Neuronal Activity Patterns of the Prefrontal Cortex in Alzheimer's Disease After Transcranial Alternating Current Stimulation: A Resting-State fMRI Study.

Transcranial alternating current stimulation (tACS) could improve cognition in patients with Alzheimer's disease (AD). However, the effects of tACS on brain activity remain unclear. The purpose is to investigate the change in regional neuronal activity after tACS in AD patients employing resting-state functional magnetic resonance imaging (rs-fMRI). A total of 46 patients with mild AD were enrolled. Each patient received 30 one-hour sessions of real or sham tACS for three weeks (clinical trial: NCT03920826). The fractional amplitude of low-frequency fluctuations (fALFF) and the regional homogeneity (ReHo) measured by rs-fMRI were calculated to evaluate the regional brain activity. Compared to baseline, AD patients in the real group exhibited increased fALFF in the left middle frontal gyrus-orbital part and right inferior frontal gyrus-orbital part, as well as increased ReHo in the left precentral gyrus and right middle frontal gyrus at the end of intervention. At the 3-month follow-up, fALFF increased in the left superior parietal lobule and right inferior temporal gyrus, as well as ReHo, in the left middle frontal gyrus and right superior medial frontal gyrus. A higher fALFF in the right lingual gyrus and ReHo in the right parahippocampal gyrus were observed in the response group than in the nonresponse group. The findings demonstrated the beneficial effects of tACS on the neuronal activity of the prefrontal cortex and even more extensive regions and provided a neuroimaging biomarker of treatment response in AD patients.

240. CACHEXIA INDEX AS A POTENTIAL BIOMARKER FOR SENSITIVITY OF NEOADJUVANT THERAPY AND PROGNOSIS IN ESOPHAGEAL SQUAMOUS CELL CARCINOMA

Abstract Background Cancer cachexia has a negative impact on the clinical outcome of patients with esophageal squamous cell carcinoma (ESCC). The cachexia index (CXI) is a potential biomarker for cancer cachexia, whereas its implications for ESCC prognosis and treatment outcomes have not been investigated. Methods In our study, 454 ESCC patients who had neoadjuvant therapy followed by surgery were included. Based on the exclusion criteria, a total of 224 patients were finally enrolled in this study. The CXI was determined as the serum albumin/neutrophil-lymphocyte ratio × the skeletal muscle index (based on CT image), which was classified as L3-CXI or pectoralis muscles-CXI depending upon the type of muscle involved. The patients were divided into high- and low-CXI groups using sex-specific medians as cutoff values for CXI. Results Tumor regression grade = 0,1 (sensitive to treatment) to neoadjuvant therapy was obtained in 61.6% and 46.4% of patients in the high-pretreatment L3-CXI and low-pretreatment L3-CXI groups, respectively (P = 0.023). ESCC patients with △L3-CXI <0 (L3-CXI decreased during treatment) had significantly shorter overall survival (P = 0.006) and disease-free survival (P = 0.002) than those with △L3-CXI ≥0. Multivariable analysis showed that △L3-CXI <0 was an independent negative prognostic factor for overall survival and disease-free survival. Conclusions In patients with ESCC, pretreatment CXI is a biomarker for treatment response, and △CXI can predict postoperative complications and survival outcomes. Patients could be clearly stratified by pretreatment CXI and △CXI categories, which provides a new nutritional assessment tool for clinical decision-making for patients with ESCC.

CXCR7 genetic variant predicts treatment response of pegylated-interferon α in HBeAg-positive chronic hepatitis B patients

