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PubMed2026

Effects of GLP-1 Receptor Agonists and Dual GIP/GLP-1 Receptor Agonists on Inflammatory and Metabolic Biomarkers in Type 2 Diabetes: A Systematic Review and Meta-Analysis.

BACKGROUND: Glucagon-like peptide-1 receptor agonists (GLP-1RAs) and dual GIP/GLP-1 receptor agonists improve cardiovascular outcomes in type 2 diabetes mellitus (T2DM), but their effects on inflammatory and oxidative biomarkers are not fully defined. MATERIALS AND METHODS: We searched PubMed, Ovid MEDLINE, Scopus, Web of Science and the Cochrane Library from inception to 19 February 2026 for randomised controlled trials (RCTs) in adults with T2DM comparing a GLP-1RA or dual GIP/GLP-1 agonist with placebo or active therapy, and reporting C-reactive protein (CRP or high-sensitivity CRP [hs-CRP]), interleukin-6 (IL-6), tumour necrosis factor-α (TNF-α), monocyte chemoattractant protein-1 (MCP-1), malondialdehyde (MDA) or adiponectin. Random-effects meta-analyses were conducted using standardised mean differences (SMDs). RESULTS: Forty-one RCTs were included. GLP-1RAs significantly reduced CRP/hs-CRP (27 studies, 1991 participants; SMD -0.37, 95% CI -0.59 to -0.14) and MDA (3 studies, 272 participants; SMD -0.98, 95% CI -1.65 to -0.30), and increased adiponectin (16 studies, 1327 participants; SMD 0.30, 95% CI 0.13 to 0.46). Pooled effects on IL-6 (17 studies, 1068 participants; SMD -0.14, 95% CI -0.37 to 0.10), TNF-α (16 studies, 1164 participants; SMD -0.25, 95% CI -0.61 to 0.12) and MCP-1 (7 studies, 450 participants; SMD -0.27, 95% CI -0.58 to 0.03) were not statistically significant, although MCP-1 decreased in sensitivity analyses. Across biomarkers, heterogeneity was moderate to high. Two tirzepatide RCTs (562 participants) showed a significant reduction in IL-6 (SMD -0.28, 95% CI -0.47 to -0.09) and a non-significant trend towards lower CRP/hs-CRP. CONCLUSIONS: In adults with T2DM, incretin-based therapies consistently lower CRP/hs-CRP, reduce oxidative stress (MDA) and increase adiponectin, while effects on IL-6 and TNF-α are more variable. These data support a selective anti-inflammatory and metabolic regulatory profile of GLP-1-based therapy, but heterogeneity and limited data for some biomarkers warrant cautious interpretation and further mechanistic studies. TRIAL REGISTRATION: PROSPERO number: CRD420261321430.

Humans↗

PubMed2025

Expression analysis of LINC00671 and LINC01913 long non-coding RNAs in gastric cancer patients and their correlation with EMT markers.

BACKGROUND: Long-chain non-coding RNAs (lncRNAs) play various roles in the regulation of gene expression at the levels of transcription and translation, and epigenetic modification. Dysregulation of lncRNAs is associated with various malignancies, including cancer. lncRNAs have been demonstrated to regulate critical biological processes in cancer cells, such as apoptosis, proliferation, migration, and invasion. They also play essential roles in the development of gastric cancer (GC). However, the clinical significance and biological function of many lncRNAs remain unexplored in GC progression. This study aimed to evaluate the expression profiles of LINC00671 and LINC01913 in GC patients and investigate their correlation with epithelial-to-mesenchymal transition (EMT) markers. METHOD: The real-time PCR technique was applied to measure the expression levels of the selected lncRNAs (LINC01913 and LINC00671) and EMT-related mRNAs (MAMLs and MMP-13) in 83 tumor and adjacent normal tissues obtained from GC patients. RESULT: A significant reduction in LINC00671 expression was observed in 55.4% of tumor tissues, while elevated expression of LINC01913 (41%), MMP13 (56.6%), and MAML1 (44.6%) was detected, representing the proportion of samples with dysregulated expression relative to matched normal tissues. Dysregulation of these genes was significantly associated with various clinicopathological features (P < 0.05), supporting a potential link between these lncRNAs and EMT processes in GC. CONCLUSION: The observed associations between LINC00671, LINC01913, and EMT-related genes suggest their potential as prognostic biomarkers for treatment response in GC patients.

