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PubMed2006

Different immunoaffinity fractionation strategies to characterize the human plasma proteome.

Plasma proteins may often serve as indicators of disease and are a rich source for biomarker discovery. However, the intrinsic large dynamic range of plasma proteins makes the analysis very challenging because a large number of low abundance proteins are often masked by a few high abundance proteins. The use of prefractionation methods, such as depletion of higher abundance proteins before protein profiling, can assist in the discovery and detection of less abundant proteins that may ultimately prove to be informative biomarkers. But there are few studies on comprehensive investigation of the proteins both in the fractions depleted and remainder. In the present study, two different immunoaffinity fractionation columns for the top-6 or the top-12 proteins in plasma were investigated and both the proteins in column-bound and flow-through fractions were subsequently analyzed. A two-dimensional peptide separation strategy, utilizing chromatographic separation techniques, combined with tandem mass spectrometry (MS/MS) was employed for proteomic analysis of the four fractions. Using the established HUPO PPP criteria, a total of 2401 unique plasma proteins were identified. The Multiple Affinity Removal System yielded 921 and 725 unique proteins from the flow-through and bound fractions, respectively, whereas the Seppro MIXED 12 column yielded identification of 897 and 730 unique proteins from the flow-through and bound fractions, respectively. When more stringent criteria, based on searching against the reversed database, were implemented, 529 unique proteins were identified from the four fractions with the confidence in peptide identification increased from 73.6% to 99%. To determine whether the presence of nontarget proteins in the immunoaffinity-bound fraction could be attributed to their interaction with high abundance proteins, co-immunoprecipitation analysis with an antibody to human plasma albumin was performed, which resulted in an identification of 40 unique proteins from the coimmunoprecipitate with the more stringent criteria. This study illustrated that combining the column-bound and flow-through fractions from immunoaffinity separation affords more extensive profiling of the protein content of human plasma. The presence of nontarget proteins in the column-bound fractions may be induced by their binding to the higher abundance proteins targeted by the immunoaffinity column.

Amino Acid Sequence↗

PubMed2006

Transcriptome profile of macrophages from atherosclerosis-sensitive and atherosclerosis-resistant mice.

We performed a strain intercross between two apoE-deficient mouse strains with a large difference in lesion susceptibility and measured aortic root lesion area in 98 female F(2) progeny. Total RNA was prepared from bone marrow-derived macrophages, and RNA from the five mice with the smallest and largest lesions were used for microarray gene expression profiling. Remarkably, approximately 5% of the 12,288 expressed transcripts were differentially expressed in the atherosclerosis-susceptible and atherosclerosis-resistant bone marrow-derived macrophages (unadjusted p < 0.05), thus defining the transcriptome of macrophages associated with atherosclerosis susceptibility. Using more stringent criteria of twofold or greater change and p < 0.01, 116 and 70 transcripts were overexpressed in lesion-prone and lesion-resistant bone marrow-derived macrophages, respectively. Transcription factor binding site analysis identified two promoter elements that were found more often in the genes overexpressed in the large-lesion group, and one promoter element that was found more often in the small-lesion group. The combination of this expression profiling data with the genetic method of quantitative trait locus mapping should give powerful insights into the genes that affect atherosclerosis susceptibility in mice.

Alternative Splicing↗

PubMed2003

PCA disjoint models for multiclass cancer analysis using gene expression data.

MOTIVATION: Microarray expression profiling appears particularly promising for a deeper understanding of cancer biology and to identify molecular signatures supporting the histological classification schemes of neoplastic specimens. However, molecular diagnostics based on microarray data presents major challenges due to the overwhelming number of variables and the complex, multiclass nature of tumor samples. Thus, the development of marker selection methods, that allow the identification of those genes that are most likely to confer high classification accuracy of multiple tumor types, and of multiclass classification schemes is of paramount importance. RESULTS: A computational procedure for marker identification and for classification of multiclass gene expression data through the application of disjoint principal component models is described. The identified features represent a rational and dimensionally reduced base for understanding the basic biology of diseases, defining targets for therapeutic intervention, and developing diagnostic tools for the identification and classification of multiple pathological states. The method has been tested on different microarray data sets obtained from various human tumor samples. The results demonstrate that this procedure allows the identification of specific phenotype markers and can classify previously unseen instances in the presence of multiple classes.

