Prognostic Biomarker Research Articles

Application of Nexus Learning framework for Personalized Medicine and Drug Development

Biological systems provide an enormous amount of knowledge on development and disease. The pharmaceutical industry is facing new possibilities and challenges with the rise of high-throughput methods to study disease and biology. The aim is to develop drugs based on acceptable therapeutic assumptions. Nexus Learning provides a variety of tools that help improve discovery and decision making using extensive, high-quality data and well-specified queries. Potential applications of NLF can be found across the whole drug development process. Clinical study target validation, prognostic biomarker discovery, and digital pathology data processing are a few examples. There has been a wide variety of applications in terms of technique and environment, with some methods producing reliable forecasts and insights. The primary problem with using NLF is that the findings provided by NL tend to be easy to understand or reproduce, which can limit their value. The collection of complete and methodical high-dimensional data remains an essential need across all domains. By addressing these challenges and increasing understanding about what is required to verify NLF methodologies, we can employ NLF to make data-driven decisions, which can speed up drug discovery and development and minimize failure rates.

Identification of alternative lengthening of telomeres-related genes prognosis model in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is a common malignant tumor worldwide, characterized by high mortality. This study aimed to explore the prognostic value and function of alternative lengthening of telomeres (ALT)-related genes in HCC. Differentially expressed genes (DEGs) were identified based on The Cancer Genome Atlas (TCGA) and then intersected with ALT-related genes to obtain ALTDEGs. Risk score model was constructed using the least absolute shrinkage and selection operator (LASSO) algorithm and Cox regression and validated with Gene Expression Omnibus (GEO) datasets. The predictive efficacy of the risk score and ALTs-score was evaluated by Kaplan-Meier curves, time-ROC curves, and the nomogram analyses. The impacts of SMG5 silencing on the HCC cell behaviors were assessed by CCK-8, wound healing, and Transwell assays. A total of 500 ALTDEGs were screened and 13 genes (CDCA8, SMG5, RAD54B, FOXD2, NOL10, RRP12, CCT5, CCT4, HDAC1, DDX1, HRG, HDAC2, and PPP1CB) were identified for constructing a prognostic model. The overall survival (OS) curves, time-ROC curves, and nomograms based on the risk score or ALTs-score were developed to optimally predict the survival of HCC patients. ALTs-score was correlated with immune infiltration and confirmed its value in predicting immunotherapy outcomes. Furthermore, RT-qPCR demonstrated that eight risk signature genes were up-regulated in HCC cells. SMG5 silencing suppressed the proliferation, migration, and invasion of HCC cells. It was also found that SMG5 silencing reduced C-circle level in SNU-387 cells. We identified new ALT-related prognostic biomarkers for HCC. SMG5 knockdown inhibited the HCC progression, which might be a promising target for HCC therapy.

BIOM-48. UTILITY OF CIRCULATING TUMOR DNA (CTDNA) FROM CEREBROSPINAL FLUID (CSF) FOR PROGNOSIS OF PATIENTS WITH RECURRENT HIGH-GRADE GLIOMA

