Comprehensive Biomarker Research Articles

Unveiling Aquatic Organism Health Through eProteins: A Contemporary Perspective

Environmental DNA (eDNA) analysis has transformed our understanding of aquatic ecosystems, but traditional methods often lack insights into organismal health. The emerging field of environmental protein (eProtein) analysis offers a novel approach to monitoring the physiological status of aquatic organisms. Recent advancements in proteomic technologies have enabled the detection and characterization of stress-responsive proteins in water samples, providing valuable insights into organismal health and environmental stressors. This perspective paper explores the potential of eProtein analysis for monitoring aquatic organism health, disease dynamics and reproductive cycles. Methodological advancements in protein extraction and mass spectrometry have enhanced the sensitivity and specificity of eProtein analysis, facilitating comprehensive molecular profiling and biomarker identification. By integrating eProtein analysis into aquaculture management and environmental monitoring, researchers can proactively manage fish health, mitigate disease outbreaks and safeguard aquatic ecosystems. Future research directions include refining extraction methods, establishing standardized protocols and leveraging interdisciplinary collaborations to maximize the potential of eProtein analysis for aquatic research and conservation.

Comprehensive echocardiographic and biomarker assessment of patients with diabetic ketoacidosis

BackgroundSystemic stress, inflammation, and hydroelectrolytic and acid‒base abnormalities observed during diabetic ketoacidosis (DKA) can cause changes in the heart and even induce cardiovascular damage. We aimed to evaluate the structure and function of the heart during and after a DKA episode via echocardiography and biomarker assessment.MethodsWe performed a transthoracic echocardiogram (TTE) in subjects with an episode of DKA in the first 4–6 h of treatment. We evaluated left ventricular wall thickness, diameters and volumes, as well as systolic and diastolic function using tissue Doppler imaging, pulsed wave Doppler and left ventricular ejection fraction (LVEF). Left ventricular function was also assessed with global longitudinal strain (GLS). We obtained cardiac troponin levels in the first 24 h after admission. A second TTE was performed following the same protocol 6–12 h after the resolution of the DKA episode.ResultsWe included a total of 20 subjects. The mean age was 33 ± 13.6 years; 70% were female, and 70% had type 1 DM. 75% of the patients experienced severe episodes, and the rest experienced moderate episodes. Left ventricular isovolumetric contraction and ejection time were significantly shorter during DKA and prolonged after the resolution of the episodes (47.6 ± 9.9 vs. 62.2 ± 14.1, p = < 0.001) and (218.6 ± 37.9 vs. 265.06 ± 34.7). The isovolumetric relaxation time was also shorter during DKA, (41.72 ± 8.29 vs. 59.32 ± 17.98, p = < 0.001). Volumes and diameters of the left ventricle increased significantly after DKA resolution. We found no difference between LVEF or GLS during and after DKA resolution. 20% of the participants had troponin elevations, half of whom had moderate episodes and half of whom had severe episodes. 35% had LV dysfunction, 28.5% both in GLS and LVEF. 28.5% occurred after DKA resolution, with alterations in GLS.ConclusionsDiabetic ketoacidosis induces changes in the structure and function of the heart, which are mostly transient, reflect the presence of a hyperdynamic state and resolve after the resolution of the episode. Some subjects present with evidence of myocardial injury with elevated cardiac troponin and left ventricular dysfunction.Graphical abstractIcons in the graphical abstract are made by Freepik from www.flaticon.com.

Global Immune-Nutrition-Inflammation Index as a novel comprehensive biomarker in predicting the radiation-induced trismus rates in locally advanced nasopharyngeal carcinoma patients.

In this study, we aimed to evaluate whether the novel pretreatment Global Immune-Nutrition-Inflammation Index (GINI) can predict radiation-induced trismus (RIT) in locally advanced nasopharyngeal carcinoma (LA-NPC) patients undergoing concurrent chemoradiotherapy (CCRT). Data of LA-NPC patients presenting without RIT were reviewed retrospectively. Any post-CCRT maximum mouth openings (MMO) ≤ 35 mm were considered RIT. The GINI index was calculated using the formula: GINI = (CRP x Monocytes x Platelets x Neutrophils) ÷ (Albumin x Lymphocytes). We used receiver operating characteristic (ROC) curve analysis to examine the potential correlation between pretreatment GINI measures and post-CCRT RIT status. Logistic regression analysis examined the independence of the association between confounding factors and RIT rates. The study comprised 230 participants, and 52 (22.6%) received an RIT diagnosis. The optimal pre-CCRT GINI cutoff that dichotomizes RIT rates was determined to be 1,424 (area under the curve [AUC]: 76%; sensitivity: 75.0%; specificity: 71.7%; J-index: 0.463). RIT incidence was significantly higher in the GINI ≥ 1424 group than in its GINI < 1424 counterpart (43.3% vs. 9.3%; hazard ratio: 4.76; P < 0.001). Multivariate logistic regression analysis revealed that a pre-CCRT GINI ≥ 1424 was an independent predictor of increased RIT rates after definitive CCRT in this patient group (P < 0.001). In conclusion, the present results revealed that elevated pre-CCRT GINI measures (≥ 1424) can efficiently and independently predict elevated RIT rates in LA-NPC patients after CCRT.