Acute Disease↗

PubMed2006

Clusterin expression in primary and metastatic melanoma.

Clusterin is a pleiotrophic glycoprotein that has been implicated in diverse physiologic processes. Recent studies of gene expression profiling found clusterin to be expressed in desmoplastic variants of malignant melanoma. In this study, we extended those observations and examined clusterin expression in a larger number of primary as well as in metastatic melanomas and melanocytic nevi. We used tissue microarray panels as well as selected conventional sections from formalin-fixed and paraffin-embedded tissue blocks. Positive staining for clusterin was found in seven of 21 (30%) primary desmoplastic and three of 21 (7%) non-desmoplastic melanoma. Among metastatic tumors, clusterin expression was found in five of 37 tumors (13.5%). Clusterin expression was not seen in melanocytes of normal skin or in any of the 10 melanocytic nevi tested. Clusterin expression was not entirely restricted to melanoma; it was also seen in a few non-neoplastic tissues, including perifollicular fibroblasts, occasional sebocytes, and the epithelial cells lining sebaceous duct and the isthmus of the hair follicle. Our findings confirm the observation that clusterin can be expressed in melanoma, in particular primary desmoplastic melanoma. However, clusterin appears to be present only in a minority of melanomas.

Biomarkers, Tumor↗

PubMed2004

Analysis of gene expression in cancer cell lines identifies candidate markers for pancreatic tumorigenesis and metastasis.

Pancreatic cancer is a highly aggressive type of malignancy and the prognosis for disease presenting typically at a late stage is extremely poor. A comprehensive understanding of its molecular genetics is required in order to develop new approaches to clinical management. To date, serial analysis of gene expression and more recently oligo/cDNA microarray technologies have been employed in order to identify genes involved in pancreatic neoplasia that can be developed as diagnostic markers and drug targets for this dismal disease. This study describes the expression profile obtained from 20 pancreatic cell lines using cDNA microarrays containing 9,932 human gene elements. Numerous genes were identified as being differentially expressed, some of which have been previously implicated in pancreatic adenocarcinoma (S100P, S100A4, prostate stem cell antigen, lipocalin 2, claudins 3 and 4, trefoil factors 1 and 2) as well as several novel genes. The differentially expressed genes identified are involved in a variety of cellular functions, including control of transcription, regulation of the cell cycle, proteolysis, cell adhesion and signaling. Validation of our array results was performed by exploring the SAGEmap database and by immunohistochemistry for a selection of 4 genes that have not previously been studied in pancreatic cancer: anterior gradient 2 homologue (Xenopus laevis), insulin-like growth factor binding protein 3 and 4 and Forkhead box J1. Immunostaining was performed using pancreas-specific tissue microarrays containing core biopsies from 305 clinical specimens. In addition, using statistical group comparison and hierarchical clustering, a selection of genes was identified that may be linked to the site of metastasis from which these cell lines were isolated.

Biomarkers, Tumor↗

PubMed2005

Metastatic transcriptional pattern revealed by gene expression profiling in primary colorectal carcinoma.

Metastatic spread to the liver is the major contributor to mortality in patients with colorectal carcinoma (CRC). In order to seek for gene expression patterns associated with metastatic potential in primary CRC, we compared the transcriptional profiles of 10 radically resected primary CRCs from patients who did not develop distant metastases within a 5-year follow-up period with those of 10 primary/metastatic tumor pairs from patients with synchronous liver metastases. To focus selectively on neoplastic cells, the study was conducted on laser-microdissected bioptic tissues. Arrays of 7,864 human cDNAs were utilized. While a striking transcriptional similarity was observed between the primary tumors and their distant metastases, the nonmetastasizing primary tumors were clearly distinct from the primary/metastatic tumor pairs. Of 37 gene expression differences found between the 2 groups of primary tumors, 29 also distinguished nonmetastasizing tumors from metastases. The gene encoding for mannosyl (alpha-1,3-)-glycoprotein beta-1,4-N-acetyl-glucosaminyl-transferase (GnT-IV) became significantly upregulated in primary/metastatic tumor pairs (p < 0.001). GnT-IV upregulation was confirmed by RT-PCR. These data support the existence of a specific transcriptional signature distinguishing primary colon adenocarcinomas with different metastatic potential, the further pursuit of which may lead to relevant clinical and therapeutic applications.