Humans↗

PubMed2005

Identification of 2 serum biomarkers of renal cell carcinoma by surface enhanced laser desorption/ionization mass spectrometry.

PURPOSE: Surface enhanced laser desorption/ionization mass spectrometry can generate robust information from a small amount of clinical samples such as serum and plasma. In this study we identified novel diagnostic biomarkers of renal cell carcinoma (RCC) by large-scale serum protein profiling using surface enhanced laser desorption/ionization mass spectrometry. MATERIALS AND METHODS: Proteomic spectra were generated by a time of flight mass spectrometer from a set of training samples (21 patients with RCC and 24 healthy volunteers) and another set of validation samples (19 patients with RCC, 20 healthy volunteers and 5 patients with pyelonephritis). Information on the peaks (intensity and m/z) was extracted from the mass spectra using newly developed algorithms, and the Mann-Whitney's U test and linear support vector machine were used to identify the peaks distinguishing RCC samples from the controls. RESULTS: Two peaks with molecular masses of 4,151 and 8,968 m/z were selected as significantly more prominent in RCC samples (p <0.01) among the 3,539 peaks in the range of 3,000 to 30,000 m/z obtained from the training samples. Simultaneous recognition of these 2 biomarkers was shown to have a sensitivity of 89.5% for the diagnosis of RCC and an overall specificity of 80.0% (95% [19 of 20] of healthy volunteers and 20% [1 of 5] of patients with pyelonephritis) in the blinded validation samples, and to allow detection of RCC in stage I (UICC) in 88.9% (16 of 18) of the cases. CONCLUSIONS: We identified 2 serum biomarkers potentially useful for the early diagnosis of RCC. This finding warrants a further large-scale multi-institutional analysis for clinical evaluation of the diagnostic significance of these biomarkers.

Adult↗

PubMed2002

Design of proteome-based studies in combination with serology for the identification of biomarkers and novel targets.

Recently proteome analysis has rapidly developed in the post-genome era and is now widely accepted as a complementary technology to genetic profiling. The improvement in the technology of both two-dimensional electrophoresis (2-DE) analysis as well as protein identification has made proteomics a valuable and powerful tool to study human diseases. A combination of conventional proteome analysis with serology has been developed as a promising experimental approach for the discovery of serological markers in different malignancies. However, the design of proteome-based studies has to be carefully performed since there are a number of critical needs for systematic and reproducible proteome analysis. In particular, the selection of tissue and its preparation represent an important step in proteome analysis. Besides the preparation of protein samples, the 2-DE and protein identification is a further critical issue. So far proteome-based technologies have been successfully used in tumor immunnology for the identification of tumor-specific autoantigens. Similarly, this technology has been employed for the detection of virulence factors, antigens and vaccine candidates in infectious diseases, as well as for the identification of diagnostic and prognostic markers, suggesting that proteome-based analysis is a promising tool for the identification of prognostic, diagnostic markers as well as for novel therapeutic targets which could be used for treatment of diseases. The integration of proteome-based approaches with data from genomic or genetic profiling will lead to a better understanding of different diseases, which will then contribute to the direct translation of the research findings into clinical practice.

Antigens, Neoplasm↗

PubMedDate not supplied

Transcriptional profiling of circulating tumor cells: quantification and cancer progression (Review).