Abstract High-grade gliomas (HGGs) are the most aggressive primary brain tumors, and molecular characterization is vital for their diagnosis and treatment. Due to their location, tumor sampling is often challenging. Therefore, developing minimally invasive diagnostic methods is urgently needed. Here we report that circulating tumor DNA (ctDNA) from cerebrospinal fluid (CSF) can identify key genomic alterations and track clonal evolution in HGGs. Detection of CSF ctDNA correlates with leptomeningeal disease and overall survival, indicating its potential for integration into clinical decision-making. Our study includes 313 samples from 253 patients with recurrent glioma treated at MSKCC who underwent CSF collection using the MSK-IMPACT targeted sequencing assay. 37% of genomic alterations were detected using our less stringent variant calling criteria and Gaussian Mixture Model to call copy number events. CSF ctDNA positivity was determined by the presence of at least one oncogenic disease-defining alteration or any shared alteration with the tumor. We found 212 CSF ctDNA positive (68%) and 101 CSF ctDNA negative (32%) samples. CSF ctDNA positivity was the highest amongst histone mutant tumors (96%). We noticed 44% of alterations shared between the tumor and the CSF, additionally, we noted considerable tumor evolution particularly within the growth signaling pathways (e.g. PDGFRA). Our cohort demonstrated that patients with positive CSF ctDNA had a significantly shorter overall survival compared to those who were CSF ctDNA negative (4.83 months vs 14.14 months, HR 2.4, p < 0.001). Radiographic findings such as enhancing disease and contact of the tumor with the ventricular space were positively associated with CSF ctDNA positivity. Additionally, CSF ctDNA was associated with positive cytology in 12/12 cases (100%). With our improved pipeline, we hypothesize CSF ctDNA may be used as a prognostic biomarker for survival, but confirmation requires further validation in a prospective study.

Neutrophil-albumin ratio serves as a superior prognostic biomarker for traumatic brain injury.

Traumatic brain injury (TBI) represents a common and severe medical condition necessitating prompt risk stratification to enhance patient outcomes. Although substantial research has been conducted on the prognostic utility of various biomarkers for TBI, no single biomarker has been definitively recognized as the most precise predictor of disease outcomes. In comparison to other markers, the neutrophil-albumin ratio (NAR) has emerged as a cost-effective and reproducible inflammatory biomarker, demonstrating potential in evaluating the severity of inflammation and prognosticating outcomes in infections and cerebrovascular diseases. This study evaluated the prognostic significance of the NAR in comparison to two other readily accessible and cost-effective composite indices: the Neutrophil-Lymphocyte Ratio (NLR) and the Platelet-Lymphocyte Ratio (PLR) in individuals with TBI. We conducted a retrospective cohort analysis involving 297 hospitalized TBI patients, gathering comprehensive demographic, anthropometric, medical, clinical, laboratory, and imaging data to assess the expression changes of these biomarkers. Our findings suggest that both the NAR and the NLR possess predictive value regarding prognosis following TBI. However, receiver operating characteristic (ROC) curve analysis revealed that NAR outperformed NLR as a prognostic predictor. In conclusion, our examination of blood biochemistry composite indicators indicates that, while both NAR and NLR serve as significant prognostic markers, NAR is a more effective predictor of outcomes in patients with TBI.

PATH-53. DNA MUTATION SEQUENCING AND METHYLATION ANALYSIS OF SOMATICNF1 MUTANT IDH-WILDTYPE GLIOBLASTOMA IDENTIFIES THREE EPIGENETIC GROUPS ANDCDKN2A/B LOSS AS A NEGATIVE PROGNOSTIC BIOMARKER

Abstract The tumor suppressor NF1 is frequently mutated in IDH-wildtype glioblastoma. However, the molecular subgroups and clinically relevant biomarkers within somatic NF1 mutant, IDH-wildtype glioblastomas remain incompletely understood. Here, we combine methylation arrays and targeted DNA sequencing to identify epigenetic subgroups and clinical biomarkers within non-syndromic NF1 mutant IDH-wildtype glioblastoma. We identified 186 patients treated at the University of California San Francisco between 2016-2024 with newly diagnosed IDH-wildtype glioblastoma containing a somatic pathogenic NF1 mutation on a CLIA certified targeted DNA sequencing assay. Illumina EPIC DNA methylation arrays (n=129 patients) were processed using the minfi package and Heidelberg random forest classifier (v12.8). Downstream analyses including hierarchical clustering and survival analyses were performed in R. DNA sequencing identified 12 recurrently altered genes in greater than 10% of cases across cell cycle regulators (CDKN2A/B, TP53, RB1), PI3K signaling (PTEN, PIK3R1, PIK3CA), epigenetic modifiers (ATRX, SETD2), and growth factor signaling (EGFR, PDGFRA, PTPN11). DNA methylation analysis revealed three epigenetic subgroups. Group 1 showed lower median patient age and significantly increased TP53 co-mutation rate. Group 2 contained a significantly higher proportion of male patients and was significantly enriched for RB1 and TERT promoter alterations, with a majority of tumors classified as GBM-MES using the Heidelberg classifier. Group 3 showed a significantly higher proportion of female patients and was significantly enriched for homozygous CDKN2A/B deletion. Homozygous CDKN2A/B loss was associated with significantly worse overall survival across the entire non-syndromic NF1 mutant glioblastoma cohort but not in a propensity score matched NF1 wildtype glioblastoma cohort. DNA methylation profiling revealed three epigenetic subgroups characterized by distinct clinical features, co-mutation patterns, and reference DKFZ methylation classifier identities. CDKN2A/B loss may be a negative prognostic biomarker specifically in NF1 mutant glioblastomas; future multi-institutional studies are required to validate these findings and their therapeutic implications in a larger, representative cohort.