ObjectivesCXC chemokine receptor 7 (CXCR7) plays pivotal roles in different virus infections. However, no research focused on the role of CXCR7 in hepatitis B virus (HBV)-infected patients. The primary aim of this study is to elucidate the role of CXCR7 in predicting the treatment response of chronic hepatitis B (CHB) patients undergoing pegylated interferon-alpha (PegIFNα) therapy. MethodsTwo cohorts with a total of 945 Chinese CHB patients (Cohort 1, n = 238; Cohort 2, n = 707) were enrolled in this retrospective study, all the patients were positive for hepatitis B e antigen (HBeAg) and received PegIFNα treatment for 48 weeks and followed-up for 24 weeks post-treatment. Nineteen tag single-nucleotide polymorphisms (SNPs) were selected within and surrounding the CXCR7 gene region. The associations of CXCR7 SNPs and polygenic score (PGS) with PegIFNα treatment response were investigated in the two cohorts. ResultsAmong the 19 candidate SNPs of CXCR7, rs2952665 (A > G) was significantly associated with combined response (CR, defined as HBeAg seroconversion and HBV DNA level <3.3log10IU/mL, P = 0.002) and hepatitis B surface antigen (HBsAg) decline (P = 0.015) in the two cohorts at week 72. Furthermore, a PGS comprising CXCR7_rs2952665 and five additional SNPs, which were previously recognized as biomarkers of PegIFNα treatment response, demonstrated a robust correlation with both CR (P = 1.38 × 10−12) and HBsAg decline (P = 0.003) in all the patients. ConclusionThis research illustrated that CXCR7_rs2952665 is a promising predictor of the PegIFNα therapy efficiency in Chinese HBeAg-positive CHB patients. A PGS consisting of CXCR7_rs2952665 and five previously reported SNPs predicts treatment response to PegIFNα better.

CIBRA identifies genomic alterations with a system-wide impact on tumor biology.

Genomic instability is a hallmark of cancer, leading to many somatic alterations. Identifying which alterations have a system-wide impact is a challenging task. Nevertheless, this is an essential first step for prioritizing potential biomarkers. We developed CIBRA (Computational Identification of Biologically Relevant Alterations), a method that determines the system-wide impact of genomic alterations on tumor biology by integrating two distinct omics data types: one indicating genomic alterations (e.g. genomics), and another defining a system-wide expression response (e.g. transcriptomics). CIBRA was evaluated with genome-wide screens in 33 cancer types using primary and metastatic cancer data from the Cancer Genome Atlas and Hartwig Medical Foundation. We demonstrate the capability of CIBRA by successfully confirming the impact of point mutations in experimentally validated oncogenes and tumor suppressor genes (0.79 AUC). Surprisingly, many genes affected by structural variants were identified to have a strong system-wide impact (30.3%), suggesting that their role in cancer development has thus far been largely under-reported. Additionally, CIBRA can identify impact with only 10 cases and controls, providing a novel way to prioritize genomic alterations with a prominent role in cancer biology. Our findings demonstrate that CIBRA can identify cancer drivers by combining genomics and transcriptomics data. Moreover, our work shows an unexpected substantial system-wide impact of structural variants in cancer. Hence, CIBRA has the potential to preselect and refine current definitions of genomic alterations to derive more nuanced biomarkers for diagnostics, disease progression, and treatment response. The R package CIBRA is available at https://github.com/AIT4LIFE-UU/CIBRA.

797. A COMPARATIVE ANALYSIS ON THE EFFECTIVENESS OF DIFFERENT TREATMENT MODALITIES FOR ESOPHAGEAL CARCINOMA; A SYSTEMATIC REVIEW

Abstract Background Esophageal carcinoma; sixth most common cancer worldwide, presents a significant clinical challenge due to its aggressive nature and often late-stage diagnosis, resulting in poor prognosis and limited treatment options. Various treatment modalities, including surgery, chemotherapy, radiation therapy, immunotherapy, and targeted therapy, are utilized in clinical practice. However, the optimal treatment strategy remains uncertain, as the comparative effectiveness of these modalities is not well-defined. Past studies have provided conflicting evidence, necessitating a comprehensive evaluation to guide clinical decision-making. Therefore, this systematic review aims to compare the efficacy and safety of different treatment modalities for esophageal carcinoma, with the objective of informing evidence-based treatment approaches and improving patient outcomes. Methods Total 350 publications from PubMed, EMBASE, Cochrane, Google Scholar and Semantic Scholar databases were identified on the effectiveness of different treatment modalities for esophageal carcinoma between 2000 and 2024. Following deduplication, two independent reviewers initially screened the articles for eligibility with titles and abstracts, and then, with complete articles. Bias assessment using GRADE guidelines for observational studies was done. Non-English studies, case-series/case-reports/essays/book-chapters/conference-abstracts/editorials/thesis/dissertations and studies without full-texts were excluded. Results Overall, the effectiveness of each treatment modality for esophageal carcinoma depends on various factors, including tumor stage, histology, patient characteristics, and treatment regimen. Combination approaches, such as chemoradiotherapy or multimodal therapy, are often used to maximize treatment efficacy and improve patient outcomes. Conclusion Multidisciplinary collaboration, personalized treatment approach, integration of novel therapies, such as immunotherapy and targeted therapy, into standard treatment regimens, survivorship care and advocate for further research to identify optimal treatment sequencing, identify predictive biomarkers of treatment response, and explore novel therapeutic targets to improve outcomes for patients with esophageal carcinoma is recommended.