Comprehensive biomarker and modeling approach to support dose finding for BI 836880, a VEGF/Ang-2 inhibitor

BackgroundBI 836880 is a humanized bispecific nanobody® that binds to and blocks vascular endothelial growth factor (VEGF) and angiopoietin-2 (Ang-2). A comprehensive biomarker and modeling approach is presented here that supported dose finding for BI 836880.MethodsTwo Phase I dose-escalation studies (1336.1 [NCT02674152], 1336.6 [NCT02689505]) assessed BI 836880 in adults with confirmed locally advanced or metastatic solid tumors, refractory to standard therapy or for which standard therapy was not reliably effective. Two dosing schedules were investigated, 3 weeks (q3w) or once weekly (qw), starting at a dose of 40 mg. In a comprehensive biomarker approach, soluble pharmacodynamic markers (free and total plasma VEGF-A and Ang-2), as well as circulating angiogenic factors (soluble VEGF3, soluble Tie2 and placenta growth factor, amongst others) were analyzed to assess target engagement in peripheral blood for q3w doses. A Population based pharmacokinetics/pharmacodynamics (PopPK/PD) model was built using the limited Phase I dataset to support dose finding by simulations. In order to demonstrate drug activity in the tumor, dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) was applied.ResultsDCE-MRI scans supported target engagement in the tumor. Free VEGF-A was depleted at all doses, whereas free Ang-2 decreased dose-dependently, reaching depletion in most patients from 360 mg q3w onwards. While total VEGF-A levels increased in a dose-dependent manner, reaching saturation at 360 mg q3w, total Ang-2 levels increased, but did not plateau. Angiogenic biomarkers showed changes from doses ≥ 360 mg q3w. PopPK/PD modeling showed that doses ≥ 360 mg q3w led to > 90% inhibition of free Ang-2 at steady-state in most patients. By increasing the dose to ≥ 500 mg q3w, > 90% of patients are expected to achieve this level.ConclusionsThe comprehensive analyses of multiple target engagement markers support BI 836880 720 mg q3w as a biologically relevant monotherapy dose schedule.Trial registration: NCT02674152 and NCT02689505.

Potential of plasma biomarkers for heart failure prediction, management, and prognosis: A multiomics perspective.

Heart failure (HF) remains a major global health challenge, and more effective and comprehensive plasma biomarkers are needed to effectively treat HF patients. Multiomics studies have shown that DNA fragments, noncoding RNAs, proteins, and metabolites may be potential plasma biomarkers for HF. However, comprehensive reviews that focus on research on plasma biomarkers for HF from an omics perspective are lacking. This review summarizes the applications of various omics approaches in the exploration of biomarkers related to the risk assessment, diagnosis, subtype classification, medical management, and prognosis prediction of HF. Moreover, as heart transplantation and left ventricular assistant device (LVAD) implantation are terminal therapies for end-stage HF patients, this review also discusses the role of cell-free DNA as a biomarker for cardiac transplant rejection and omics studies of plasma biomarkers in patients who respond to LVAD therapy. Our findings suggest that future omics research on HF biomarkers should employ integrated multiomics methods and expand the sample size to increase the robustness of the results and that the identified biomarkers should be further validated in large cohorts.