Circulating tumor cells in peripheral blood have been demonstrated to reflect the biological characteristics of tumors including the potential for metastasis development and tumor recurrence. A number of mRNA markers may feasibly enable the detection of circulating tumor cells from virtually all patients with different cancer types. Of clinical relevance, quantification of circulating tumor cell mRNAs in cancer patients may prove valuable for monitoring disease progression and patients' response to treatment, and assessing the risk for metastasis or recurrence. With prognostic implications, the quantities of mRNA markers in blood could indicate the stage of cancer progression and the need for more intensive therapeutic intervention to better the outcome of cancer patients.

Biomarkers, Tumor↗

PubMed2005

The molecular signature of metastases of human hepatocellular carcinoma.

The current metastasis paradigm suggests that the primary tumor starts off benign but over time slowly acquires changes that provide a few rare cells within the tumor the ability to metastasize. However, this concept has been challenged by several recent studies using the microarray-based approach. We have recently found that the molecular signature of primary hepatocellular carcinoma (HCC) is very similar to that of their corresponding metastases, while it differs significantly in primary HCCs with or without metastasis. Similar findings are also evident in primary cancers of the lung, breast, and prostate. Such a signature can be used to predict the prognosis of HCC patients. Moreover, there are significant differences in the gene expression profiles of liver parenchyma among HCC patients with or without intrahepatic metastases. These findings imply that many of the metastasis-promoting genes are embedded in the primary tumors and that the ability to metastasize may be an inherent quality of the tumor from the beginning. In addition, the condition of liver parenchyma may dictate the intrahepatic metastasis potential, which is consistent with the hypothesis that the degree of viral-hepatitis-mediated liver damage or possibly the genetic makeup of individuals may play an important role in metastasis.

Biomarkers, Tumor↗

PubMed2006

Global gene expression profiling of circulating endothelial cells in patients with metastatic carcinomas.

Increased numbers of endothelial cells are observed in peripheral blood of cancer patients. These circulating endothelial cells (CECs) may contribute to the formation of blood vessels in the tumor or reflect vascular damage caused by treatment or tumor growth. Characterization of these cells may aid in the understanding of the angiogenic process and may provide biomarkers for treatment efficacy of angiogenesis inhibitors. To identify markers typical for CECs in cancer patients, we assessed global gene expression profiles of CD146 immunomagnetically enriched CECs from healthy donors and patients with metastatic breast, colorectal, prostate, lung, and renal cancer. From the generated gene profiles, a list of 61 marker genes for CEC detection was generated, and their expression was measured by real-time quantitative PCR in blood samples from 81 metastatic cancer patients and 55 healthy donors that were immunomagnetically enriched for CECs. A set of 34 genes, among which novel CEC-associated genes, such as THBD, BST1, TIE1, POSTN1, SELE, SORT1, and DTR, were identified that were expressed at higher levels in cancer patients compared with healthy donors. Expression of the VWF, DTR, CDH5, TIE, and IGFBP7 genes were found to discriminate between cancer patients and "healthy" donors with a receiver operating characteristic curve accuracy of 0.93. Assessment of the expression of these genes may provide biomarkers to evaluate treatment efficacy.

Biomarkers, Tumor↗

PubMed2006

[Application of SELDI-TOF MS technology analyzing serum protein profiling for distinguishing laryngeal carcinoma from ordinary people].

OBJECTIVE: To analyze the spectrometric serum protein profiling of laryngeal carcinoma and healthy controls by surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS), to establish serum marker pattern for the diagnosis of laryngeal carcinoma. METHOD: The serum samples of 46 cases of laryngeal carcinoma, 51 cases of healthy controls on WCX2 proteinchip, were collected. the spectrometric protein profiling was defected by SELDI-TOF-MS, the data were analyzed by Biomarker Patterns Software provided by Ciphergen Corp. A primary diagnosis model of laryngeal carcinoma was set up. This model was further evaluated by blind test with other l2 cases patients and 13 cases healthy controls. RESULT: Seventy-six protein peaks were detected at the molecular range of 2000-20000 Da., among which 27 ones were significantly different between laryngeal carcinoma and controls( P < 0.05). A diagnostic pattern consisting of 3 protein peaks was established with of accuracy 88.7% (86/97), sensitivity 87% (40/46), specificity 90.2% (46/51), Blind test generated a sensitivity of 83.3% (10/12)and specificity of 84.6% (11/13) respectively. CONCLUSION: It is successful to develop and evaluate the different spectrometric protein profiling patterns of laryngeal carcinoma and healthy control by SELDI-TOF-MS. This affords possibly a new method to early diagnosis of laryngeal carcinoma.