Metabolomic characterization of human glioblastomas and patient plasma: a pilot study

Background Glioblastoma (GBM) is a clinically challenging primary brain tumor with poor survival outcome despite surgical resection and intensive chemoradiation. The metabolic heterogeneity of GBM can become biomarkers for treatment response, resistance, and outcome prediction. The aim of the study is to investigate metabolic distinctions between primary and recurrent GBM tissue and patient plasma to establish feasibility for metabolic profiling. Methods A single-center cohort study analyzed tissue and blood samples from 15 patients with GBM using untargeted metabolomic/lipidomic assays. Metabolomic, lipidomic, and biogenic amine analyses were conducted on GBM tissue and patient plasma at diagnosis and recurrence using untargeted mass spectrometry. The study utilized a small but longitudinally collected cohort to evaluate alteration in metabolites, lipids, and biogenic amines between specimens at diagnosis and recurrence. Results Exploratory analysis revealed significant alteration in metabolites, lipids, and biogenic amines between diagnostic and recurrent states in both tumor and plasma specimens. Notable metabolites differed at recurrence, including N-alpha-methylhistamine, glycerol-3-phosphate, phosphocholine, and succinic acid in tissue, and indole-3-acetate, and urea in plasma. Principal component analysis revealed distinct metabolomic profiles between tumor tissue and patient plasma. Distinct metabolic profiles were observed in GBM tissue and patient plasma at recurrence, demonstrating the feasibility of using metabolomic methodologies for longitudinal studies. One patient exhibited a unique tumor resistance signature at diagnosis, possibly indicating a high-risk metabolomic phenotype. Conclusions In this small cohort, the findings suggest the potential of metabolomic signatures of GBM tissue and patient plasma for risk stratification, outcome prediction, and the development of novel adjuvant metabolic-targeting therapies. The findings suggest metabolic discrepancies at diagnosis and recurrence in tissue and plasma, highlighting potential implications for evaluation of clinical response. The identification of significant changes in metabolite abundance emphasizes the need for larger studies using targeted metabolomics to validate and further explore these profiles.

Comprehensive Analysis of Microsatellite Instability in Canine Cancers: Implications for Comparative Oncology and Personalized Veterinary Medicine.

Microsatellite instability (MSI) is a crucial feature in cancer biology, yet its prevalence and significance in canine cancers remain largely unexplored. This study conducted a comprehensive analysis of MSI across 10 distinct canine cancer histotypes using whole-exome sequencing data from 692 tumor-normal sample pairs. MSI was detected in 64% of tumors, with prevalence varying significantly among cancer types. B-cell lymphomas exhibited the highest MSI burden, contrasting with human studies. A novel "MSI-burden" score was developed, correlating significantly with tumor mutational burden. MSI-high (MSI-H) tumors showed elevated somatic mutation counts compared to MSI-low and microsatellite stable tumors. The study identified 3632 recurrent MSI-affected genomic regions across cancer types. Notably, seven of the ten cancer types exhibited MSI-H tumors, with prevalence ranging from 1.5% in melanomas to 37% in B-cell lymphomas. These findings highlight the potential importance of MSI in canine cancer biology and suggest opportunities for targeted therapies, particularly immunotherapies. The high prevalence of MSI in canine cancers, especially in B-cell lymphomas, warrants further investigation into its mechanistic role and potential as a biomarker for prognosis and treatment response.

Peripheral blood T-cell modulation by omalizumab in chronic urticaria patients.

