Construction of a prognostic model for breast cancer based on moonlighting genes.

Breast cancer (BRCA) is a highly heterogeneous disease, with significant differences in prognosis among patients. Existing biomarkers and prognostic models have limited ability to predict BRCA prognosis. Moonlighting genes regulate tumor progression and are associated with cancer prognosis. This study aimed to construct a moonlighting gene-based prognostic model for BRCA. We obtained differentially expressed genes (DEGs) in BRCA from The Cancer Genome Atlas and intersected them with moonlighting genes from MoonProt to acquire differential moonlighting genes. GO and KEGG results showed main enrichment of these genes in the response of BRCA cells to environmental stimuli and pentose phosphate pathway. Based on moonlighting genes, we conducted drug prediction and validated results through cellular experiments. After ABCB1 knockdown, viability and proliferation of BRCA cells were significantly enhanced. Based on differential moonlighting genes, BRCA was divided into three subgroups, among which cluster2 had the highest survival rate and immunophenoscore and relatively low tumor mutation burden. TP53 had the highest mutation frequency in cluster2 and cluster3, while PIK3CA had a higher mutation frequency in cluster1, with the majority being missense mutations. Subsequently, we established an 11-gene prognostic model in the training set based on DEGs among subgroups using univariate Cox regression, LASSO regression, and multivariable Cox regression analyses. Model prognostic performance was verified in GEO, METABRIC and ICGC validation sets. In summary, this study obtained three BRCA moonlighting gene-related subtypes and constructed an 11-gene prognostic model. The 11-gene BRCA prognostic model has good predictive performance, guiding BRCA prognosis for clinical doctors.

Development of a breast cancer prognostic model based on vesicle-mediated transport-related genes to predict immune landscape and clinical drug therapy.

BACKGROUND: Vesicle-mediated transport, vital for substance exchange and intercellular communication, is linked to tumor initiation and progression. This work was designed to study the role of vesicle-mediated transport-related genes (VMTRGs) in breast cancer (BC)prognosis. METHODS: Univariate Cox analysis was utilized to screen prognosis-related VMTRGs. BC samples underwent unsupervised clustering based on VMTRGs to analyze survival, clinical factors, and immune cell abundance across different subtypes. We constructed a risk model using univariate Cox and LASSO regression analysis, with validation conducted using GEO datasets. Subsequently, we performed tumor mutational burden analysis, and immune landscape analysis on both groups. Ultimately, we conducted immunophenoscore (IPS) scoring to forecast immunotherapy and performed drug sensitivity analysis. RESULTS: We identified 102 VMTRGs associated with BC prognosis. Using these 102 VMTRGs, BC patients were classified into 3 subtypes, with Cluster3 patients showing significantly better survival rates. We constructed a prognostic model for BC based on 12 VMTRGs that effectively predicted patient survival. Riskscore was an independent prognostic factor for BC patients. According to median risk score, high-risk group (HRG) had higher TMB values. The immune landscape of the HRG exhibited characteristics of cold tumor, with higher immune checkpoint expression levels and lower IPS scores, whereas Gemcitabine, Nilotinib, and Oxaliplatin were more suitable for treating low-risk group. CONCLUSION: We classified BC subtypes and built a prognostic model based on VMTRGs. The genes in the prognostic model may serve as potential targets for BC therapy.

The HLA-I landscape confers prognosis and antitumor immunity in breast cancer.