Shedding of membrane complement inhibitors CD59 and CD46 into the circulation is associated with poor prognosis in acute coronary syndrome patients: a cohort study

IntroductionThe role of the complement inhibitory proteins CD46 and CD59 in the immune response to an acute coronary syndrome (ACS) is unknown. We investigated the relationships between the shedding of CD46 and CD59 into the circulation, reflected by plasma levels of soluble CD46 and CD59, and the risk for post-ACS complications.MethodsWe measured plasma sCD46 and sCD59 in a cohort of 546 ACS patients within 24 h after hospital admission, and after 6-weeks in a subgroup of 114 patients. Study outcomes were incident heart failure (HF), major adverse cardiovascular events (MACE) and mortality during a median follow-up period of up to 3.3 years. Echocardiography at 1-year was performed in the follow-up subgroup.ResultsElevated sCD46 and sCD59 were correlated with increased levels of inflammatory mediators and metalloproteinases in plasma, and were associated with increased risk for MACE in Cox proportional hazard models adjusted for cardiovascular risk factors and revascularization [HR 95% CI 1.24 (1.02–1.52), p = 0.034 for sCD46 and 1.18 (1.00–1.38), p = 0.049 for sCD59]. Elevated sCD59 was also associated with higher incidence of HF [HR 95% CI 1.41 (1.15–1.74), p = 0.001], and with lower left ventricular ejection fraction at 1-year post-ACS (Spearman r = − 0.234, p = 0.020). We found no associations between plasma levels of the proteins at 6 weeks and outcomes.ConclusionsShedding of the complement regulators CD46 and CD59 in plasma in the acute phase of ACS is associated with a negative prognosis. Plasma sCD46 and sCD59 could reflect the degree of local immune activation and serve as prognostic biomarkers in ACS patients.

Clinical Significance of Complement and Coagulation Cascades Genes for Patients With Acute Lymphoblastic Leukemia.

Acute lymphoblastic leukemia (ALL) is the second most common acute leukemia in adults and the 5-year survival remains low. We analyzed the gene expression profiles of the complement and coagulation cascades pathway (CCCP) in 998 bone marrow (BM) and 122 peripheral blood (PB) samples of ALL patients and healthy individuals obtained from the TCGA database and evaluated their clinical significance in terms of being diagnostic and prognostic biomarkers. We identified 18 CCCP genes (SERPINA1, C5AR1, F5, CD55, PLAUR, C3AR1, THBD, CD59, PLAU, VWF, CFD, F13A1, C1QA, C1QB, C1QC, A2M, SERPINE1 and CR2) differentially expressed in the BM samples of ALL patients compared to healthy individuals. The expression levels of CD55, F13A1 and CR2 in BM were linked with the overall survival of ALL patients. While in PB only 11 CCCP genes (e.g., SERPINA1, C5AR1, F5, PLAUR, C3AR1, THBD, CFD, F13A1, C1QA, SERPINE1, and CR2) were differentially expressed and F13A1 was significantly associated with ALL patient survival. Machine learning enabled us to predict ALL using the CCCP genes and the accuracy can reach 0.9701 and 0.9167 using the BM and PB, respectively. Furthermore, using single-cell RNA sequencing, we found that the differential expression of CCCP genes was found with diversity in the BM-derived immune cells of ALL patients. Our findings suggest that the CCCP genes may play a key role in the progression of ALL and can be used as potential therapeutic targets and diagnostic markers.