Adult↗

PubMed2026

Integrated transcriptomic and immunogenomic analysis unravels the immunological functions and prognostic landscape of WD repeat domain 76.

BackgroundWD Repeat Domain 76 (WDR76) plays a potential role in cellular regulation; however, its comprehensive landscape across human malignancies and its specific biological function in hepatocellular carcinoma (HCC) remain largely unexplored.MethodsWe conducted a systematic pan-cancer analysis utilizing multi-omics data from The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), and Cancer Cell Line Encyclopedia (CCLE) atabases to evaluate WDR76 expression, subcellular localization, and its correlation with clinicopathologic features, genomic instability, and immune infiltration. Diagnostic and prognostic values were assessed via Receiver operating characteristic (ROC) and Kaplan-Meier analyses. Furthermore, the functional role of WDR76 in HCC was validated in vitro using Hep-3B and Huh7 cell lines through siRNA-mediated knockdown, followed by CCK-8, wound-healing, and transwell assays.ResultsWDR76 was significantly upregulated in the majority of tumor types, including LIHC, LUAD, and COAD, while exhibiting nuclear localization. Elevated WDR76 expression correlated with advanced tumor staging, metastasis, and poor clinical outcomes across multiple cohorts, particularly in ACC, KIRP, and LIHC. ROC analysis highlighted its exceptional diagnostic precision in cancers such as GBM and LIHC. Immunologically, WDR76 expression was intricately linked to immune cell infiltration, immune checkpoint markers, and genomic instability parameters, suggesting a role in shaping the tumor microenvironment. Drug sensitivity profiling revealed that high WDR76 levels correlate with resistance to specific chemotherapeutic agents. Experimentally, silencing WDR76 in HCC cells significantly suppressed cell proliferation, migration, and invasion capabilities.ConclusionOur study establishes WDR76 as a robust pan-cancer prognostic biomarker and a potential immunotherapeutic target. Specifically, we provide experimental evidence that WDR76 functions as an oncogenic driver in liver cancer, promoting malignant phenotypes and offering a novel avenue for targeted therapeutic intervention.

Humans↗

PubMed2004

Acute leukemia subclassification: a marker protein expression perspective.

Improved leukemia classification and tailoring of therapy have greatly improved patient outcome particularly for children with acute leukemia (AL). Using immunophenotyping, molecular genetics and cytogenetics the low hanging fruits of biomedical research have been successfully incorporated in routine diagnosis of leukemia subclasses. Future improvements in the classification and understanding of leukemia biology will very likely be more slow and laborious. Recently, gene expression profiling has provided a framework for the global molecular analysis of hematological cancers, and high throughput proteomic analysis of leukemia samples is on the way. Here we consider classification of acute leukemia samples by flow cytometry using the marker proteins of immunophenotyping as a component of the proteome. Marker protein expressions are converted into quantitative expression values and subjected to computational analysis. Quantitative multivariate analysis from panels of marker proteins has demonstrated that marker protein expression profiles can distinguish MLLre from non-MLLre ALL cases and also allow to specifically distinguish MLL/AF4 cases. Potentially, these quantitative expression analyses can be used in clinical diagnosis. Immunophenotypic data collection using flow cytometry is a fast and relatively easily accessible technology that has already been implemented in most centers for leukemia diagnosis and the translation into quantitative expression data sets is a matter of flow cytometer settings and output calibration. However, before application in clinical diagnostics can occur it is crucial that quantitative immunophenotypic data set analysis is validated in independent experiments and in large data sets.