Breast cancer is a highly heterogeneous disease with varied subtypes, prognoses and therapeutic responsiveness. Human leukocyte antigen class I (HLA-I) shapes the immunity and thereby influences the outcome of breast cancer. However, the implications of HLA-I variations in breast cancer remain poorly understood. In this study, we established a multiomics cohort of 1156 Chinese breast cancer patients for HLA-I investigation. We calculated four important HLA-I indicators in each individual, including HLA-I expression level, somatic HLA-I loss of heterozygosity (LOH), HLA-I evolutionary divergence (HED) and peptide-binding promiscuity (Pr). Then, we evaluated their distribution and prognostic significance in breast cancer subtypes. We found that the four breast cancer subtypes had distinct features of HLA-I indicators. Increased expression of HLA-I and LOH were enriched in triple-negative breast cancer (TNBC), while Pr was relatively higher in hot tumors within TNBCs. In particular, a higher Pr indicated a better prognosis in TNBCs by regulating the infiltration of immune cells and the expression of immune molecules. Using the matched genomic and transcriptomic data, we found that mismatch repair deficiency-related mutational signature and pathways were enriched in low-Pr TNBCs, suggesting that targeting mismatch repair deficiency for synthetic lethality might be promising therapy for these patients. In conclusion, we presented an overview of HLA-I indicators in breast cancer and provided hints for precision treatment for low-Pr TNBCs.

Spatiotemporal ATF3 Expression Determines VSMC Fate in Abdominal Aortic Aneurysm.

BACKGROUND: Abdominal aortic aneurysm (AAA) is a catastrophic disease with little effective therapy, likely due to the limited understanding of the mechanisms underlying AAA development and progression. ATF3 (activating transcription factor 3) has been increasingly recognized as a key regulator of cardiovascular diseases. However, the role of ATF3 in AAA development and progression remains elusive. METHODS: Genome-wide RNA sequencing analysis was performed on the aorta isolated from saline or Ang II (angiotensin II)-induced AAA mice, and ATF3 was identified as the potential key gene for AAA development. To examine the role of ATF3 in AAA development, vascular smooth muscle cell-specific ATF3 knockdown or overexpressed mice by recombinant adeno-associated virus serotype 9 vectors carrying ATF3, or shRNA-ATF3 with SM22α (smooth muscle protein 22-α) promoter were used in Ang II-induced AAA mice. In human and murine vascular smooth muscle cells, gain or loss of function experiments were performed to investigate the role of ATF3 in vascular smooth muscle cell proliferation and apoptosis. RESULTS: In both Ang II-induced AAA mice and patients with AAA, the expression of ATF3 was reduced in aneurysm tissues but increased in aortic lesion tissues. The deficiency of ATF3 in vascular smooth muscle cell promoted AAA formation in Ang II-induced AAA mice. PDGFRB (platelet-derived growth factor receptor ß) was identified as the target of ATF3, which mediated vascular smooth muscle cell proliferation in response to TNF-alpha (tumor necrosis factor-α) at the early stage of AAA. ATF3 suppressed the mitochondria-dependent apoptosis at the advanced stage by upregulating its direct target BCL2. Our chromatin immunoprecipitation results also demonstrated that the recruitment of NFκB1 and P300/BAF/H3K27ac complex to the ATF3 promoter induces ATF3 transcription via enhancer activation. NFKB1 inhibitor (andrographolide) inhibits the expression of ATF3 by blocking the recruiters NFKB1 and ATF3-enhancer to the ATF3-promoter region, ultimately leading to AAA development. CONCLUSIONS: Our results demonstrate a previously unrecognized role of ATF3 in AAA development and progression, and ATF3 may serve as a novel therapeutic and prognostic marker for AAA.

High-Throughput Antigen Microarray Identifies Longitudinal Prognostic Autoantibody for Chemoimmunotherapy in Advanced Non-Small Cell Lung Cancer.