Clinical relevance of lung microbiota composition in critically ill children with acute lower respiratory tract infections: insights from a retrospective analysis of metagenomic sequencing.

Acute lower respiratory tract infections (ALRIs) is a leading cause of child mortality worldwide. Metagenomic next-generation sequencing (mNGS) identifies ALRIs pathogens and explores the lung microbiota's role in disease severity and clinical outcomes. This study examines the association between lung microbiota and ALRIs outcomes in children, exploring its potential as a prognostic biomarker. We retrospectively analyzed mNGS data from the bronchoalveolar lavage fluid (BALF) of 83 pediatric ALRIs patients from 2019 to 2023. Microbial diversity and relative abundances of specific taxa were compared between survivor and non-survivor groups, as well as between varying severity levels. LEfSe was employed to identify key biomarkers related to survival and disease severity. Among the 83 patients, 68 survived and 15 died. Patients were also divided into a low severity group (n = 38) and a moderate-to-very-high severity group (n = 45) according to mPIRO score at admission. Significant differences in beta diversity were observed between the survival groups and across different severity levels. Prevotella, Haemophilus and Veillonella exhibited higher abundances in both the survivor and low severity groups, suggesting their potential as predictors of better outcomes. Conversely, Enterococcus and Acinetobacter baumannii were more prevalent in the non-survivor and moderate-to-very-high severity groups. Additionally, Streptococcus pneumoniae and Streptococcus mitis showed increased abundances in survivors. LEfSe further revealed that these microorganisms may predict outcomes and severity in ALRIs. Our findings underscore the complex relationship between lung microbiota and ALRIs, with specific microbial profiles associated with disease severity and clinical outcomes. This underscores the need for further research to explore and validate its prognostic predictive capacity. Not applicable.

Extracellular DNA and Deoxyribonuclease Activity as Prognostic Markers in Sepsis

Background/Objectives: Sepsis is characterized by a dysregulated immune response to infection and is associated with high lethality. Extracellular DNA (ecDNA) has drawn significant interest as a damage-associated molecular pattern because of its potential involvement in the pathophysiology of sepsis. Methods: In this study, we examined the ecDNA concentration in 27 adult patients admitted to the intensive care unit. Fluorometry and quantitative PCR were used for the assessment of ecDNA. In addition, deoxyribonuclease activity was measured as a potential modulator of ecDNA. Results: Our findings reveal nearly 5-fold higher concentrations of ecDNA in non-survivors, suggesting its potential as a prognostic indicator for sepsis outcomes on day 7. Interestingly, the subcellular origin of ecDNA was similar between patients diagnosed with systemic inflammatory response syndrome, sepsis, and septic shock. Deoxyribonuclease activity, implicated in the cleavage of ecDNA, was comparable across all patient groups. Conclusions: To establish the prognostic value of ecDNA as a biomarker, further investigations within a larger patient cohort are needed. Nevertheless, our results suggest that high ecDNA in sepsis patients represents a negative prognostic biomarker.

Electrophysiological indices of reward anticipation as ADHD risk and prognostic biomarkers.