Acute Disease↗

PubMed2005

Prediction of glycan structures from gene expression data based on glycosyltransferase reactions.

MOTIVATION: Glycan chains are synthesized by a combination of several kinds of glycosyltransferases (GTs). Thus, once we know the repertoire of GTs in the genome, in the transcriptome or in the proteome, it should in principle be possible to predict the repertoire of possible glycan structures in an organism or at a specific stage of the cell. Here, we show that a repertoire of glycan structures can be predicted from the set of GTs in the transcriptome. That is, using knowledge about glycan structure characteristics, we can predict glycan structures from incomplete or noisy data such as DNA microarray data. RESULTS: First, we constructed a reaction pattern library consisting of bond-formation patterns of GT reactions and investigated the co-occurrence frequencies of all reaction patterns in the glycan database. This was followed by the prediction of glycan structures using this library and a co-occurrence score. A penalty score was also implemented in the prediction method. Then we examined the performance of prediction by the leave-one-out cross validation method using individual reaction pattern profiles in the KEGG GLYCAN database as virtual expression profiles. The accuracy of prediction was 81%. Finally, we applied the prediction method to real expression data. Using expression profiles from the human carcinoma cell, glycan structures with sialic acid and sialyl Lewis X epitope were predicted, which corresponded well with experimental results.

Algorithms↗

PubMed2005

Characterization of an acute molecular marker of nongenotoxic rodent hepatocarcinogenesis by gene expression profiling in a long term clofibric acid study.

Evaluation of the nongenotoxic potential early during the development of a drug presents a major challenge. Recently, two genes were identified as potential molecular markers of rodent hepatic carcinogenesis: transforming growth factor-beta stimulated clone 22 (TSC-22) and NAD(P)H cytochrome P450 oxidoreductase (CYP-R) (1). They were identified after comparing the gene expression profiles obtained from the livers of Sprague-Dawley rats treated with different genotoxic and nongenotoxic compounds in a 5 day repeat dose in vivo study. To assess the potential of these two genes as acute markers of carcinogenesis, we investigated their modulation during a long-term nongenotoxic study in the rat using a classic initiation-promotion regime. Clofibric acid (CLO), which belongs to the broad class of chemicals known as peroxisome proliferators, was used as a nongenotoxic hepatocarcinogen. Male F344 rats were given a single nonnecrogenic injection of diethylnitrosamine (0 or 30 mg/kg) and fed a diet containing none or 5000 ppm CLO for up to 20 months. Necropsies of five rats per groups were performed at 18, 46, 102, 264, 377, 447 (control, DEN, and DEN + CLO rats), 524, and 608 days (for the CLO and control rats). Gross macroscopic and microscopic evaluation and gene expression profiling (on Affymetrix microarrays) were performed in peritumoral and tumoral liver tissues. Bioanalysis of the liver gene expression data revealed that TSC-22 was strongly down-regulated early in the study. Its underexpression was maintained throughout the study but disappeared upon CLO withdrawal. These modulations were confirmed by real-time polymerase chain reaction. However, CYP-R gene expression was not significantly altered in our study. Taken together, our results showed that TSC-22, but not CYP-R, has the potential to be an acute early molecular marker for nongenotoxic hepatocarcinogenesis in rodents.

Animals↗

PubMed2006

Tissue microarray profiling of primary and xenotransplanted synovial sarcomas demonstrates the immunophenotypic similarities existing between SYT-SSX fusion gene confirmed, biphasic, and monophasic fibrous variants.