Chemoimmunotherapy has evolved as a standard treatment for advanced non-small cell lung cancer (aNSCLC). However, inevitable drug resistance has limited its efficacy, highlighting the urgent need for biomarkers of chemoimmunotherapy. A three-phase strategy to discover, verify, and validate longitudinal predictive autoantibodies (AAbs) for aNSCLC before and after chemoimmunotherapy was employed. A total of 528 plasma samples from 267 aNSCLC patients before and after anti-PD1 immunotherapy were collected, plus 30 independent formalin-fixed paraffin-embedded samples. Candidate AAbs were firstly selected using a HuProt high-density microarray containing 21,000 proteins in the discovery phase, followed by validation using an aNSCLC-focused microarray. Longitudinal predictive AAbs were chosen for ELISA based on responders versus non-responders comparison and progression-free survival (PFS) survival analysis. Prognostic markers were also validated using immunohistochemistry and publicly available immunotherapy datasets. We identified and validated a panel of two AAbs (MAX and DHX29) as pre-treatment biomarkers and another panel of two AAbs (MAX and TAPBP) as on-treatment predictive markers in aNSCLC patients undergoing chemoimmunotherapy. All three AAbs exhibited a positive correlation with early responses and PFS (p < 0.05). The kinetics of MAX AAb showed an increasing trend in responders (p < 0.05) and a tendency to initially increase and then decrease in non-responders (p < 0.05). Importantly, MAX protein and mRNA levels effectively discriminated PFS (p < 0.05) in aNSCLC patients treated with immunotherapy. Our results present a longitudinal analysis of changes in prognostic AAbs in aNSCLC patients undergoing chemoimmunotherapy.

Prognostic Factors for Early Recurrence After Resection of Pancreatic Cancer: A Systematic Review and Meta-Analysis.

BACKGROUND & AIMS: More than half of pancreatic ductal adenocarcinomas (PDACs) recur within 12 months after curative-intent resection. This systematic review and meta-analysis was conducted to identify all reported prognostic factors for early recurrence in resected PDACs. METHODS: After a systematic literature search, a meta-analysis was conducted using a random effects model. Separate analyses were performed for adjusted vs unadjusted effect estimates as well as reported odds ratios (ORs) and hazard ratios (HRs). Risk of bias was assessed using the Quality in Prognostic Studies tool, and evidence was rated according to Grading of Recommendations Assessment, Development and Evaluation recommendations. RESULTS: After 2903 abstracts were screened, 65 studies were included. Of these, 28 studies (43.1%) defined early recurrence as evidence of recurrence within 6 months, whereas 34 (52.3%) defined it as evidence of recurrence within 12 months after surgery. Other definitions were uncommon. Analysis of unadjusted ORs and HRs revealed 41 and 5 prognostic factors for early recurrence within 6 months, respectively. When exclusively considering adjusted data, we identified 25 and 10 prognostic factors based on OR and HR, respectively. Using a 12-month definition, we identified 38 (OR) and 15 (HR) prognostic factors from unadjusted data and 38 (OR) and 30 (HR) prognostic factors from adjusted data, respectively. On the basis of frequency counts of adjusted data, preoperative carbohydrate antigen 19-9, N status, nondelivery of adjuvant therapy, grading, and tumor size based on imaging were identified as key prognostic factors for early recurrence. CONCLUSIONS: Reported prognostic factors of early recurrence vary considerably. Identified key prognostic factors could aid in the development of a risk stratification framework for early recurrence. However, prospective validation is necessary.

An investigation of the molecular characterization of the tripartite motif (TRIM) family and primary validation of TRIM31 in gastric cancer.