A Novel Nutrition-Related Prognostic Biomarker for Predicting Survival in Patients with Colorectal Cancer

Background Colorectal cancer (CRC) is a prevalent global malignancy with substantial morbidity and mortality. Accurate prognostic evaluation is essential in CRC patient management. This study investigates the prognostic significance of red blood cell count (RBC) and Onodera’s prognostic nutritional index (OPNI) in resectable CRC patients. Methods A retrospective analysis of 210 CRC patients undergoing radical resection (January 2015–January 2017) assessed clinical and hematological factors, including RBC, albumin, hemoglobin, and OPNI. A novel comprehensive biomarker, R-OPNI, combining preoperative RBC with OPNI, was introduced. Correlations with patient survival were analyzed, and R-OPNI’s independent prognostic value was assessed through univariate and multivariate Cox models. Predictive ability was compared to other factors using the receiver operating characteristic (ROC) method. Results Higher RBC levels (≥ 3.9 × 1012/L) and elevated OPNI were associated with significantly improved overall survival. Lower R-OPNI scores (0 or 1) indicated notably poorer survival. Multivariate analysis confirmed R-OPNI’s independent prognostic significance (HR: 0.273, 95% CI: 0.098–0.763, p = 0.013). R-OPNI (AUC = 0.732) demonstrated superior predictive value compared to individual prognostic factors. Conclusion R-OPNI emerges as a robust, independent prognostic predictor for resectable CRC patients, emphasizing the importance of assessing preoperative nutritional status.

IMPACT-NSCLC: Innovative machine-learning protocols for accurate clinical biomarker testing in non-small cell lung cancer (NSCLC).

84 Background: Lung cancer is often detected in advanced stages and can benefit from biomarker testing to identify targeted therapeutics. The IMPACT-NSCLC study was designed to identify barriers to equitable biomarker testing for lung cancer patients and develop targeted interventions to help improve biomarker testing rates using a digital personal health record and AI-enabled analysis. Methods: IMPACT-NSCLC unites the O'Neal Comprehensive Cancer Center (UAB) and Novellia, a leading personal health record tool, in a two-part single-institution study of adult NSCLC patients. Novellia uses proprietary technology and AI-enabled services to help patients digitally collect retrospective health records from providers and track health records prospectively, offering researchers a novel method of collecting and evaluating longitudinal health data. Part 1 of the study involves a retrospective study of patients with advanced NSCLC, with advanced data modeling to identify barriers and predictive factors in biomarker testing. Part 2 focuses on developing, implementing, and evaluating targeted interventions based on Part 1’s findings with the goal of improving biomarker testing rates in both academic and community settings. Results: In Part 1, data were collected from 35 patients diagnosed with NSCLC from 2020-2024. Most were white (80.77%) and male (53.84%). Median age was 65 (range 51-79). Most received care at an academic (NCI-designated) cancer center (74.28%). Most were not on commercial insurance plans (85.71%), with the most common form being BCBS/Medicare B and Viva Medicare. Most patients had Stage IV NSCLC (82.85%). More patients received liquid NGS testing at diagnosis (91.42%) than tissue NGS testing at diagnosis (68.57%). Nearly all patients (82.85%) received combination therapy, such as pemetrexed, and pembrolizumab, following biomarker testing. Oncologists initiated treatment while biomarker testing results were pending or incomplete more often in non-academic settings (55.55% of cases) vs. academic settings (26.92%). Conclusions: The pilot analysis found that patients with NSCLC typically received biomarker testing at diagnosis, more often with liquid biopsy. However, oncologists, especially in non-academic settings, often started treatment before full biomarker testing was completed. Comprehensive biomarker testing was frequently not done at progression. Further analysis leveraging machine learning and advanced modeling of Part 1 data may reveal more predictive factors for these variations, guiding interventions in Part 2. Developing a scalable best-practice guide for comprehensive biomarker testing could improve health system efficiencies and outcomes for patients with NSCLC.

Increasing access to biomarker-driven treatment for lung cancer in Alabama: The Alabama Access initiative.

159 Background: Lung cancer is the leading cause of cancer death in Alabama, with an estimated 2,550 deaths in 2024. Non-small cell lung cancer (NSCLC) represents 85% of these cases. Despite national guidelines recommending comprehensive biomarker testing (CBT) for metastatic NSCLC, significant disparities persist in the utilization of CBT and targeted therapies among Alabama residents. Methods: In March 2024, we launched the "Alabama Access" initiative – a partnership between the LUNGevity Foundation and the O’Neal Comprehensive Cancer Center at the University of Alabama at Birmingham – to foster academic and community oncology partnerships to increase access to biomarker-driven treatments. We used a population health science and geospatial mapping approach to visualize oncology practices serving counties with Alabama's highest lung cancer burden. Practices in Walker, Dothan, Marengo, Morgan, Jackson, Marshall, and Montgomery counties were identified as the highest priority based on annual mortality rates. Key interventions will include virtual molecular tumor boards and oncology navigation to facilitate the integration of resources and expertise and ensure that patients in nonacademic practices benefit from the latest advances in precision oncology. After roll-out, we will collect feasibility and acceptability data around program integration. Results: Our analysis revealed that 62.0% of the state’s population resides in Primary Care Health Professional Shortage Areas (HPSAs), and 58 out of 67 counties are classified as Medically Underserved Areas. The poverty rate in 89.6% of counties surpasses the national average, contributing to higher lung cancer incidence and mortality rates, with 62.0% of cases diagnosed at advanced stages. The state also shows a higher smoking prevalence, affecting 97.0% of counties compared to national figures. We will present practice-level testing data, including barriers to CBT. Conclusions: This pilot aims to mitigate disparities in CBT through enhanced collaboration between academic and community oncology settings. Integrating molecular navigation into community practices will be pivotal in disseminating program information and collecting data on current testing practices to improve overall lung cancer care quality in Alabama.