This paper discusses the diversity of synovial sarcomas (SSs) [biphasic (BSS), monophasic fibrous (MFSS), and poorly differentiated (PDSS)] and tissue microarray (TMA) evaluation of the immunophenotypic and histological progression of SSs in nude mice using three TMAs comprising 11 primary SSs (8 MFSSs, 2 BSSs, and 1 PDSS) and their xenografts. BSS and MFSS progressively transformed to a similar undifferentiated phenotype with loss of glandular component in the xenografts. Epidermal growth factor receptor and SALL2 were expressed in primary tumors and xenografts. Enhanced bcl-2 and bax expression were noted in xenografts. Ki-67 overexpression in xenografts correlated with high mitotic index. Epithelial membrane antigen (EMA) and cytokeratin AE1/AE3 were detected in all original and xenografted SSs. Hierarchical clustering differentiated original MFSS and BSS, but their xenografts clustered together due to similar immunoexpression profile. Our study demonstrates definite phenotypic variability of BSS and MFSS in the xenografts. Differences in immunoexpression for various markers existed between primary tumor and xenografts but not between subtypes. Hierarchical clustering grouped TMA immunostaining data and confirmed immunophenotypic variability; however, it failed to reveal any immunophenotypic differences between SYT-SSX1 and SYT-SSX2 type tumors. Nonetheless, reverse-transcriptase-polymerase chain reaction detected SYT-SSX transcripts in all primary SSs and their xenografts, thereby demonstrating their genetic stability.

Animals↗

PubMed2006

Applications of antibody array platforms.

Antibody arrays are valuable for the parallel analysis of multiple proteins in small sample volumes. The earliest and most widely used application of antibody arrays has been to measure multiple protein abundances, using sandwich assays and label-based assays, for biomarker discovery and biological studies. Modifications to these assays have led to studies profiling specific protein post-translational modifications. Additional novel uses include profiling enzyme activities and protein cell-surface expression. Finally, array-based antibody platforms are being used to assist the development and characterization of antibodies. Continued progress in the technology will surely lead to extensions of these applications and the development of new ways of using the methods.

Animals↗

PubMed2026

Novel genetic variants identification and immune profiling in ataxia telangiectasia patients.

BACKGROUND: Ataxia telangiectasia (AT) is an autosomal recessive neurodegenerative disease. While heterozygous relatives of AT patients are known to be clinically healthy, a predisposition to various pathologies has been reported. Our aim was firstly, to further characterize the clinical features and broaden the spectrum of genetic pathogenic variants in AT patients. Secondly, we aimed to study the immune profiles of AT patients and their relatives to identify similarities or common biomarkers. METHODS: A Target Gene Sequencing for six patients suspected with AT was performed. Computational analysis was conducted to assess the pathogenicity of novel variants. The distribution of immune cells was assessed by flow cytometry in patients with AT, AT-like disorder, Friedreich ataxia, and in AT relatives. The expression pattern of candidate genes was evaluated by RT-qPCR. RESULTS: We identified and predicted the pathogenicity of novel variants in the ATM gene. Computational analysis suggested that the novel identified missense mutation could affect ATP binding pattern and ATM protein flexibility, while Alu element insertion could probably induces a premature stop codon. Furthermore, our results confirm the pathogenic effect of identified splicing mutations on the ATM transcript. Moreover, we noticed a high percentage of LTCD4 + and LTCD8 + senescent subsets in AT patients and a relative increase of the of intermediate and non-classical monocytes accompanied with a decrease of classical monocytes specifically in AT patients with truncated biallelic mutations which was intriguingly similar to the immune profile of AT parents. In addition, a difference of immune pattern was observed between AT patients with biallelic truncated mutations compared to those with at least one non-truncated mutation, with a variability intragroup. Gene expression analysis identified FOXO3, IL33 and METTL3 as putative genes that may yield clues into AT pathogenesis. CONCLUSION: Taken together, our study expands the mutational spectrum of AT disease worldwide and further characterize the immune profile of AT patients uncovering a possible difference in some immune cellular subsets related to ATM mutation type and delineate putative immune abnormalities related to ATM heterozygosity among AT parents. Furthermore, dysregulation in FOXO3, IL33 and METTL3 expression could be related to disease severity.

Humans↗

PubMed2003

Ensemble machine learning on gene expression data for cancer classification.