Most TRIM family members characterized by the E3-ubiquitin ligases, participate in ubiquitination and tumorigenesis. While there is a dearth of a comprehensive investigation for the entire family in gastric cancer (GC). By combining the TCGA and GEO databases, common TRIM family members (TRIMs) were obtained to investigate gene expression, gene mutations, and clinical prognosis. On the basis of TRIMs, a consensus clustering analysis was conducted, and a risk assessment system and prognostic model were developed. Particularly, TRIM31 with clinical prognostic and diagnostic value was chosen for single-gene bioinformatics analysis, in vitro experimental validation, and immunohistochemical analysis of clinical tissue microarrays. The combined dataset consisted of 66 TRIMs, of which 52 were differentially expressed and 43 were differentially prognostic. Significant survival differences existed between the gene clusters obtained by consensus clustering analysis. Using 4 differentially expressed genes identified by multivariate Cox regression and LASSO regression, a risk scoring system was developed. Higher risk scores were associated with a poorer prognosis, suppressive immune cell infiltration, and drug resistance. Transcriptomic data and clinical sample tissue microarrays confirmed that TRIM31 was highly expressed in GC and associated with a poor prognosis. Pathway enrichment analysis, cell migration and colony formation assay, EdU assay, reactive oxygen species (ROS) assay, and mitochondrial membrane potential assay revealed that TRIM31 may be implicated in cell cycle regulation and oxidative stress-related pathways, contribute to gastric carcinogenesis. This study investigated the whole functional and expression profile and a risk score system based on the TRIM family in GC. Further investigation centered around TRIM31 offers insight into the underlying mechanisms of action exhibited by other members of its family in the context of GC.

Comprehensive pan-cancer analysis of the C2ORF40 expression: Infiltration associations and prognostic implications.

In recent years, C2ORF40 has been identified as a tumor suppressor gene with multiple functions, including roles in cell proliferation, migration, and senescence. To explore the role of the C2ORF40 gene in different tumors, we used multiple databases for analysis. Compared to adjacent normal tissues, C2ORF40 is downregulated in a variety of malignant tumors, including tumors such as breast cancer, colorectal cancer, bladder cancer, hepatocellular carcinoma and prostate cancer. Notably, low expression of the gene is significantly associated with poor overall survival and relapse-free survival rates. In specific cancers including colon cancer and prostate cancer, the expression of C2ORF40 is correlated with the infiltration of CAFs. C2ORF40 is also involved in biological processes such as cell apoptosis and regulation of protein stability. In conclusion, C2ORF40 can hold promise as a prognostic marker for pan-cancer analysis.

Nerve growth factor inducible (VGF) is a secreted mediator for metastatic breast cancer tropism to the brain.

Brain metastases are one of the most serious clinical problems in breast cancer (BC) progression, associated with lower survival rates and a lack of effective therapies. Thus, to dissect the early stages of the brain metastatic process, we studied the impact of brain organotropic BC cells' secretomes on the establishment of the brain pre-metastatic niche (PMN). We found that BC cells with specific tropism to the brain caused significant blood-brain barrier (BBB) disruption, as well as microglial activation, in both in vitro and in vivo models. Further, we searched for a brain-organotropic metastatic signature, as a promising source for the discovery of new biomarkers involved in brain metastatic progression. Of relevance, we identified VGF (nerve growth factor inducible) as a key mediator in this process, also impacting the BBB and microglial functions both in vitro and in vivo. In a series of human breast tumors, VGF was found to be expressed in both cancer cells and the adjacent stroma. Importantly, VGF-positive tumors showed a significantly worse prognosis and were associated with HER2 (human epidermal growth factor receptor 2) overexpression and triple-negative molecular signatures. Further clinical validation in primary tumors from metastatic BC cases showed a significant association between VGF and the brain metastatic location, clearly and significantly impacting on the prognosis of BC patients with brain metastasis. In conclusion, our study reveals a unique secretome signature for BC with a tropism for the brain, highlighting VGF as a crucial mediator in this process. Furthermore, its specific impact as a poor prognostic predictor for BC patients with brain metastasis opens new avenues to target VGF to control the progression of brain metastatic disease. © 2024 The Pathological Society of Great Britain and Ireland.

Management of Refractory/Resistant Herpes Simplex Virus Infections in Haematopoietic Stem Cell Transplantation Recipients: A Literature Review.