The American Cancer Society National Lung Cancer Roundtable strategic plan: Methods for improving turnaround time of comprehensive biomarker testing in non-small cell lung cancer.

Comprehensive biomarker testing for patients with non-small cell lung cancer is critical for selecting appropriate targeted therapy or immunotherapy. Ensuring timely ordering, processing, and reporting is key to optimizing patient outcomes. However, various factors can prevent or delay patients from being offered the option of treatment selection based on comprehensive biomarker testing. These factors include problems with access to testing, tissue adequacy, turnaround time, and health insurance coverage and billing practices. Turnaround time depends on several logistical and tissue handling factors, which involve institutional policies, processes, resources, testing methodology, and testing algorithms that vary across different practices. In this article, the authors identify key factors that prolong biomarker testing turnaround time, propose strategies to reduce it, and present a process map to aid physicians and key organizational stakeholders in improving testing efficiency.

The American Cancer Society National Lung Cancer Roundtable strategic plan: Advancing comprehensive biomarker testing in non-small cell lung cancer.

Comprehensive biomarker testing is a crucial requirement for the optimal treatment of advanced-stage non-small cell lung cancer (NSCLC), with emerging relevance in the adjuvant treatment setting. To advance its goal of ensuring optimal therapy for persons diagnosed with lung cancer, the American Cancer Society National Lung Cancer Roundtable (ACS NLCRT) held The Summit on Optimizing Lung Cancer Biomarkers in Practice in September 2020 to align its partners toward the goal of ensuring comprehensive biomarker testing for all eligible patients with NSCLC. The ACS NLCRT's Strategic Plan for Advancing Comprehensive Biomarker Testing in NSCLC, a product of the summit, comprises actions to promote comprehensive biomarker testing for all eligible patients. The approach is multifaceted, including policy-level advocacy and the development and dissemination of targeted educational materials, clinical decision tools, and guides to patients, physicians, and payers aimed at ameliorating barriers to testing experienced by each of these groups. PLAIN LANGUAGE SUMMARY: The ACS NLCRT works to improve care for patients with lung cancer. The ACS NLCRT supports comprehensive biomarker testing as essential to determine treatment options for all eligible patients with non-small cell lung cancer. Many factors lead to some patients not receiving optimal biomarker testing. The ACS NLCRT held a collaborative summit and developed a strategic plan to achieve and promote comprehensive biomarker testing for all patients. These plans include developing educational materials and physician tools and advocating for national policies in support of biomarker testing.

Comprehensive biomarker assessment for predicting severe acute kidney injury and need of kidney replacement therapy in liver transplantation patients

Background Renal dysfunction is a common complication following liver transplantation (LT). This study aimed to determine whether a comprehensive assessment of kidney function using nineteen serum and urinary biomarkers (BMs) within the first 48 h post-LT could enhance the prediction of severe acute kidney injury (AKI) and the need of kidney replacement therapy (KRT) during the first postoperative week. Methods Blood and urine (U) samples were collected during the pre- and postoperative periods. Nineteen BMs were evaluated to assess kidney health in the first 48 h after LT. Classification and regression tree (CART) cross-validation identified key predictors to determine the best BM combination for predicting outcomes. Results Among 100 LT patients, 36 developed severe AKI, and 34 required KRT within the first postoperative week. Preoperative assessment of U neutrophil gelatinase-associated lipocalin (NGAL) and liver-type fatty acid-binding protein (L-FABP) predicted the need for KRT with 75% accuracy. The combined assessment of U osmolality (OSM), U kidney injury molecule 1 (KIM-1), and tissue inhibitor of metalloproteinase (TIMP-1) within 48 h post-LT predicted severe AKI with 80% accuracy. U-OSM alone, measured within 48 h post-LT, had an accuracy of 83% for predicting KRT need, outperforming any BM combination. Conclusions Combined BM analysis can accurately predict severe AKI and KRT needs in the perioperative period of LT. U-OSM alone proved to be an effective tool for monitoring the risk of severe AKI, available in most centers. Further studies are needed to assess its impact on AKI progression postoperatively. Registered at Clinical Trials (clinicaltrials.gov) in March 24th, 2014 by title ‘Acute Kidney Injury Biomarkers: Diagnosis and Application in Pre-operative Period of Liver Transplantation (AKIB)’ and identifier NCT02095431.