Adenocarcinoma↗

PubMed2001

Carcinogenic effects of polychlorinated biphenyls.

As part of its mandate, the Agency for Toxic Substances and Disease Registry (ATSDR) prepares toxicological profiles on hazardous chemicals found at Comprehensive Environmental Response, Compensation, and Liability Act (CERCLA) National Priorities List (NPL) sites that have the greatest public health impact. These profiles comprehensively summarize toxicological and environmental information. This article constitutes the release of an important section of the Toxicological profile for polychlorinated biphenyls [ATSDR. 2000: Toxicological profile for polychlorinated biphenyls. Atlanta, GA: US Department of Health and Human Services, Agency for Toxic Substances and Disease Registry.] into the scientific literature. This article focuses on the carcinogenic effects of this group of synthetic organic chemicals (polychlorinated biphenyls) in humans and animals. Information on other health effects, toxicokinetics, mechanisms of toxicity, biomarkers, interactions, chemical and physical properties, potential for human exposure, and regulations and advisories is detailed in the profile.

Animals↗

PubMed2004

Search for new biomarkers of gastric cancer through serial analysis of gene expression and its clinical implications.

Gastric cancer is one of the most common human cancers and is the second most frequent cause of cancer-related death in the world. Serial analysis of gene expression (SAGE) is a powerful technique to allow genome-wide analysis of gene expression in a quantitative manner without prior knowledge of the gene sequences. SAGE on 5 samples of gastric cancer with different histology and clinical stages have created large SAGE libraries of gastric cancer that enable us to identify new cancer biomarkers. Commonly up-regulated genes in gastric cancer in comparison with normal gastric epithelia included CEACAM6, APOC1 and YF13H12. By comparing gene expression profiles of gastric cancers at early and advanced stages, several genes differentially expressed by tumor stage were also identified, including FUS, CDH17, COL1A1 and COL1A2, which should be novel genetic markers for high-grade malignancy. Regenerating gene type IV (REGIV) is one of the most up-regulated genes in a SAGE library of a scirrhous-type gastric cancer. In vitro studies using RegIV-transfected cells revealed that RegIV is secreted by cancer cells and inhibits apoptosis, suggesting that RegIV may serve as a novel biomarker and therapeutic target for gastric cancer. Production of RNA aptamers could be a useful approach to establish a detection system in blood. A custom-made array, named Ex-STOMACHIP, consisting of 395 genes, including highly differentially expressed genes identified by our SAGE and other known genes related to carcinogenesis and chemosensitivity, is useful to study the molecular pathogenesis of gastric cancer and to obtain information about biological behavior and sensitivity to therapy in the clinical setting. Combined analyses of gene expression profile, genetic polymorphism and genetic instability will aid not only cancer detection, but also characterization of individual cancers and patients, leading to personalized medicine and cancer prevention.

Biomarkers, Tumor↗

PubMed2026

Early Transcriptional Changes in Neutrophil-Mediated Processes Following Recanalization After Ischemic Stroke.