Whole genome RNA expression studies permit systematic approaches to understanding the correlation between gene expression profiles to disease states or different developmental stages of a cell. Microarray analysis provides quantitative information about the complete transcription profile of cells that facilitate drug and therapeutics development, disease diagnosis, and understanding in the basic cell biology. One of the challenges in microarray analysis, especially in cancerous gene expression profiles, is to identify genes or groups of genes that are highly expressed in tumour cells but not in normal cells and vice versa. Previously, we have shown that ensemble machine learning consistently performs well in classifying biological data. In this paper, we focus on three different supervised machine learning techniques in cancer classification, namely C4.5 decision tree, and bagged and boosted decision trees. We have performed classification tasks on seven publicly available cancerous microarray data and compared the classification/prediction performance of these methods. We have observed that ensemble learning (bagged and boosted decision trees) often performs better than single decision trees in this classification task.

Algorithms↗

PubMed2026

Plasma Proteome Signatures in Sickle Cell Anemia and the Effect of Hydroxyurea Treatment.

Sickle Cell Anaemia (SCA) is a monogenic blood disorder caused by a mutation in the β-globin gene, yet it presents with marked clinical variability. Although hydroxyurea (HU) is an established therapy, its precise mechanism of action remains incompletely understood. Plasma proteins represent valuable biomarkers for elucidating disease mechanisms and treatment responses. In this study, plasma proteome profiling of 31 healthy controls and 76 SCA patients identified 43 differentially abundant proteins (DAPs) that form a highly interconnected interaction network. Proteins with increased abundance in SCA were largely associated with immune and inflammatory responses, whereas those with reduced levels were linked to coagulation and proteolytic pathways. HU therapy was associated with elevated levels of haptoglobin (HP) and hemopexin (HPX), key mediators of free hemoglobin scavenging. We also identified several previously unreported plasma proteins altered in SCA, broadening the landscape of potential biomarkers and HU-responsive targets. Many DAPs significantly correlated with clinical indices, such as transfusion frequency, vaso-occlusive crises, white blood cell counts, and platelet counts, offering insights into disease mechanisms and potential utility in disease management. Notably, overlap with β-thalassemia-associated signatures suggests shared pathophysiological pathways between these hemoglobinopathies. Collectively, these findings provide a strong foundation for translational validation in larger, independent cohorts.

Humans↗

PubMed2004

Overexpression of SPARC gene in human gastric carcinoma and its clinic-pathologic significance.

Gastric cancer is the second most common cancer in the world and the fifth leading cause of cancer-related death in Taiwan. To improve the survival of gastric cancer patients, biomarkers for early detection and effective anticancer therapy are required. An essential first step is to profile gene expression in gastric cancer and identify genes that are aberrantly expressed, and to do this cDNA microarrays were performed. The clinic-pathologic correlation and prognostic significance of the aberrantly expressed genes were evaluated to identify novel biomarkers of gastric cancer. Fresh surgical samples of tumour tissue and matching noncancerous mucosa were obtained immediately after gastric resection in 43 patients. Secreted Protein, Acidic and Rich in Cysteine (SPARC) (Osteonectins), one of the most highly expressed genes in both intestinal and diffuse gastric cancers in our microarray results, was selected for further study. The overexpression of SPARC was verified using real-time quantitative-reverse transcription-polymerase chain reaction (Q-RT-PCR), Northern blot and immunohistochemical staining. The expression of SPARC in tumour tissues was, on average, 4.27-fold increased (95% CI 2.68-5.85) compared to adjacent noncancerous mucosa (P<0.001). The expression of SPARC was higher in advanced (T2, T3 and T4) cancer compared to the early (T1) cancer (P=0.048) with regard to depth of wall invasion. Higher expression of SPARC was significantly associated with lymph node metastasis (P<0.001), lymphatic invasion (P=0.004) and perineural invasion (P=0.047). Expression of SPARC in patients in stage II and above was significantly higher than those in stage I (P=0.017). The 3-year survival of patients with lower expression of SPARC was significantly better than those with a higher expression (log rank P=0.047). These data indicate the potential of SPARC as a prognostic marker for gastric cancer.

Adult↗