Chronic spontaneous urticaria (CSU) is a highly prevalent and difficult to manage cutaneous disease characterized by the presence of recurrent urticaria, angioedema, or both, for a period of 6 weeks or longer. One of the biological treatments used for patients with CSU with an autoimmune background and bad control of the disease is omalizumab, an anti-IgE monoclonal antibody. The understanding of the mechanism of action of this biological drug in CSU along with the identification of potential biomarkers of clinical response can be helpful in the personalized management of the disease. The purpose of this study was to analyze the effect of omalizumab on peripheral blood lymphocyte subpopulations in patients with CSU in order to identify potential biomarkers of treatment response. We analyzed 71 patients with CSU [33 under omalizumab and 38 under non-immunomodulatory drugs (treated with antihistamines; NID)] and 50 healthy controls. An exhaustive immunophenotyping of whole blood T-cell subpopulations, including naïve, central memory, effector memory, effector cells, Th1, Th2, and Th17 was performed by multiparametric flow cytometry. Moreover, in CSU patients, we analyzed markers of inflammation (ESR, DD, CRP), atopy (prick test, IgE quantification), and autoimmunity (anti-thyroid antibodies and indirect basophil activation test).To evaluate the clinical activity, the Urticaria Activity Score 7 (UAS 7) test was used. In patients with CSU under treatment with omalizumab, there was a significant decrease in the percentage of naïve and an increase in the percentage of central memory CD4 T cells as well as a decrease in the percentage of naïve and increase in the percentage of effector CD8 T-cell subsets. Moreover, patients under treatment with omalizumab had higher percentages of Th1 and Th2 cells than patients under treatment with NID. The immune monitoring of T-cell subpopulations in patients with CSU starting omalizumab, may be a useful strategy to analyze treatment response in the clinical practice.

Artificial Intelligence Applications in Oral Cancer and Oral Dysplasia.

Oral squamous cell carcinoma (OSCC) is a highly unpredictable disease with devastating mortality rates that have not changed over the past decades, in the face of advancements in treatments and biomarkers, which have improved survival for other cancers. Delays in diagnosis are frequent, leading to more disfiguring treatments and poor outcomes for patients. The clinical challenge lies in identifying those patients at the highest risk of developing OSCC. Oral epithelial dysplasia (OED) is a precursor of OSCC with highly variable behavior across patients. There is no reliable clinical, pathological, histological, or molecular biomarker to determine individual risk in OED patients. Similarly, there are no robust biomarkers to predict treatment outcomes or mortality in OSCC patients. This review aims to highlight advancements in artificial intelligence (AI)-based methods to develop predictive biomarkers of OED transformation to OSCC or predictive biomarkers of OSCC mortality and treatment response. Biomarkers such as S100A7 demonstrate promising appraisal for the risk of malignant transformation of OED. Machine learning-enhanced multiplex immunohistochemistry workflows examine immune cell patterns and organization within the tumor immune microenvironment to generate outcome predictions in immunotherapy. Deep learning (DL) is an AI-based method using an extended neural network or related architecture with multiple "hidden" layers of simulated neurons to combine simple visual features into complex patterns. DL-based digital pathology is currently being developed to assess OED and OSCC outcomes. The integration of machine learning in epigenomics aims to examine the epigenetic modification of diseases and improve our ability to detect, classify, and predict outcomes associated with epigenetic marks. Collectively, these tools showcase promising advancements in discovery and technology, which may provide a potential solution to addressing the current limitations in predicting OED transformation and OSCC behavior, both of which are clinical challenges that must be addressed in order to improve OSCC survival.

Real-world data confirm elexacftor/tezacaftor/ivacaftor modulators halves sweat chloride concentration in eligible people with cystic fibrosis.

Sweat chloride concentration, a diagnostic feature in cystic fibrosis (CF), reflects CF transmembrane conductance regulator (CFTR) activity. CFTR modulator therapies, especially elexacaftor/tezacaftor/ivacaftor (ETI), has improved CF outcomes. We report nationwide, real-world data on sweat chloride concentration in people with CF (pwCF) with and without modulator therapies. All Danish pwCF with a minimum of one F508del allele were included. Sweat chloride measurements were stratified by genotype and modulator treatment. Differences were assessed using mixed-effects models. We included 977 sweat chloride measurements from 430 pwCF, 71% of which were F508del homozygous. Heterozygous and homozygous ETI-treated pwCF had an estimated mean sweat chloride concentration of 43 mmol/L (95% confidence interval: 39; 48) and 43 mmol/L (39; 47), respectively-48% and 59% lower than those without treatment. High variation in concentrations remained regardless of treatment status. Despite ETI treatment, 27% heterozygous and 23% homozygous pwCF had elevated concentrations (≥60 mmol/L). These real-world data confirm a substantial decrease in sweat chloride concentration during modulator treatment, especially ETI, where mean concentrations halved. However, large variation remained, including persistently high concentrations. These findings emphasize the potential of sweat chloride concentration as a treatment response biomarker and the need to explore its heterogeneity and relationship with clinical outcomes.