BACKGROUND: Ischemic stroke is a leading cause of death and long-term disability worldwide. Recanalization therapies, including thrombolysis and mechanical thrombectomy, restore blood flow, yet many patients experience poor outcomes, a phenomenon known as futile recanalization. Given the short therapeutic window for ischemic stroke, identifying early biomarkers to guide targeted interventions and improve outcomes is critical. METHODS: Using a murine middle cerebral occlusion model that mimics a large vessel occlusion with recanalization, a comprehensive microarray analysis from blood samples collected immediately and 3 hours after recanalization (N=44) was performed. Differentially expressed genes, enrichment pathways, immune cell proportions, enriched cell markers, predicted micro-RNAs, and transcription factors were identified using RStudio. Findings in mice were validated with rat middle cerebral artery occlusion (GSE21136) and patients with stroke (GSE16561) data sets to confirm transcriptional changes in peripheral blood postrecanalization. RESULTS: Il1r2, Cd55, Mmp8, Cd14, and Cd69 were early biomarkers poststroke and postrecanalization. Cross-validation revealed Vcan as a differentially expressed gene conserved across species, making it a novel ischemic marker detected as early as 3 hours postrecanalization (4 hours after middle cerebral artery occlusion) in mice, 24 hours after recanalization in rats (middle cerebral artery occlusion-thrombectomy), and within 24 hours from onset in humans receiving recombinant tissue plasminogen activator-thrombolysis. CIBERSORTx and ImmuCellAI-mouse deconvolution showed neutrophil elevation postrecanalization. Leukocyte and neutrophil activation pathways were enriched early after stroke in mice and humans, with stronger upregulation in the female sex. Several regulatory micro-RNAs were identified, and Nuclear Factor Erythroid 4 (NFE4) and Metal Regulatory Transcription Factor 1 (MTF1) emerged as key transcription factors. A coregulatory network underlying neutrophil activity was constructed, highlighting its central role in early responses to ischemia and recanalization, which was enriched in the female sex. CONCLUSIONS: We identified novel early genomic markers for ischemia and recanalization, including the conserved marker Vcan, and highlighted age- and sex-specific immune responses. Mapping a neutrophil-centered coregulatory network provides mechanistic insight into futile recanalization and supports the development of targeted therapies to improve clinical outcomes.

Animals↗

PubMed2004

Expression profiling using tissue microarray in 211 malignant fibrous histiocytomas confirms the prognostic value of Ki-67.

The tissue microarray technology is a high-throughput technique that allows studies of multiple markers in large tumor materials. We performed immunohistochemical profiling using tissue microarray and immunostaining for Ki-67, p53, bcl-2, CD44, cyclin A and Pgp in a series of 211 malignant fibrous histiocytomas (MFHs) with correlation to prognosis. Tissue from 50 local recurrences and 20 metastases was available for comparison with the primary tumors. In univariate analysis, Ki-67 was the only immunohistochemical marker significantly correlated with metastasis with a hazard ratio of 1.9. Multivariate analysis, with tumor size, depth, necrosis, vascular invasion, mitotic rate and Ki-67 expression, revealed an independent prognostic value of tumor size and Ki-67. Local recurrences did not differ from the corresponding primary tumors, whereas metastases showed a trend for upregulation of cyclin A and Pgp. In this large series of MFHs, a tumor size greater than 8 cm and a Ki-67 index of more than 20% were strong and independent prognostic factors for metastasis. In contrast, p53, bcl-2, CD44, cyclin A and Pgp, which have previously been suggested as prognostic factors in soft tissue sarcomas, did not show such correlations. Hence, we suggest that proliferation, as measured by Ki-67 index, should be considered as a prognostic marker in clinical management of pleomorphic soft tissue sarcomas.

Adult↗

PubMed2001

Analysis of gene expression profiles in normal and neoplastic ovarian tissue samples identifies candidate molecular markers of epithelial ovarian cancer.