Multi-Sensor Biomarker Using Accelerometer and ECG Data

The development of multi-sensor biomarkers offers a promising avenue for enhancing personalized healthcare and remote monitoring. This study focuses on the integration of accelerometer and electrocardiogram (ECG) data to create a comprehensive multi-sensor biomarker capable of assessing both physical activity and cardiovascular health. Accelerometers track movement patterns, activity levels, and postures, while ECG sensors monitor heart rate, heart rate variability (HRV), and overall cardiac function. By combining these data streams, it is possible to correlate physical exertion with heart performance, resulting in a more holistic health assessment. This research employs advanced machine learning algorithms to analyze synchronized accelerometer and ECG data, identifying patterns that reflect an individual's physiological state. The primary goal is to develop a reliable, real-time biomarker that can detect early signs of disease, monitor chronic conditions, and support preventive health measures. This multi-sensor approach aims to improve accuracy in health assessments by providing deeper insights into the relationship between physical activity and cardiovascular function.

Role of Fyn expression in predicting the sensitivity to platinum‑based chemotherapy in patients with ovarian serous carcinoma.

Ovarian serous carcinoma is a gynecological malignancy associated with a high mortality rate, which is commonly diagnosed in the first instance at a late stage and has a propensity to develop resistance to platinum-based chemotherapy. Identifying reliable biomarkers for platinum sensitivity is critical for improving patient outcomes. The present retrospective study included 64 patients with high-grade serous ovarian carcinoma (Federation of Gynecology and Obstetrics stages III or IV). Patients were classified as platinum-sensitive (no relapse within 6 months of the last platinum administration) or platinum-resistant (relapse within 6 months). Immunohistochemical analysis was performed to evaluate Fyn expression in tumor tissues, and Fyn knockdown experiments were performed using the OVSAHO ovarian cancer cell line to assess carboplatin sensitivity. Fyn expression was significantly higher in platinum-resistant patients compared with in platinum-sensitive patients (P<0.01). A weighted Fyn expression score was developed and a cutoff score of 6 was determined to predict platinum sensitivity with a specificity of 65.5% and a sensitivity of 62.9%. Patients with low Fyn expression (score ≤6) exhibited higher platinum sensitivity and longer overall survival (P<0.05). Multivariate analysis identified Fyn expression and postoperative residual tumor size as independent predictors of platinum sensitivity (P=0.033 and P=0.023, respectively). In vitro, Fyn knockdown significantly increased carboplatin sensitivity in ovarian cancer cells (P<0.05). Fyn, a member of the Src family of kinases, serves a crucial role in various cellular functions and has been implicated in chemotherapy resistance. The results demonstrated a notable association between Fyn expression and platinum sensitivity in ovarian serous carcinoma. The findings suggested that Fyn may serve as a predictive biomarker for response to platinum-based chemotherapy, offering the potential for more personalized treatment strategies. To the best of our knowledge, the present study is the first to establish an association between Fyn expression and platinum sensitivity in advanced ovarian serous carcinoma. Prospective studies with larger, multi-center cohorts and comprehensive biomarker analyses are recommended to validate and extend these results, ultimately improving therapeutic strategies and patient prognosis.

8-OxodG: A Potential Biomarker for Chronic Oxidative Stress Induced by High-LET Radiation.