The attention-deficit/hyperactivity disorder (ADHD) clinical phenotype has limitations for deciphering ADHD etiology and predicting prognosis. Although relative to the clinical phenotype, intermediate phenotypes may have better explanatory and prognostic power, the extent to which ADHD intermediate phenotypes are associated with ADHD risk and prognosis is unknown. The aim of this study was to evaluate evidence for event-related potential (ERP) measures of reward anticipation as ADHD risk and prognostic biomarkers. We examined, whether (1) in a sample of adolescents (N = 304; Mage = 15.78years, SD = 1.08; 39.5% female), accounting for the effects of age, sex, ADHD severity and depression, ERPs are associated with ADHD polygenic risk scores (PRSs) (ADHD risk) and (2) in a sample of adolescents at-risk for ADHD (n = 99; Mage = 15.78years, SD = 1.08; 39.5% female), accounting for the effects of age, sex, ADHD severity, depression, and baseline outcome values, ERPs are associated, prospectively, with alcohol misuse (ADHD prognosis). In adolescents, greater ADHD PRSs were associated with lower electrophysiological anticipatory attention to motivationally relevant feedback (b = -0.115, p = .046 95%CI [-0.228; -0.002]). The predictors accounted for 5% of the variance in the outcome. In adolescents at-risk for ADHD, at 18-month follow-up, lower electrophysiological anticipatory attention to motivationally relevant feedback was associated with greater alcohol consumption (b = -7.454, p = .007, 95%CI [-12.873; -2.034]). The predictors accounted for 31% of the variance in this outcome. These findings were replicated in sensitivity analyses with behavioral performance variables added as covariates. The current findings support the hypothesis that ERP amplitudes of reward anticipation may be ADHD risk and prognostic biomarkers and suggest that intermediate phenotypes may confer advantages over the ADHD clinical phenotype in delineating etiology and predicting prognosis.

Association between hemoglobin-to-red blood cell distribution width ratio and chronic kidney disease: A cross sectional study.

The hemoglobin-to-red blood cell distribution width ratio (HRR) is recognized as a novel prognostic biomarker; however, studies exploring its relationship with chronic kidney disease (CKD) are scarce. This study used data from the National Health and National Health and Nutrition Examination Survey database from 2005 to 2018. The analysis included individuals aged ≥ 20 years who had complete HRR and CKD data. Weighted univariate and multivariate logistic regression analyses were used to assess the association between the HRR and CKD prevalence. Additionally, restricted cubic spline and subgroup analyses were conducted for further validation. Ultimately, 19,426 participants were included in this study. After adjusting for confounders, multivariate logistic regression analysis revealed a negative association between HRR and CKD (OR = 0.35, 95% CI = 0.22-0.56). In addition, restricted cubic spline regression analysis revealed a negative linear association between HRR and CKD, with higher levels of HRR associated with a lower prevalence of CKD. The subgroup analysis revealed that the negative association between HRR and CKD was stronger in the male population. HRR is negatively associated with the prevalence of CKD in the adult population of the US. HRR is a potential indicator for assessing the prevalence of CKD and provides a rationale for personalized management.

KRAS inhibitors may prevent colorectal cancer metachronous metastasis by suppressing TGF‑β mediated epithelial‑mesenchymal transition.

In colorectal cancer (CRC), KRAS mutations enhance metachronous metastasis, a condition without prognostic biomarkers or preventive measures. The present study demonstrated that KRAS mutation may be a risk factor for CRC metachronous metastasis through meta‑analysis of public databases. A risk scoring model was constructed using machine learning for predicting metachronous metastasis in KRAS‑mutant CRC. Wound healing and Transwell assay indicated that KRAS inhibitors strongly suppress migration and invasion capabilities of high‑risk CRC cells and these findings were validated through ex vivo organoid and a mouse model of splenic‑liver metastasis. Mechanistically, RNA sequencing, reverse transcription‑quantitative PCR and western blot analyses revealed that KRAS inhibitors suppressed epithelial‑mesenchymal transition (EMT) and transforming growth factor β (TGF‑β) signaling. Notably, addition of TGF‑β1 protein partially reversed the inhibitory effects of KRAS inhibitors on CRC. These results suggested that KRAS inhibitors may prevent CRC metachronous metastasis by downregulating TGF‑β‑mediated EMT, suggesting they can be used prophylactically in high‑risk KRAS‑mutant CRC.