Epithelial ovarian cancer is the leading cause of death from gynecologic cancer, in part because of the lack of effective early detection methods. Although alterations of several genes, such as c-erb-B2, c-myc, and p53, have been identified in a significant fraction of ovarian cancers, none of these mutations are diagnostic of malignancy or predictive of tumor behavior over time. Here, we used oligonucleotide microarrays with probe sets complementary to >6,000 human genes to identify genes whose expression correlated with epithelial ovarian cancer. We extended current microarray technology by simultaneously hybridizing ovarian RNA samples in a highly parallel manner to a single glass wafer containing 49 individual oligonucleotide arrays separated by gaskets within a custom-built chamber (termed "array-of-arrays"). Hierarchical clustering of the expression data revealed distinct groups of samples. Normal tissues were readily distinguished from tumor tissues, and tumors could be further subdivided into major groupings that correlated both to histological and clinical observations, as well as cell type-specific gene expression. A metric was devised to identify genes whose expression could be considered ideal for molecular determination of epithelial ovarian malignancies. The list of genes generated by this method was highly enriched for known markers of several epithelial malignancies, including ovarian cancer. This study demonstrates the rapidity with which large amounts of expression data can be generated. The results highlight important molecular features of human ovarian cancer and identify new genes as candidate molecular markers.

Adenocarcinoma, Papillary↗

PubMed2005

Expression profiling reveals differences in metabolic gene expression between exercise-induced cardiac effects and maladaptive cardiac hypertrophy.

While cardiac hypertrophy elicited by pathological stimuli eventually leads to cardiac dysfunction, exercise-induced hypertrophy does not. This suggests that a beneficial hypertrophic phenotype exists. In search of an underlying molecular substrate we used microarray technology to identify cardiac gene expression in response to exercise. Rats exercised for seven weeks on a treadmill were characterized by invasive blood pressure measurements and echocardiography. RNA was isolated from the left ventricle and analysed on DNA microarrays containing 8740 genes. Selected genes were analysed by quantitative PCR. The exercise program resulted in cardiac hypertrophy without impaired cardiac function. Principal component analysis identified an exercise-induced change in gene expression that was distinct from the program observed in maladaptive hypertrophy. Statistical analysis identified 267 upregulated genes and 62 downregulated genes in response to exercise. Expression changes in genes encoding extracellular matrix proteins, cytoskeletal elements, signalling factors and ribosomal proteins mimicked changes previously described in maladaptive hypertrophy. Our most striking observation was that expression changes of genes involved in beta-oxidation of fatty acids and glucose metabolism differentiate adaptive from maladaptive hypertrophy. Direct comparison to maladaptive hypertrophy was enabled by quantitative PCR of key metabolic enzymes including uncoupling protein 2 (UCP2) and fatty acid translocase (CD36). DNA microarray analysis of gene expression changes in exercise-induced cardiac hypertrophy suggests that a set of genes involved in fatty acid and glucose metabolism could be fundamental to the beneficial phenotype of exercise-induced hypertrophy, as these changes are absent or reversed in maladaptive hypertrophy.

Animals↗

PubMed2006

Outcome-based profiling of astrocytic tumours identifies prognostic gene expression signatures which link molecular and morphology-based pathology.

Astrocytomas are intracranial malignancies for which invasive growth and high motility of tumour cells preclude total resection; the tumours usually recur in a more aggressive and, eventually, lethal form. Clinical outcome is highly variable and the accuracy of morphology-based prognostic statements is limited. In order to identify novel molecular markers for prognosis we obtained expression profiles of: i) tumours associated with particularly long recurrence-free intervals, ii) tumours which led to rapid patient death, and iii) tumour-free control brain. Unsupervised data analysis completely separated the three sample entities indicating a strong impact of the selection criteria on general gene expression. Consequently, significant numbers of specifically expressed genes could be identified for each entity. An extended set of tumours was then investigated by RT-PCR targeting 12 selected genes. Data from these experiments were summarised into a sample-specific index which assigns tumours to high- and low-risk groups as successfully as does morphology-based grading. Moreover, this index directly correlates with definite survival suggesting that integrated gene expression data allow individualised prognostic statements. We also analysed localisation of selected marker transcripts by in situ hybridization. Our finding of cell-specificity for some of these outcome-determining genes relates global expression data to the presence of morphological correlates of tumour behaviour and, thus, provides a link between morphology-based and molecular pathology. Our identification of expression signatures that are associated individually with clinical outcome confirms the prognostic relevance of gene expression data and, thus, represents a step towards eventually implementing molecular diagnosis into clinical practice in neuro-oncology.