Oxidative stress-mediated biomolecular damage is a characteristic feature of ionizing radiation (IR) injury, leading to genomic instability and chronic health implications. Specifically, a dose- and linear energy transfer (LET)-dependent persistent increase in oxidative DNA damage has been reported in many tissues and biofluids months after IR exposure. Contrary to low-LET photon radiation, high-LET IR exposure is known to cause significantly higher accumulations of DNA damage, even at sublethal doses, compared to low-LET IR. High-LET IR is prevalent in the deep space environment (i.e., beyond Earth's magnetosphere), and its exposure could potentially impair astronauts' health. Therefore, the development of biomarkers to assess and monitor the levels of oxidative DNA damage can aid in the early detection of health risks and would also allow timely intervention. Among the recognized biomarkers of oxidative DNA damage, 8-oxo-7,8-dihydro-2'-deoxyguanosine (8-OxodG) has emerged as a promising candidate, indicative of chronic oxidative stress. It has been reported to exhibit differing levels following equivalent doses of low- and high-LET IR. This review discusses 8-OxodG as a potential biomarker of high-LET radiation-induced chronic stress, with special emphasis on its potential sources, formation, repair mechanisms, and detection methods. Furthermore, this review addresses the pathobiological implications of high-LET IR exposure and its association with 8-OxodG. Understanding the association between high-LET IR exposure-induced chronic oxidative stress, systemic levels of 8-OxodG, and their potential health risks can provide a framework for developing a comprehensive health monitoring biomarker system to safeguard the well-being of astronauts during space missions and optimize long-term health outcomes.

Comprehensive biomarker analysis of metabolomics in different syndromes in traditional Chinese medical for prediabetes mellitus

BackgroundPrediabetes mellitus (PreDM) is a high-risk state for developing type 2 diabetes mellitus (T2DM) and often goes undiagnosed, which is closely associated with obesity and characterized by insulin resistance that urgently needs to be treated.PurposeTo obtain a better understanding of the biological processes associated with both "spleen-dampness" syndrome individuals and those with dysglycaemic control at its earliest stages, we performed a detailed metabolomic analysis of individuals with various early impairments in glycaemic control, the results can facilitate clinicians’ decision making and benefit individuals at risk.MethodsAccording to the diagnostic criteria of TCM patterns and PreDM, patients were divided into 4 groups with 20 cases, patients with syndrome of spleen deficiency with dampness encumbrance and PreDM (PDMPXSK group), patients with syndrome of dampness-heat in the spleen and PreDM (PDMSRYP group), patients with syndrome of spleen deficiency with dampness encumbrance and normal blood glucose (NDMPXSK group), and patients with syndrome of dampness-heat in the spleen and normal blood glucose (NDMSRYP group). Plasma samples from patients were collected for clinical index assessment and untargeted metabolomics using liquid chromatography-mass spectrometry.ResultsAmong patients with the syndrome of spleen deficiency with dampness encumbrance (PXSK), those with PreDM (PDMPXSK group) had elevated levels of 2-hour post-load blood glucose (2-h PG), glycosylated hemoglobin (HbA1c), high-density lipoprotein cholesterol (HDL-C), and systolic blood pressure (SBP) than those in the normal blood glucose group (NDMPXSK group, P < 0.01). Among patients with the syndrome of dampness-heat in the spleen (SRYP), the levels of body mass index (BMI), fasting blood glucose (FBG), 2-h PG, HbA1c, and fasting insulin (FINS) were higher in the PreDM group (PDMSRYP group) than those in the normal blood glucose group (NDMSRYP group, P < 0.05). In both TCM syndromes, the plasma metabolomic profiles of PreDM patients were mainly discriminatory from the normal blood glucose controls of the same syndrome in the levels of lipid species, with the PXSK syndrome showing a more pronounced and broader spectrum of alterations than the SRYP syndrome. Changes associated with PreDM common to both syndromes included elevations in the levels of 27 metabolites which were mainly lipid species encompassing glycerophospholipids (GPs), diglycerides (DGs) and triglycerides (TGs), cholesterol and derivatives, and decreases in 5 metabolites consisting 1 DG, 1 TG, 2 N,N-dimethyl phosphatidylethanolamine (PE-NMe2) and iminoacetic acid. Correlation analysis identified significant positive correlations of 3α,7α,12α,25-Tetrahydroxy-5β-cholestane-24-one with more than one glycaemia-related indicators, whereas DG (20:4/20:5) and PC (20:3/14:0) were positively and PC (18:1/14:0) was inversely correlated with more than one lipid profile-related indicators. Based on the value of correlation coefficient, the top three correlative pairs were TG with PC (18:1/14:0) (r = − 0.528), TG with TG (14:0/22:4/22:5) (r = 0.521) and FINS with PE-NMe (15:0/22:4) (r = 0.52).ConclusionOur results revealed PreDM patients with different TCM syndromes were characterized by different clinical profiles. Common metabolite markers associated with PreDM shared by the two TCM syndromes were mainly lipid species encompassing GP, GL, cholesterol and derivatives. Our findings were in line with the current view that altered lipid metabolism is a conserved and early event of dysglycaemia. Our study also implied the possible involvement of perturbed bile acid homeostasis and dysregulated PE methylation during development of dysglycaemia.