Annexin A2 in Tumors of the Gastrointestinal Tract, Liver, and Pancreas

Annexin A2 (ANXA2) is a protein that is involved in many physiological and pathological cellular processes. There is compelling evidence that its dysregulated expression, be it up- or downregulation, contributes to the oncogenesis of various neoplasms, including those of the digestive system. The present review summarizes the current knowledge on the role of ANXA2 in the main tumors of the digestive system. The clinical significance of ANXA2 is primordial, due to its potential use as a diagnostic and prognostic biomarker, and as a part of therapeutic protocols. Certain preclinical studies have shown that inhibiting ANXA2 or disrupting its interactions with key molecules can suppress tumor growth, invasion, and metastasis, as well as increase the cancer cells’ sensitivity to treatment in various cancers. Further research is needed to fully elucidate the complex role of ANXA2 in the carcinogenesis of tumors of the digestive system, and to translate these findings into clinical applications for improved diagnosis, prognosis, and treatment.

Genomic, epigenomic and transcriptomic inter- and intra-tumor heterogeneity in desmoid tumors.

Desmoid tumors are bland fibroblastic tumors that do not metastasize but have a high rate of local recurrence. Previously published studies proposed two different transcriptomic signatures to predict relapse. Molecular heterogeneity has been well established in high-grade sarcomas but little is known about molecular variability within locally aggressive tumors such as desmoids. We performed transcriptomic profiling of 31 specimens from 20 primary desmoid tumors to identify genes predictive of relapse. We also performed multi-omic analysis including DNA methylation, copy number alterations, point mutations and gene expression on 24 specimens from different regions of primary and recurrent desmoid tumors from 3 patients (7-9 specimens per patient). We observed highly variable expression of transcriptomic prognostic signatures, both in patients who did or did not progress. Signatures associated with favorable and unfavorable outcome were detected in different regions within the same tumor. Further multi-omic studies showed remarkable intra- and inter-tumor heterogeneity of genomic, epigenomic and transcriptomic patterns. The transcriptomic profiles showed the highest degree of variability within tumors and between primary and recurrent tumors from the same patient. This study shows an unexpected degree of intra- and inter-tumor heterogeneity in desmoid tumors. Our analysis indicates that molecular analysis of a single tumor biopsy may underestimate the magnitude of molecular alterations in desmoid tumors. Our study also shows that recurrent desmoid tumors acquire multiple new molecular alterations. Thus, molecular heterogeneity is an important consideration in drug development and validation of prognostic and predictive biomarkers for desmoid tumors.

Comprehensive analysis of GPN1 in human cancer and its effects on the migration of hepatocellular carcinoma cells.

To investigate the prognostic value of GPN1 in cancer and its role in the migration of hepatocellular carcinoma (HCC or LIHC) cells, we used several databases to assess GPN1 expression levels and effects in human tumors. Furthermore, experiments were conducted to verify changes in GPN1 expression in HCC cell lines and explore its biological function. We found that GPN1 gene and protein expression were significantly increased in several tumor tissues. Higher GPN1 expression was associated with unfavorable overall survival. Additionally, there was a strong association between GPN1 expression and several clinicopathological features, according to multivariate Cox regression analysis. Moreover, GPN1 gene mutation and methylation were present in some tumors. A relationship was also found between GPN1 expression and immune infiltration. Notably, immune checkpoint analysis showed that GPN1 expression was correlated with PD-1/PDL-1 and CTLA-4, suggesting it may serve as a biomarker for predicting immune subtypes and response to immunotherapy in HCC. Enrichment analysis in HCC indicated that GPN1 is primarily involved in RNA metabolism. Additionally, drug sensitivity analysis revealed that GPN1 appeared to be responsive to 16 drugs. Finally, GPN1 upregulation was confirmed to promote the migration of HCC cells. This study provides a comprehensive overview of GPN1 in human cancer and demonstrates that GPN1 contributes to the migration of HCC cells, potentially serving as a prognostic and immunotherapy biomarker.