Herpes simplex virus (HSV) infections in allogeneic haematopoietic stem cell transplantation (HSCT) recipients pose significant challenges, with higher incidence, severity, and risk of emergence of resistance to antivirals due to impaired T-cell mediated immunity. This literature review focuses on acyclovir-refractory/resistant HSV infections in HSCT recipients. The review addresses the efficacy of antiviral prophylaxis, the incidence of acyclovir-refractory/resistant HSV infections, and the identification of risk factors and potential prognostic impact associated with those infections. Additionally, alternative therapeutic options are discussed. While acyclovir prophylaxis demonstrates a significant benefit in reducing HSV infections in HSCT recipients and, in some cases, overall mortality, concerns arise about the emergence of drug-resistant HSV strains. Our systematic review reports a median incidence of acyclovir-resistant HSV infections of 16.1%, with an increasing trend in recent years. Despite limitations in available studies, potential risk factors of emergence of HSV resistance to acyclovir include human leucocyte antigen (HLA) mismatches, myeloid neoplasms and acute leukaemias, and graft-versus-host disease (GVHD). Limited evidences suggest a potentially poorer prognosis for allogeneic HSCT recipients with acyclovir-refractory/resistant HSV infection. Alternative therapeutic approaches, such as foscarnet, cidofovir, topical cidofovir, optimised acyclovir dosing, and helicase-primase inhibitors offer promising options but require further investigations. Overall, larger studies are needed to refine preventive and therapeutic strategies for acyclovir-refractory/resistant HSV infections in allogeneic HSCT recipients and to identify those at higher risk.

Circulating tumour cells predict recurrences and survival in head and neck squamous cell carcinoma patients.

Patients with head and neck squamous cell carcinoma (HNSCC) are at a high risk of developing recurrence and secondary cancers. This study evaluates the prognostic and surveillance utilities of circulating tumour cells (CTCs) in HNSCC. A total of 154 HNSCC patients were recruited and followed up for 4.5 years. Blood samples were collected at baseline and follow-up. CTCs were isolated using a spiral microfluid device. Recurrence and death due to cancer were assessed during the follow-up period. In patients with HNSCC, the presence of CTCs at baseline was a predictor of recurrence (OR = 8.40, p < 0.0001) and death (OR= ∞, p < 0.0001). Patients with CTCs at baseline had poor survival outcomes (p < 0.0001). Additionally, our study found that patients with CTCs in a follow-up appointment were 2.5 times more likely to experience recurrence or death from HNSCC (p < 0.05) prior to their next clinical visit. Our study highlights the prognostic and monitoring utilities of CTCs' in HNSCC patients. Early identification of CTCs facilitates precise risk assessment, guiding treatment choices and ultimately enhancing patient outcomes.

Identification of prognostic biomarkers for cholangiocarcinoma by combined analysis of molecular characteristics of clinical MVI subtypes and molecular subtypes.

Cholangiocarcinoma (CCA) is widely noted for its high degree of malignancy, rapid progression, and limited therapeutic options. This study was carried out on transcriptome data of 417 CCA samples from different anatomical locations. The effects of lipid metabolism related genes and immune related genes as CCA classifiers were compared. Key genes were derived from MVI subtypes and better molecular subtypes. Pathways such as epithelial mesenchymal transition (EMT) and cell cycle were significantly activated in MVI-positive group. CCA patients were classified into three (four) subtypes based on lipid metabolism (immune) related genes, with better prognosis observed in lipid metabolism-C1, immune-C2, and immune-C4. IPTW analysis found that the prognosis of lipid metabolism-C1 was significantly better than that of lipid metabolism-C2 + C3 before and after correction. KRT16 was finally selected as the key gene. And knockdown of KRT16 inhibited proliferation, migration and invasion of CCA cells.

EPHB2 as a key mediator of glioma progression: Insights from microenvironmental receptor ligand-related prognostic gene signature.