Identifying digital biomarkers of illness activity and treatment response in bipolar disorder with a novel wearable device (TIMEBASE): protocol for a pragmatic observational clinical study.

Bipolar disorder is highly prevalent and consists of biphasic recurrent mood episodes of mania and depression, which translate into altered mood, sleep and activity alongside their physiological expressions. The IdenTifying dIgital bioMarkers of illnEss activity and treatment response in BipolAr diSordEr with a novel wearable device (TIMEBASE) project aims to identify digital biomarkers of illness activity and treatment response in bipolar disorder. We designed a longitudinal observational study including 84 individuals. Group A comprises people with acute episode of mania (n = 12), depression (n = 12 with bipolar disorder and n = 12 with major depressive disorder (MDD)) and bipolar disorder with mixed features (n = 12). Physiological data will be recorded during 48 h with a research-grade wearable (Empatica E4) across four consecutive time points (acute, response, remission and episode recovery). Group B comprises 12 people with euthymic bipolar disorder and 12 with MDD, and group C comprises 12 healthy controls who will be recorded cross-sectionally. Psychopathological symptoms, disease severity, functioning and physical activity will be assessed with standardised psychometric scales. Physiological data will include acceleration, temperature, blood volume pulse, heart rate and electrodermal activity. Machine learning models will be developed to link physiological data to illness activity and treatment response. Generalisation performance will be tested in data from unseen patients. Recruitment is ongoing. This project should contribute to understanding the pathophysiology of affective disorders. The potential digital biomarkers of illness activity and treatment response in bipolar disorder could be implemented in a real-world clinical setting for clinical monitoring and identification of prodromal symptoms. This would allow early intervention and prevention of affective relapses, as well as personalisation of treatment.

MEN1/DAXX/ATRX mutations enhance progression-free survival in gastroenteropancreatic neuroendocrine tumors treated with peptide receptor radionuclide therapy.

Pre-clinical data suggest that mutations in the MEN1, DAXX, and/or ATRX genes may potentially increase radiation efficacy in cancer cells. Herein, we explore the association between response to peptide receptor radionuclide therapy (PRRT) and those mutations in patients with gastroenteropancreatic neuroendocrine tumors (GEP-NETs). We analyzed tissue-based next generation sequencing (NGS) assay results and clinicopathologic data from 28 patients with GEP-NETs treated with PRRT. Findings were correlated with progression-free survival (PFS) and objective response (ORR). Patients with mutations in MEN1, DAXX, and/or ATRX (n = 13) had a longer median PFS (26.47 vs. 12.13 months; p = 0.014) than wildtype (n = 15) patients when adjusted for surgery prior to PRRT, tumor grade, and presence of TP53 mutation. Alterations in MEN1 along with a concurrent mutation in either DAXX or ATRX (n = 6) trended towards longer PFS compared to patients without concurrent mutations (31.53 vs. 17.97 months; p = 0.09). ORR was higher in patients with a mutation in MEN1, DAXX, or ATRX (41.67% vs. 15.38%). In pancreatic NET patients, these target mutations also showed a longer PFS (28.43 vs. 9.83 months; p = 0.04). TP53 alterations showed a shorter PFS than wild-type cases (11.17 vs. 20.47 months; p = 0.009). Mutations in MEN1/DAXX/ATRX are associated with improved PFS in patients with GEP-NETs receiving PRRT and might be used as a biomarker for treatment response.

Lymphocyte-to-monocyte, platelet-to-albumin and platelet-to-lymphocyte ratios as prognostic biomarkers for neoadjuvant treatment response in rectal cancer patients

IntroductionSystemic inflammatory response (SIR) indicators are an emerging category of serum biomarkers with significant potential as prognostic and predictive factors in various types of cancers The primary focus of our study was to determine the prognostic value of the lymphocyte-to-monocyte ratio (LMR), platelet-to-albumin ratio (PLR) and platelet-to-albumin ratio (PAR) in evaluating the response to neoadjuvant treatment for patients with rectal cancer. Materials and methodsWe included 99 consecutive patients with rectal cancer which were admitted for surgery in our institution after completing a standard neoadjuvant radio-chemotherapy regimen. Several hematologic parameters, including LMR, PAR and PLR, were calculated by collecting and analyzing blood samples preoperatively. Cases were divided into groups using ROC curve analysis to determine optimal cutoff values for each of the investigated parameters. Treatment response was assessed through histopathological analysis of the resected specimens. ResultsPLR values over 215.2 were correlated with the presence of lymph node metastasis. A similar correlation was observed between PAR values over 41.89 and lymph node positivity. A significant correlation was observed between the presence of tumor budding on histopathological analysis and high-PAR values. A statistically significant correlation between a high PLR and a good response to neoadjuvant treatment was determined. ConclusionsHigh PLR values may be associated with a more favorable treatment response to neoadjuvant radio-chemotherapy. A high PAR may be associated with unfavorable histopathological characteristics. Further studies on these readily available biomarkers are required in order to validate their clinical utility.