A tumor-naive ctDNA assay detects minimal residual disease in resected stage II or III colorectal cancer and predicts recurrence: subset analysis from the GALAXY study in CIRCULATE-Japan.

Analysis of circulating tumor DNA (ctDNA) may enable early identification of patients likely to relapse, presenting an opportunity for early interventions and improved outcomes. Tumor-naïve plasma-only approaches for molecular residual disease (MRD) assessment accelerate turnaround time, enabling rapid treatment decisions and ongoing surveillance. Plasma samples were obtained from 80 study participants with stage II or III colorectal cancer (CRC) selected from CIRCULATE-Japan GALAXY. MRD status was assessed using a tumor-naïve ctDNA assay (xM) that integrates methylation and genomic variant data, delivering a binary call. MRD was assessed at 4 weeks post-surgery (landmark timepoint (LMT)) using methylation and genomic variant data and longitudinally (median 22.1 months) using only methylation data. At LMT, 69/80 study participants were evaluable (36 recurrent; 33 non-recurrent). Of recurrent study participants, 22/36 had detectable ctDNA (MRD+) at LMT and 29/33 non-recurrent study participants had undetectable ctDNA (MRD-), yielding clinical sensitivity of 61.1% and specificity of 87.9%. Additionally, 74 study participants were evaluable for longitudinal performance with a clinical sensitivity of 83.3% and specificity of 89.5%. Median lead time from first MRD+ result to recurrence was 4.77 months overall, and 5.30 months for study participants with no adjuvant treatment. At 12 weeks post-surgery, MRD status strongly correlated with disease-free survival (DFS) [adj. HR 9.69], outperforming carcinoembryonic antigen (CEA) correlation [HR 2.13]. This tumor-naïve MRD assay demonstrated clinically meaningful performance at LMT and longitudinally, accurately predicting clinical recurrence. MRD status was a stronger prognostic biomarker to DFS compared to standard of care CEA.

Fasciculation potentials are related to the prognosis of amyotrophic lateral sclerosis.

Some prognostic biomarkers of amyotrophic lateral sclerosis (ALS) have been described; however, they are inadequate for satisfactorily predicting individual patient outcomes. Fasciculation potentials (FPs) on electromyography (EMG) are useful for the early diagnosis of ALS, and complex FPs are associated with shorter survival in ALS. In this study, we investigated the relationship between the proportion of muscles with FPs, biochemical markers, and the prognosis of ALS. 89 Patients with ALS were retrospectively classified into three groups based on the interval from onset to death or tracheostomy (less than 1 year: fast progression; from 1 year to less than 3 years: average progression; 3 years or more: slow progression). We performed statistical analysis of the electrophysiological findings, including the percentage of examined muscles with FPs, and biochemical markers evaluated on admission. Patients with fast ALS progression had a higher percentage of muscles with FPs (93.1% vs. 37.9%, P<0.001) and lower uric acid (UA) levels (male: 4.19 mg/dl vs 5.55 mg/dl, P<0.001; female: 3.71 mg/dl vs 5.41 mg/dl, P<0.001) than patients with slow progression. Survival curves demonstrated a relationship between these factors and the survival time in patients with ALS. Furthermore, UA levels were correlated with the percentage of muscles with FPs. Our electrophysiological findings suggest that ALS presents with multisystem neurological manifestations, and these manifestations differed among the groups classified by disease progression. The percentage of muscles with FPs on EMG and serum UA levels were especially associated with the prognosis of ALS.

