Biomarker Insights最新文献

Background: ATP7B (ATPase copper transporting beta gene) is constituted of 21 exons, and codes for a 1465 amino acid. The protein of ATP7B plays an key role of copper metabolism. Many previous reports indicated that mutations in ATP7B are well known to cause defective copper transporting copper-transporting ATPase 2 protein leading to the accumulation of copper, resulting the Wilson disease.

Objectives: The meta-analysis was performed to comprehensive gain a thorough grasp of the spectrum of genetic variations.

Design: A meta-analysis was conducted according to the guiding of PRISMA. aiming to assess the diversity and frequency of mutations in the ATP7B gene, with an emphasis on mutations located within specific exons.

Data sources and methods: The dataset of detected mutations within their positions, types as well as nomenclature, were recorded from previous studies (spanning the year from 2013 to 2023). The analysis focused on exon-specific variations and their prevalence across different populations.

Results: A total of 40 studies were enrolled into current data analysis. Our comprehensive study revealed a variety of mutations, most notably over 50% of single nucleotide changes described, distributed over the 21 exons of the gene. Focusing on the exon 8, itisplayed the most diversity of mutations, with 18 studies identifying 53 unique variants, the majority of which were missense mutations (81.13%). Additionally, the variations c.2333G>A/T (p.R778Q/L), c.2305A>G (p.M769V), c.2336G>A (p.W779*), and c.2304dupC (p.M769HfsX26) are reported in many populations. The weighted mean of variants' proportion was used to calculate the pooled estimate of these percentages, which were 14.19% for c.2333G>A/T (p.R778Q/L), 2.70% for c.2305A>G (p.M769V), 1.42% for c.2336G>A (p.W779*), and 2.33% for c.2304dupC (p.M769HfsX26).

Conclusion: This design demonstrate to identify the spectrum of ATP7B gene's mutations, especially exon 8, offering important insights into the prevalence and significance of exon 8 mutations. Understanding the mutation in the ATP7B gene offers insights into the mechanisms behind WD and guides strategies for diagnosis and treatment.

Background: Helicobacter pylori (H. pylori) is a known gastro-intestinal pathogen but implicated in extra-gastric diseases. The relationship between H. pylori infection and type 2 diabetes (T2DM) remains insufficiently elucidated, particularly in terms of molecular mediators such as microRNAs (miRNAs) and messenger RNAs (mRNAs).

Objective: We aimed to characterize expression pattern of insulin signalling mRNAs and targeted miRNAs in T2DM patients exposed to H. pylori infection.

Methods: We conducted a cross-sectional study among patients diagnosed with type 2 diabetes mellitus and were aged 18 to 60 years. Overnight fasting blood samples were collected and processed for plasma and serum. The plasma samples were used for glucose estimation and the serum used for H. pylori IgG screening. Total RNA was extracted from the serum with commercial kit, and mRNAs and miRNAs quantified by RT-qPCR with specific primers and under predetermined amplification conditions. Clinical data were obtained from medical records of patients.

Results: Among 351 patients enrolled, 267 (76.1%) were females, 224 (63.8%) were married, and 79 (22.5%) had tertiary education. Expression level of insulin receptor mRNA was significantly lower in H. pylori positive T2DM patients compared to H. pylori negative (P < .05). There was no evidence of a difference in insulin receptor substrate 1 mRNA level (P > .05). Although not statistically significant, the expression levels of miRNA-222 and miRNA-155 in the patients exposed to H. pylori were higher than that of the unexposed group (P > .05).

Conclusions: We found a significantly reduced serum insulin receptor messenger RNA level and higher levels of miRNA-222 and miRNA-155 in H. pylori exposed T2DM patients. The findings suggest a possible role of the infection in insulin signalling alteration in the patients.

Background: Sensitivity to ionizing radiation differs between individuals, but there is a limited understanding of the biological mechanisms that account for these variations. One example of such mechanisms are the mutations in the ATM (mutated ataxia telangiectasia) gene, that cause the rare recessively inherited disease Ataxia telangiectasia (AT). Hallmark features include chromosomal instability and increased sensitivity to ionizing radiation (IR).

Objectives: To deepen the molecular understanding of radiosensitivity and to identify potential new markers to predict it, human ATM-mutated and proficient cells were compared on a proteomic level.

Design: In this study, we analyzed 3 cell lines from AT patients, with varying radiosensitivity, and 2 cell lines from healthy volunteers, 24 hours and 72 hours post-10 Gy irradiation.

Methods: We used label-free mass spectrometry to identify differences in signaling pathways after irradiation in normal and radiosensitive individuals. Cell viability was initially determined by water soluble tetrazolium (WST) assay and DNA damage response was analyzed with 53BP1 repair foci formation along with KRAB-associated protein 1 (KAP1) phosphorylation.

Results: Proteomic analysis identified 4028 proteins, which were used in subsequent in silico pathway enrichment analysis to predict affected biological pathways post-IR. In AT cells, networks were heterogeneous at both time points with no common pathway identified. Mitotic cell cycle progress was the most prominent pathway altered after IR in cells from healthy donors. In particular, components of the chromosome passenger complex (INCENP and CDCA8) were significantly downregulated after 72 hours. This could also be verified at the mRNA level.

Conclusion: Altogether, the most striking result was that proteins forming the chromosome passenger complex were downregulated after radiation exposure in healthy normosensitive control cells, but not in radiosensitive ATM-deficient cells. Thus, mitosis-associated proteins form an interesting compound to gain insights into the development and prediction of radiosensitivity.

Background: Tumor-induced coagulation is widely observed in cancer patients. Moreover, it is associated with tumorigenesis, tumor progression and metastasis, by creating a proliferative and proangiogenic microenvironment. Therefore, D-dimer, a fibrin degradation product, correlates with tumor prognosis in several cancer types.