In perspective of specific symptoms of major depressive disorder: Functional connectivity analysis of electroencephalography and potential biomarkers of treatment response

BackgroundThe symptom variability in major depressive disorder (MDD) complicates treatment assessment, necessitating a thorough understanding of MDD symptoms and potential biomarkers. MethodsIn this prospective study, we enrolled 54 MDD patients and 39 controls. Over the course of weeks 1, 2, and 4 participants underwent evaluations, with electroencephalograms (EEG) recorded at baseline and week 1. Our investigation considered five previously identified syndromal factors derived from the 17-item Hamilton Depression Rating Scale (17-item HAMD) for assessing depression: core, insomnia, somatic anxiety, psychomotor-insight, and anorexia. We assessed treatment response and EEG characteristics across all syndromal factors and total scores, all of which are based on the 17-item HAMD. To analyze the topology of brain networks, we employed functional connectivity (FC) and a graph theory-based method across various frequency bands. ResultsThe healthy control group had notably higher values in delta band EEG FC compared to the MDD patient group. Similar distinctions were observed between the responder and non-responder patient groups. Further exploration of baseline FC values across distinct syndromal factors revealed significant variations among the core, psychomotor-insight, and anorexia subgroups when using a specific graph theory-based approach, focusing on global efficiency and average clustering coefficient. LimitationsDifferent antidepressants were included in this study. Therefore, the results should be interpreted with caution. ConclusionsOur findings suggest that delta band EEG FC holds promise as a valuable predictor of antidepressant efficacy. It demonstrates an ability to adapt to individual variations in depressive symptomatology, offering insights into personalized treatment for patients with depression.

Exploring the association between melatonin and nicotine dependence (Review).

Due to the addictive qualities of tobacco products and the compulsive craving and dependence associated with their use, nicotine dependence continues to be a serious public health concern on a global scale. Despite awareness of the associated health risks, nicotine addiction contributes to numerous acute and chronic medical conditions, including cardiovascular disease, respiratory disorders and cancer. The nocturnal secretion of pineal melatonin, known as the 'hormone of darkness', influences circadian rhythms and is implicated in addiction‑related behaviors. Melatonin receptors are found throughout the brain, influencing dopaminergic neurotransmission and potentially attenuating nicotine‑seeking behavior. Additionally, the antioxidant properties of melatonin may mitigate oxidative stress from chronic nicotine exposure, reducing cellular damage and lowering the risk of nicotine‑related health issues. In addition to its effects on circadian rhythmicity, melatonin acting via specific neural receptors influences sleep and mood, and provides neuroprotection. Disruptions in melatonin signaling may contribute to sleep disturbances and mood disorders, highlighting the potential therapeutic role of melatonin in addiction and psychiatric conditions. Melatonin may influence neurotransmitter systems involved in addiction, such as the dopaminergic, glutamatergic, serotonergic and endogenous opioid systems. Preclinical studies suggest the potential of melatonin in modulating reward processing, attenuating drug‑induced hyperactivity and reducing opioid withdrawal symptoms. Chronotherapeutic approaches targeting circadian rhythms and melatonin signaling show promise in smoking cessation interventions. Melatonin supplementation during periods of heightened nicotine cravings may alleviate withdrawal symptoms and reduce the reinforcing effects of nicotine. Further research is required however, to examine the molecular mechanisms underlying the melatonin‑nicotine association and the optimization of therapeutic interventions. Challenges include variability in individual responses to melatonin, optimal dosing regimens and identifying biomarkers of treatment response. Understanding these complexities could lead to personalized treatment strategies and improve smoking cessation outcomes.

Dupilumab Reduces Urticaria Activity, Itch, and Hives in Patients with Chronic Spontaneous Urticaria Regardless of Baseline Serum Immunoglobulin E Levels.