Cervicovaginal lavages uncover growth factors as key biomarkers for early diagnosis and prognosis of endometrial cancer

Endometrial cancer (EC) rates are continuing to rise and it remains the most common gynecologic cancer in the US. Existing diagnostic methods are invasive and can cause pain and anxiety. Hence, there is a need for less invasive diagnostics for early EC detection. The study objective was to evaluate the utility of growth factors collected through minimally invasive cervicovaginal lavage (CVL) sampling as diagnostic and prognostic biomarkers for EC. CVL samples from 192 individuals undergoing hysterectomy for benign or malignant conditions were collected and used to quantify the concentrations of 19 growth and angiogenic factors using multiplex immunoassays. Patients were categorized based on disease groups: benign conditions (n = 108), endometrial hyperplasia (n = 18), and EC (n = 66). EC group was stratified into grade 1/2 endometrial endometrioid cancer (n = 53) and other EC subtypes (n = 13). Statistical associations were assessed using receiver operating characteristics, Spearman correlations and hierarchical clustering. Growth and angiogenic factors: angiopoietin-2, endoglin, fibroblast activation protein (FAP), melanoma inhibitory activity, and vascular endothelial growth factor-A (VEGF-A) were significantly (p < 0.0001) elevated in EC patients. A multivariate model combining 11 proteins with patient age and body mass index exhibited excellent discriminatory potential (area under curve = 0.918) for EC, with a specificity of 90.7% and a sensitivity of 87.8%. Moreover, angiopoietin-2, FAP and VEGF-A significantly (p < 0.05–0.001) associated with tumor grade, size, myometrial invasion, and mismatch repair status. Our results highlight the innovative use of growth and angiogenic factors collected through CVL sampling for the detecting endometrial cancer, showcasing not only their diagnostic potential but also their prognostic value.

Multi-omics analysis of Prolyl 3-hydroxylase 1 as a prognostic biomarker for immune infiltration in ccRCC

The formation of human collagen requires the presence of Prolyl 3-hydroxylase 1 (P3H1), but the regulatory mechanism of P3H1 remained insufficiently understood. Our study aimed to identify the role of P3H1 in clear cell renal cell carcinoma (ccRCC). P3H1 expression in ccRCC was validated using multiple databases and in vitro experiments. We performed a correlation analysis of P3H1 with drug sensitivity, immune checkpoints, and immune cell infiltration using transcriptome and single-cell sequencing. Drawing upon the Encyclopedia of RNA Interactomes database, we selected P3H1 as the focal point of our investigation, meticulously uncovering the intricate network of microRNAs and lncRNAs that potentially orchestrate ceRNA mechanisms. This study employs a multidimensional approach integrating vitro assays and multi-omics bioinformatics analyses to investigate P3H1’s impact on ccRCC prognosis, immune modulation, immune checkpoints, ceRNA regulatory network, drug sensitivity, and therapeutic responses, aiming to uncover new insights into its therapeutic potential and inform future clinical strategies.

Elevated ITGA3 expression serves as a novel prognostic biomarker and regulates tumor progression in cervical cancer

Patients with advanced and recurrent cervical cancer often lack satisfactory treatment outcomes. Thus, it is necessary to seek reliable biomarkers that provide the ability to identify the disease at an early stage and predict the patient prognosis, providing new strategies for the treatment of cervical cancer. The sequencing data of ITGA3 were retrieved from public datasets. Immune infiltration and sensitivity of potential immunotherapy and chemotherapy have been analyzed between two subgroups. Functional analysis was applied to excavate the related pathways of ITGA3 in cervical cancer. Furthermore, the impact of ITGA3 in tumor progression has been verified in vitro. The results revealed that the level of ITGA3 was upregulated in cervical cancer, and was positively correlated with worse prognosis. The tumor microenvironment of patients in the high-risk group was immunosuppressed. Patients in high-risk group may not benefit from immunotherapy, but be may be sensitive to several chemotherapy drugs. Notably, the angiogenesis, epithelial mesenchymal transition, and PI3K pathway were increased in high-risk group. Collectively, ITGA3 is a marker of poor prognosis and promotes tumor progression by regulating PI3K/AKT pathway in cervical cancer. Our results provide new insights for potential molecular targeted therapy and prognostic prediction of cervical cancer.