Adolescent↗

PubMed2006

Molecular characterization of adenocarcinoma and squamous carcinoma of the uterine cervix using microarray analysis of gene expression.

In an attempt to understand the molecular mechanisms for the different clinical features between adenocarcinoma/adenosquamous carcinoma (AC/ASC) and squamous carcinoma (SC) of the uterine cervix, we analyzed gene expression profiles of different histological subtypes of cervical cancer. Cancer specimens and the surrounding normal tissue counterparts were separately collected from cervical cancer patients undergoing type III radical hysterectomy. Paired total RNA (cancer and normal tissues) was isolated and analyzed with cDNA microarrays containing duplicate spots of 7 334 sequence-verified human cDNA clones. Selected differentially expressed genes specific for AC or SC were further verified using real-time quantitative polymerase chain reaction (RTQ-PCR) and immunohistochemistry. Genes, including CEACAM5, TACSTD1, S100P and MSLN were upregulated in AC. Contrarily, genes involved in epidermal differentiation complex such as S100A9 and ANXA8 were upregulated in SC. Cross-validation of the results using an independent but comparable group of patients with known long-term outcomes (n = 63, median follow-up 70.3 months; range, 4-208 months) showed that the correlation between the selected 6 differentially expressed genes and histology was highly significant. CEACAM5 (p < 0.0001) and TACSTD1 (p = 0.009) were significant prognostic factors by multivariate Cox proportional hazards regression analysis. The combination of cDNA microarray, RTQ-PCR and immunohistochemical results of this study showed that it is possible to define different gene profiles for AC and SC. Moreover, TACSTD1 expression may be a novel poor prognostic factor.

Adenocarcinoma↗

PubMed2005

The future of breast cancer: the role of prognostic factors.

There remains a number of unmet clinical needs in patients with breast cancer that research and development aims to address. More sensitive and specific indicators of prognosis are required to identify those patients at greatest risk for disease progression. A number of biological markers including the cyclins, circulating epithelial cells, and components of the urokinase plasminogen system have been shown to correlate with patient outcome. Genomic analysis also has the potential to predict patient response to specific agents, thus ensuring patients derive the maximum benefit from the treatment they receive. Patients who require treatment are often exposed to the undesirable toxic effects that are associated with some treatments. Liposomal and nanoparticle formulations of currently available agents have been shown to be at least as effective as their parent compounds but with improved safety and tolerability profiles. Studies into patient quality of life during therapy have highlighted the importance of early administration of an erythropoietic agent to treat chemotherapy-induced anemia. Further research in breast cancer should further optimize the treatment patients receive ensuring that patients not only live longer but also have quality survival.

Antineoplastic Combined Chemotherapy Protocols↗

PubMed2006

Multiple dysregulated pathways in nasopharyngeal carcinoma revealed by gene expression profiling.

Gene expression profiling was conducted using primary human nasopharyngeal carcinoma (NPC) biopsy samples to improve the understanding of the molecular pathways defining NPC and to identify novel potential therapeutic targets. RNA samples were extracted from 36 patients suspected to have NPC and hybridized onto the Affymetrix U133A chip. NPC was diagnosed in 19 patients, 11 had lymphoid hyperplasia (LH), and 6 were "normal" biopsies. Clinical stages for these NPC patients ranged from I-IV, including one M1. All NPC patients (except the M1) were treated with curative intent, which included radiotherapy alone (4 patients), or combined with chemotherapy (14 patients). Unsupervised clustering demonstrated a distinct NPC expression pattern, compared to normal biopsies. Subsequent Significance Analysis of Microarrays (SAM) derived from 14 NPC and 6 normal samples discovered 1,089 differentially regulated genes. Pathway analyses revealed novel insights into the mechanisms leading to NPC, whereby upregulation of NFkappaB2 and survivin play central roles in increasing resistance to apoptosis, and changes in integrin and WNT/beta-catenin signaling leading to uncontrolled proliferation. The role of survivin in resisting apoptosis in NPC was confirmed by RNA interference. Our data provide novel insights into the development and progression of NPC, and suggest survivin as a novel therapeutic target for NPC.