Investigation of the Usefulness of HALP Score in Predicting Short-Term Mortality in Patients with Acute Decompensated Heart Failure in a Coronary Care Unit.

Background/Objectives: Acute decompensated heart failure (ADHF) presents a significant clinical challenge characterized by frequent hospitalizations, high mortality rates, and substantial healthcare costs. The united index of hemoglobin, albumin, lymphocytes and platelets (HALP) is a new indicator that reflects systemic inflammation and nutritional status. This study aimed to investigate the prognostic utility of the HALP score and hematological parameters in predicting short-term mortality among ADHF patients admitted to the coronary care unit (CCU). Methods: This investigation adopts a retrospective observational design, encompassing a cohort of patients with ADHF who were followed in the CCU at our medical institution between January 2019 and April 2024. Results: The cohort of 227 individuals was dichotomized into two subsets based on the presence or absence of short-term mortality in the hospital, resulting in 163 (71.8%) and 64 (28.2%) individuals in the survivor and exitus groups, respectively. Age was significantly higher in the exitus group (p-value = 0.004). Hemoglobin, lymphocyte count, platelet count, albumin, and HALP score were significantly higher in the survivor group (all p-values < 0.001). No significant difference was observed between the groups in terms of gender, diabetes mellitus (DM), coronary artery disease (CAD), or ejection fraction (EF), although hypertension (HT) prevalence was significantly higher in the exitus group (p-value = 0.038). ROC analysis demonstrated that hemoglobin, lymphocyte, albumin, and HALP score had significant discriminative power, with albumin showing the highest AUC (0.814). Conclusions: In conclusion, the HALP score and hematological parameters represent valuable prognostic feature for short-term mortality prediction in ADHF patients admitted to the CCU. These findings underscore the importance of early risk stratification and targeted interventions guided by comprehensive biomarker assessments in optimizing patient outcomes.

The cellular senescence score (CSS) is a comprehensive biomarker to predict prognosis and assess senescence and immune characteristics in hepatocellular carcinoma (HCC)

Cellular senescence, an emerging hallmark of cancer, has garnered increasing attention in recent years. However, its role in hepatocellular carcinoma (HCC) is still not well understood. Furthermore, there is a lack of comprehensive biomarkers to predict prognosis and assess senescence and immune characteristics in HCC patients. To address these gaps, we conducted functional studies on bleomycin-induced senescent Hepa1-6 cells and developed the Cellular Senescence Score (CSS) based on four core cellular senescence-related genes. We found that the cellular senescence signaling pathway was enriched among the risk genes associated with unfavorable prognosis in HCC patients. The senescence associated secretory phenotype (SASP) derived from senescent Hepa1-6 cells induced an increase in CD3+ CD8+ CD279+ T cells. The senescent Huh7 cells expressed higher levels of pro-angiogenic genes compared to their immortal counterparts. The CSS was constructed on the basis of BMI1, EZH2, NPM1, and ME1. HCC Patients in the high-CSS group had significantly shorter overall survival compared to those in the low-CSS group. In contrast to the low-CSS group, the high-CSS group exhibited more senescence characteristics at both the overall tumor microenvironment and single-cell levels. Three distinct senescence patterns were identified in hepatoma cells: oxidative stress related senescence, metabolism related senescence, and immune related senescence. The high-CSS group showed elevated TP53 mutation rate, diminished immune cell infiltration, and enhanced expression levels of immune checkpoint molecules compared to the low-CSS group. Moreover, the high-CSS group displayed a greater proportion of patients responsive to immune checkpoint therapy compared to the low-CSS group. In summary, the impacts of cellular senescence on HCC are multifaceted, and the tumor-promoting effects may be caused by SASP remodeling the HCC microenvironment rather than by the senescent hepatoma cells themselves. The CSS is a promising biomarker capable of predicting prognosis and assessing senescence and immune characteristics in HCC.

Defining the Soluble and Extracellular Vesicle Protein Compartments of Plasma Using In-Depth Mass Spectrometry-Based Proteomics.