Malignant gliomas, characterized by pronounced heterogeneity, a complex microenvironment, and a propensity for relapse and drug resistaniguree, pose significant challenges in oncology. This study aimed to investigate the prognostic value of Ligand and Receptor related genes (LRRGs) within the glioma microenvironment. An intersection of 71 ligand-related genes (LRGs) and 2628 receptor-related genes (RRGs) yielded a total of 69 LRRGs. Utilizing the least absolute shrinkage and selection operator (LASSO) regression analysis, a prognostic RiskScore model comprising 28 LRRGs was constructed. The model demonstrated robust prognostic value, further validated in the TCGA-GBMLGG dataset. Subsequent analyses included differential gene expression, Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), gene set enrichment (GSEA), and gene set variation (GSVA) within RiskScore groups. Additionally, evaluations of PPI, mRNA-RBP, mRNA-TF, and mRNA-drug interaction networks were conducted. Four hub genes were identified through differential expression analysis of the 28 LRRGs across various GSE datasets. A multivariate Cox prognostic model was constructed for nomogram analysis, gene mutation analysis, and related expression distribution. This study underscores the role of LRRGs in intercellular communication within the glioma microenvironment and identifies four hub genes crucial for prognostic assessment in clinical glioma patients. These findings offer a potential evaluation framework for glioma patients, enhancing our understanding of the disease and informing future therapeutic strategies.

Role of autophagy-related genes in liver cancer prognosis.

Autophagy, a highly conserved process of protein and organelle degradation, has emerged as a critical regulator in various diseases, including cancer progression. In the context of liver cancer, the predictive value of autophagy-related genes remains ambiguous. Leveraging chip datasets from the TCGA and GTEx databases, we identified 23 differentially expressed autophagy-related genes in liver cancer. Notably, five key autophagy genes, PRKAA2, BIRC5, MAPT, IGF1, and SPNS1, were highlighted as potential prognostic markers, with MAPT showing significant overexpression in clinical samples. In vitro cellular assays further demonstrated that MAPT promotes liver cancer cell proliferation, migration, and invasion by inhibiting autophagy and suppressing apoptosis. Subsequent in vivo studies further corroborated the pro-tumorigenic role of MAPT by suppressing autophagy. Collectively, our model based on the five key genes provides a promising tool for predicting liver cancer prognosis, with MAPT emerging as a pivotal factor in tumor progression through autophagy modulation.

Blood eosinophils and fractional exhaled nitric oxide are prognostic and predictive biomarkers in childhood asthma.

BACKGROUND: Blood eosinophils and fractional exhaled nitric oxide (Feno) are prognostic biomarkers for exacerbations and predict lung function responses to dupilumab in adolescents and adults with asthma. OBJECTIVE: We evaluated the relationship between baseline blood eosinophils and Feno and response to dupilumab in children with asthma. METHODS: Children aged 6 to 11 years with uncontrolled moderate-to-severe asthma (n = 408) were randomized to receive dupilumab 100/200 mg by body weight or volume-matched placebo every 2 weeks for 52 weeks. Annualized exacerbation rate (AER) reduction and least squares mean change in prebronchodilator percent predicted forced expiratory volume in 1 second (ppFEV1) at week 12 were assessed according to cutoff baseline levels for Feno (<20 ppb vs ≥20 ppb) and blood eosinophil count (<150, ≥150 to <300, ≥300 to <500, and ≥500 cells/µL). Quadrant analyses in populations defined by biomarker thresholds and spline models across continuous end points assessed the relationship with Feno and eosinophil count. Interaction testing evaluated the independent roles of Feno and blood eosinophils as predictive markers. RESULTS: Exacerbation risk and magnitude of AER reduction increased in subgroups with higher baseline biomarker levels. Quadrant analyses revealed that disease of patients with either elevated Feno or eosinophil counts demonstrated a clinical response to dupilumab. Interaction testing indicated blood eosinophil counts or Feno independently added value as predictive biomarkers. CONCLUSIONS: In children with uncontrolled moderate-to-severe asthma, blood eosinophil counts and Feno are clinically relevant biomarkers to identify those at risk for asthma exacerbations, as well as those with disease with clinical response to dupilumab. TRIAL REGISTRATION: Liberty Asthma VOYAGE ClinicalTrials.gov NCT02948959.