Apoptosis↗

PubMed2026

Predicting diagnostic gene biomarkers associated with immune infiltration in patients with diabetes.

Diabetes is a global public health problem with various complications, which can lead to disability and mortality. This study identified potential diagnostic markers for diabetes and explored the immunometabolic mechanisms in the pathological process. The gene expression of 17 diabetes cases and 16 normal controls were obtained from the Gene Expression Omnibus (GEO) database. The "limma" package was employed for screening differentially expressed genes (DEGs). Gene functions and enriched pathways of DEGs were analyzed via Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. Candidate key genes were screened using the least absolute shrinkage and selection operator (LASSO) regression model and support vector machine recursive feature elimination (SVM-RFE) analysis. The diagnostic effectiveness of identified markers was further verified via the receiver operating characteristic (ROC) curve. The compositional patterns of immune cell infiltration and signaling pathway enrichment associated with key genes were explored via single sample Gene Set Enrichment Analysis (ssGSEA) and GSEA analysis, respectively. Possible miRNAs interacting with key genes were predicted via miRcode database. B2M, FTL, SH3BGRL3, and SOD2 were recognized as diagnostic markers for diabetes based on LASSO regression and the support vector machine recursive feature elimination (SVM-RFE) feature selection algorithm. Analysis of immune cell infiltration demonstrated that the four key genes were related to B cells, neutrophils, macrophages, and CD8+ T cells. The diagnostic value of B2M, FTL, and SOD2 for diabetes was higher than that of SH3BGRL3 according to the ROC curve. Validation experiments indicated that the mRNA expression of B2M and FTL was increased in liver tissues of diabetic mice. B2M and FTL can act as diagnostic markers for diabetes and contribute to new understandings of the disease's molecular mechanisms.

Humans↗

PubMed2025

Distinct immune-metabolic phenotypes underlie poor coronary collateral circulation.

BACKGROUND: Coronary collateral circulation (CCC) significantly impacts myocardial perfusion and clinical outcomes in coronary artery disease patients, yet the underlying molecular heterogeneity remains inadequately characterized. OBJECTIVE: To identify distinct molecular phenotypes in patients with poor CCC, validate these phenotypes using clinical parameters, and evaluate their prognostic implications. METHODS: This study enrolled 149 patients (80 with good CCC and 69 with poor CCC) for high-throughput proteomic profiling. Unsupervised consensus clustering identified molecular subtypes within poor CCC patients, followed by differential expression analysis and KEGG pathway enrichment. Boruta feature selection was implemented, and multiple machine learning algorithms were tested on clinical data, with XGBoost optimization (accuracy 80.0%, F1-score 80.31%) and SHAP value interpretation. External validation was performed using the MIMIC database. Kaplan-Meier analysis and Cox regression models assessed major adverse cardiovascular events (MACE). RESULTS: Two distinct phenotypes emerged among poor CCC patients: Cluster 1 (n = 39, Complement-Driven Vascular Remodeling [CDVR]) and Cluster 2 (n = 30, Immuno-Thrombotic Myocardial Dysfunction [ITMD]). An XGBoost model incorporating fasting glucose, eosinophil percentage, and HbA1c achieved excellent discrimination (AUC > 0.91). External validation confirmed the phenotype-specific clinical patterns. Notably, Cluster 2 demonstrated significantly higher MACE incidence compared to Cluster 1 (Log-rank p < 0.05), with KEGG analysis revealing significant upregulation of platelet activation, diabetic cardiomyopathy, and metabolic pathways in the ITMD phenotype. CONCLUSION: Poor CCC encompasses distinct immune-metabolic phenotypes that can be accurately classified using integrated proteomic-clinical modeling. This classification enables more precise risk stratification and may guide personalized therapeutic strategies for coronary artery disease patients with inadequate collateralization.

Humans↗