Plasma-derived extracellular vesicles (pEVs) are a potential source of diseased biomarker proteins. However, characterizing the pEV proteome is challenging due to its relatively low abundance and difficulties in enrichment. This study presents a streamlined workflow to identify EV proteins from cancer patient plasma using minimal sample input. Starting with 400 μL of plasma, we generated a comprehensive pEV proteome using size exclusion chromatography (SEC) combined with HiRIEF prefractionation-based mass spectrometry (MS). First, we compared the performance of HiRIEF and long gradient MS workflows using control pEVs, quantifying 2076 proteins with HiRIEF. In a proof-of-concept study, we applied SEC-HiRIEF-MS to a small cohort (12) of metastatic lung adenocarcinoma (LUAD) and malignant melanoma (MM) patients. We also analyzed plasma samples from the same patients to study the relationship between plasma and pEV proteomes. We identified and quantified 1583 proteins in cancer pEVs and 1468 proteins in plasma across all samples. While there was substantial overlap, the pEV proteome included several unique EV markers and cancer-related proteins. Differential analysis revealed 30 DEPs in LUAD vs the MM group, highlighting the potential of pEVs as biomarkers. This work demonstrates the utility of a prefractionation-based MS for comprehensive pEV proteomics and EV biomarker discovery. Data are available via ProteomeXchange with the identifiers PXD039338 and PXD038528.

Association between the non-high-density lipoprotein cholesterol to high-density lipoprotein cholesterol ratio (NHHR) and risk of endometrial cancer among US adults: A population-based study.

123 Background: Endometrial cancer, as one of the metabolic-related malignancies, is becoming a significant public health concern worldwide. The non-high-density lipoprotein cholesterol to high-density lipoprotein cholesterol ratio (NHHR) has emerged as a comprehensive biomarker of various lipid-related metabolic disorders. However, the association of NHHR with endometrial cancer risk remains unclear to date. Therefore, we conducted this nationwide cross-sectional study to investigate the association of NHHR with the risk of endometrial cancer among US adults. Methods: Data were obtained from the National Health and Nutrition Examination Survey (1999–2018). Female participants who provided complete data on the NHHR and endometrial cancer were enrolled. The association of the NHHR with endometrial cancer was assessed by multivariate logistic regression analyses, adjusted by multiple potential confounders. Meanwhile, sensitivity analyses and subgroup analyses were conducted. Results: A total of 25,411 eligible participants were enrolled, including 214 (0.8%) women with endometrial cancer. The fully-adjusted multivariate logistic model showed a significantly positive association of NHHR with the endometrial cancer risk (odds ratio [OR] 1.15, 95% confidence interval [CI]: 1.05–1.25; P=0.003). Comparing the highest to the lowest quartile of NHHR, the fully-adjusted OR was 1.52 (95% CI: 1.02–2.28, P for trend=0.017). In subgroup analyses, the significantly positive association between NHHR and the risk of endometrial cancer was also found in non-obese women (OR 1.18, 95% CI: 1.04–1.35, P=0.012), women without diabetes (OR 1.15, 95% CI: 1.02–1.30, P=0.027), women with hypertension (OR 1.15, 95% CI: 1.03–1.28, P=0.012), women who use oral contraceptives (OR 1.16, 95% CI: 1.04–1.30, P=0.009) and in parous women(OR 1.15, 95% CI: 1.05–1.27, P=0.003). Additionally, in the sensitivity analysis by excluding participants with NHHR below 5% or above 95% in total cohort, the positive association of NHHR with endometrial cancer risk remained significant (OR 1.21, 95% CI: 1.03–1.42, P=0.018). Conclusions: This population-based study found that a higher NHHR correlated with an increased risk of endometrial cancer among the US population. Our findings suggested that NHHR might be a promising tool for the risk assessment of endometrial cancer. Prospective studies are necessary to further verify these findings. [Table: see text]

Advanced Lung Cancer Inflammation Index: A Novel Comprehensive Biomarker of Host Status for Patients with Metastatic Colorectal Cancer.

Numerous biomarkers that reflect host status have been identified for patients with metastatic colorectal cancer (mCRC). However, there has been a paucity of biomarker studies that comprehensively indicate body composition, nutritional assessment, and systemic inflammation status. The advanced lung cancer inflammation index (ALI), initially introduced as a screening tool for patients with non-small-cell lung cancer in 2013, emerges as a holistic marker encompassing all body composition, nutritional status, and systemic inflammation status. The index is calculated by the simple formula: body mass index × albumin value / neutrophil-to-lymphocyte ratio. Given its accessibility in routine clinical practice, the ALI has exhibited promising clinical utility in prognosticating outcomes for patients with multiple types of cancer. In this review, we focus on the significance of host status and the clinical applicability of the ALI in the treatment and management of patients with malignancies, including mCRC. We also suggest its potential in guiding the formulation of treatment strategies against mCRC and outline future perspectives.