Transcriptomic signatures of progression to TB disease among close contacts in Brazil.

BACKGROUND: Approximately 5% of people infected with Mycobacterium tuberculosis progress to tuberculosis (TB) disease without preventive therapy. There is a need for a prognostic test to identify those at highest risk of incident TB, so that therapy can be targeted. We evaluated host blood transcriptomic signatures for progression to TB disease. METHODS: Close contacts (≥4 hours exposure per week) of adult patients with culture-confirmed pulmonary TB were enrolled in Brazil. Investigation for incident, microbiologically-confirmed or clinically-diagnosed pulmonary or extra-pulmonary TB disease through 24 months of follow-up was symptom-triggered. Twenty previously validated blood TB transcriptomic signatures were measured at baseline by real-time quantitative PCR. Prognostic performance for incident TB was tested using receiver operating characteristic curve (ROC) analysis at 6, 9, 12, and 24 months of follow-up. RESULTS: Between June 2015 and June 2019, 1,854 close contacts were enrolled; Twenty-five progressed to incident TB, of whom 13 had microbiologically-confirmed disease. Baseline transcriptomic signature scores were measured in 1,789 close contacts. Prognostic performance for all signatures was best within 6 months of diagnosis. Seven signatures (Gliddon4, Suliman4, Roe3, Roe1, Penn-Nicholson6, Francisco2, and Rajan5) met the minimum World Health Organization target product profile (TPP) for a prognostic test through 6 months; three (Gliddon4, Rajan5, and Duffy9) through 9 months. None met the TPP threshold through 12 or more months of follow-up. CONCLUSIONS: Blood transcriptomic signatures may be useful for predicting TB risk within 9 months of measurement among TB-exposed contacts, to target preventive therapy administration.

Identification of CCL20 as a prognostic predictor for severe fever with thrombocytopenia syndrome based on plasma proteomics.

BACKGROUND: Severe fever with thrombocytopenia syndrome (SFTS), a lethal tick-borne hemorrhagic fever, prompted our investigation into prognostic predictors and potential drug targets using plasma Olink Proteomics. METHODS: Employing the Olink assay, we analyzed 184 plasma proteins in 30 survivors and 8 non-survivors of SFTS. Validation was performed in a cohort of 154 SFTS patients using enzyme-linked immunosorbent assay. We utilized the Drug Gene Interaction database to identify protein-drug interactions. RESULTS: Non-survivors exhibited 110 differentially expressed proteins (DEPs) compared to survivors, with functional enrichment in the cell chemotaxis-related pathway. Thirteen DEPs, including C-C motif chemokine 20 (CCL20), calcitonin gene-related peptide alpha and Pleiotrophin, were associated with multiple organ dysfunction syndrome. CCL20 emerged as the top predictor of death, demonstrating an area under the curve of 1 (P = .0004) and 0.9033 (P < .0001) in the discovery and validation cohort, respectively. Patients with CCL20 levels exceeding 45.74 pg/mL exhibited a fatality rate of 45.65%, while no deaths occurred in those with lower CCL20 levels. Furthermore, we identified 202 FDA-approved drugs targeting 37 death-related plasma proteins. CONCLUSIONS: Distinct plasma proteomic profiles characterize SFTS patients with different outcomes, with CCL20 emerging as a novel, sensitive, accurate, and specific biomarker for predicting SFTS prognosis.

Crossing the Halfway Point: Aptamer-Based, Highly Multiplexed Assay for the Assessment of the Proteome.