In chronic spontaneous urticaria (CSU), interleukin (IL)-4 and IL-13 may promote mast cell activation directly via IL-4 receptor expression, or indirectly via upregulated immunoglobulin E (IgE) production. Dupilumab significantly improved CSU signs and symptoms in the phase 3, randomized, placebo-controlled LIBERTY-CSU CUPID Study A. This analysis explores the impact of dupilumab on CSU signs and symptoms and serum IgE levels in patients from LIBERTY-CSU CUPID Study A with serum total IgE above and below 100IU/mL at baseline. Patients with H1-antihistamine-refractory CSU received dupilumab (n = 70) or placebo (n = 68) for 24 weeks. Efficacy endpoints were change from baseline to weeks 12 and 24 in serum total IgE levels, Itch Severity Score over 7 days (ISS7), Urticaria Activity Score over 7 days (UAS7), and Hives Severity Score over 7days (HSS7) in dupilumab- or placebo-treated patients with serum total IgE above and below 100IU/mL at baseline. Dupilumab treatment significantly reduced median (interquartile range) IgE levels at week 12 [dupilumab: -31.9% (-41.9; -22.6); placebo: -6.3% (-21.3; 14.9)] and week 24 [dupilumab: -48.2% (-56.8; - 39.5); placebo: - 6.3% (-34.5; 14.8)]. Similar IgE reductions relative to baseline were observed in dupilumab-treated patients regardless of baseline IgE level. Dupilumab treatment improved ISS7, UAS7, and HSS7 over 12 and 24 weeks, regardless of baseline serum IgE level (interaction p ≥ 0.59 for all treatment by subgroup comparisons), with weak correlations (r < 0.2) observed between IgE level changes and ISS7, UAS7, and HSS7 outcomes. Dupilumab significantly improved CSU signs and symptoms and reduced serum IgE, regardless of baseline IgE levels. In the current analysis, baseline total IgE had no predictive value as a dupilumab treatment response biomarker in CSU. Downregulation of IgE, a key mediator of mast cell activation and histamine release, may at least partially explain the effectiveness of dupilumab in reducing CSU signs and symptoms. ClinicalTrials.gov Identifier: NCT04180488.

SomaLogic proteomics reveals new biomarkers and provides mechanistic, clinical insights into Acetyl coA Carboxylase (ACC) inhibition in Non-alcoholic Steatohepatitis (NASH)

Non-alcoholic Fatty Liver Disease (NAFLD) and Non-alcoholic Steatohepatitis (NASH) are major metabolic diseases with increasing global prevalence and no approved therapies. There is a mounting need to develop biomarkers of diagnosis, prognosis and treatment response that can effectively replace current requirements for liver biopsies, which are invasive, error-prone and expensive. We performed SomaLogic serum proteome profiling with baseline (n = 231) and on-treatment (n = 72, Weeks 12 and 16, Placebo and 25 mg PF-05221304) samples from a Phase 2a trial (NCT03248882) with Clesacostat (PF-05221304), an acetyl coA carboxylase inhibitor (ACCi) in patients with NAFLD/NASH. SomaSignal NASH probability scores and expression data for 7000+ analytes were analyzed to identify potential biomarkers associated with baseline clinical measures of NAFLD/NASH [Magnetic Resonance Imaging-Proton Density Fat Fraction (MRI-PDFF), alanine aminotransferase (ALT) and aspartate aminotransferase (AST)] as well as biomarkers of treatment response to ACCi. SomaSignal NASH probability scores identified biopsy-proven/clinically defined NIT-based (Presumed) NASH classification of the cohort with > 70% agreement. Clesacostat-induced reduction in steatosis probability scores aligned with observed clinical reduction in hepatic steatosis based on MRI-PDFF. We identify a set of 69 analytes that robustly correlate with clinical measures of hepatic inflammation and steatosis (MRI-PDFF, ALT and AST), 27 of which were significantly reversed with ACC inhibition. Clesacostat treatment dramatically upregulated Wnt5a protein and Apolipoproteins C3 and E, with drug-induced changes significantly correlating to changes on MRI-PDFF. Our data demonstrate the utility of SomaLogic- analyte panel for diagnosis and treatment response in NAFLD/NASH and provide potential new mechanistic insights into liver steatosis reduction, inflammation and serum triglyceride elevation with ACC inhibition. (Clinical Trial Identifier: NCT03248882).