Measuring responses in the proteome to various perturbations improves our understanding of biological systems. The value of information gained from such studies is directly proportional to the number of proteins measured. To overcome technical challenges associated with highly multiplexed measurements, we developed an affinity reagent-based method that uses aptamers with protein-like side chains along with an assay that takes advantage of their unique properties. As hybrid affinity reagents, modified aptamers are fully comparable to antibodies in terms of binding characteristics toward proteins, including epitope size, shape complementarity, affinity and specificity. Our assay combines these intrinsic binding properties with serial kinetic proofreading steps to allow highly effective partitioning of stable specific complexes from unstable nonspecific complexes. The use of these orthogonal methods to enhance specificity effectively overcomes the severe limitation to multiplexing inherent to the use of sandwich-based methods. Our assay currently measures half of the unique proteins encoded in the human genome with femtomolar sensitivity, broad dynamic range and exceptionally high reproducibility. Using machine learning to identify patterns of change, we have developed tests based on measurement of multiple proteins predictive of current health states and future disease risk to guide a holistic approach to precision medicine.

Circulating metabolomic markers linking diabetic kidney disease and incident cardiovascular disease in type 2 diabetes: analyses from the Hong Kong Diabetes Biobank.

AIMS/HYPOTHESIS: The aim of this study was to describe the metabolome in diabetic kidney disease (DKD) and its association with incident CVD in type 2 diabetes, and identify prognostic biomarkers. METHODS: From a prospective cohort of individuals with type 2 diabetes, baseline sera (N=1991) were quantified for 170 metabolites using NMR spectroscopy with median 5.2 years of follow-up. Associations of chronic kidney disease (CKD, eGFR<60 ml/min per 1.73 m2) or severely increased albuminuria with each metabolite were examined using linear regression, adjusted for confounders and multiplicity. Associations between DKD (CKD or severely increased albuminuria)-related metabolites and incident CVD were examined using Cox regressions. Metabolomic biomarkers were identified and assessed for CVD prediction and replicated in two independent cohorts. RESULTS: At false discovery rate (FDR)<0.05, 156 metabolites were associated with DKD (151 for CKD and 128 for severely increased albuminuria), including apolipoprotein B-containing lipoproteins, HDL, fatty acids, phenylalanine, tyrosine, albumin and glycoprotein acetyls. Over 5.2 years of follow-up, 75 metabolites were associated with incident CVD at FDR<0.05. A model comprising age, sex and three metabolites (albumin, triglycerides in large HDL and phospholipids in small LDL) performed comparably to conventional risk factors (C statistic 0.765 vs 0.762, p=0.893) and adding the three metabolites further improved CVD prediction (C statistic from 0.762 to 0.797, p=0.014) and improved discrimination and reclassification. The 3-metabolite score was validated in independent Chinese and Dutch cohorts. CONCLUSIONS/INTERPRETATION: Altered metabolomic signatures in DKD are associated with incident CVD and improve CVD risk stratification.

Hypoxia-related THBD+ macrophages as a prognostic factor in glioma: Construction of a powerful risk model.

Glioma is a prevalent malignant tumour characterized by hypoxia as a pivotal factor in its progression. This study aims to investigate the impact of the most severely hypoxic cell subpopulation in glioma. Our findings reveal that the THBD+ macrophage subpopulation is closely associated with hypoxia in glioma, exhibiting significantly higher infiltration in tumours compared to non-tumour tissues. Moreover, a high proportion of THBD+ cells correlates with poor prognosis in glioblastoma (GBM) patients. Notably, THBD+ macrophages exhibit hypoxic characteristics and epithelial-mesenchymal transition features. Silencing THBD expression leads to a notable reduction in the proliferation and metastasis of glioma cells. Furthermore, we developed a THBD+ macrophage-related risk signature (THBDMRS) through machine learning techniques. THBDMRS emerges as an independent prognostic factor for GBM patients with a substantial prognostic impact. By comparing THBDMRS with 119 established prognostic features, we demonstrate the superior prognostic performance of THBDMRS. Additionally, THBDMRS is associated with glioma metastasis and extracellular matrix remodelling. In conclusion, hypoxia-related THBD+ macrophages play a pivotal role in glioma pathogenesis, and THBDMRS emerges as a potent and promising prognostic tool for GBM, contributing to enhanced patient survival outcomes.