Objectives: This study aims to investigate whether D-dimer levels can be a predictive and monitoring indicator for chemotherapy response in metastatic breast cancer (MBC) patients.

Design: This was a prospective study.

Methods: This study included two groups, 76 patients diagnosed with metastatic breast carcinoma and 25 patients with primary breast carcinoma. Plasma D-dimer levels were measured prospectively before chemotherapy initiation, and after the fourth treatment cycle in MBC patients. D-dimer levels before chemotherapy (D0) were analyzed using Receiver Operating Characteristic (ROC) curves to determine the optimal cut-off baseline values of D0, and to evaluate their discriminatory abilities in predicting response to chemotherapy.

Results: In the preliminary response evaluation, the mean level of D-dimer significantly decreased by 0.65 μg/ml in patients with partial response patterns, and by 0.5 μg/ml in patients with stable disease. In the disease progression group, a marked increase was seen in D-dimer levels by 1.2 μg/ml. Analysis of ROC curves showed that D-dimer levels at D0 could discriminate the response to chemotherapy, whereas progressive disease rate correlated with higher levels of D-dimer.

Conclusion: D-dimer level in plasma is a useful predictive and monitoring marker of response to chemotherapy in metastatic breast cancer.

Background: Clinical biomarkers, allow better classification of patients according to their disease risk, prognosis, and/or response to treatment. Although affordable omics-based approaches have paved the way for quicker identification of putative biomarkers, validation of biomarkers is necessary for translation of discoveries into clinical application.

Objective: Accordingly, in this study, we emphasize the potential of in silico approaches and have proposed and applied 3 novel sequential in silico pre-clinical validation steps to better identify the biomarkers that are truly desirable for clinical investment.

Design: As protein biomarkers are becoming increasingly important in the clinic alongside other molecular biomarkers and lung cancer is the most common cause of cancer-related deaths, we used protein biomarkers for lung cancer as an illustrative example to apply our in silico pre-clinical validation approach.

Methods: We collected the reported protein biomarkers for 3 cases (lung adenocarcinoma-LUAD, squamous cell carcinoma-LUSC, and unspecified lung cancer) and evaluated whether the protein biomarkers have cancer altering properties (i.e., act as tumor suppressors or oncoproteins and represent cancer hallmarks), are expressed in body fluids, and can be targeted by FDA-approved drugs.

Results: We collected 3008 protein biomarkers for lung cancer, 1189 for LUAD, and 182 for LUSC. Of these protein biomarkers for lung cancer, LUAD, and LUSC, only 28, 25, and 6 protein biomarkers passed the 3 in silico pre-clinical validation steps examined, and of these, only 5 and 2 biomarkers were specific for lung cancer and LUAD, respectively.

Conclusion: In this study, we applied our in silico pre-clinical validation approach the protein biomarkers for lung cancer cases. However, this approach can be applied and adapted to all cancer biomarkers. We believe that this approach will greatly facilitate the transition of cancer biomarkers into the clinical phase and offers great potential for future biomarker research.

Background: Hypoxia, a condition where there is a lack of oxygen, is known to play a role in cancer progression.

Objective: This study investigates the correlation between HIF1A gene-altered expression and hypoxia in Bangladeshi breast cancer (BC) cases and TCGA_BC datasets.

Design: This case-control study compares BC cases to healthy controls to understand the relationship between gene changes and cancer.

Method: This study used advanced analysis methods to examine the transcriptional landscape of BC, and quantitatively assessed its correlation using integrated multi-omics analysis.

Results: In Bangladeshi BC cases, the T allele of HIF1A rs1154946 correlates notably (P-value < .001) with BC incidence. ELISA results confirmed a significant association (P-value < .005) between elevated HIF1A expression and BC-related hypoxia. Bioinformatics eQTL analysis validated the correlation between increased HIF1A expression and rs11549465 T allele (P-value < .01). Structural analyses suggested that rs11549465 (P582S) mutation may decrease protein stability (ΔΔG-value: -1.24 kcal/mole), potentially affecting HIF1A function. HIF1A enrichment analysis in BC underscores strong associations with oxygen levels, hypoxia, metabolic processes, apoptosis, and programed cell death (P-value < .001). Transcriptomic data demonstrated a robust correlation (P-value < .0001) between HIF1A expression and copy-number alterations, mutations, and abnormal methylation. Altered HIF1A expression showed strong negative correlations (P-value < .00001) with methylation and the expression of the ER (ESR1), in Whites. Survival analysis revealed marked differences in overall survival linked to high and low HIF1A expression (P-value < .00001). Furthermore, HIF1A expression significantly correlated (P-value < .000001) with hypoxia, TMB, MSI, and immune infiltration by CD8+ T cells, neutrophils, dendritic, and macrophages, providing deeper insights into the BC microenvironment.

Conclusion: Thus, the HIF1A gene could serve as a promising biomarker for breast cancer progression, control, and survival across ethnicities, emphasizing its role in disease development and regulation.

Background: Our previous research have identified Interleukin (IL)-7 and IL-15 as prognostic biomarkers for elderly septic patients, however, little is known about the link between the serum levels of IL-7, IL-15, and lactate as well as their potential roles in the regulation of inflammation in elderly septic patients.

Objectives: This study aimed at investigating the link between the serum levels of IL-7, IL-15, and lactate as well as with other factors in elderly septic patients.

Design: This is a retrospective study including 129 elderly patients with sepsis who were divided into the survival group (N = 34) and the nonsurvival group (N = 95) and further subgrouped based on the Acute Physiology and Chronic Health Evaluation II (APACHE II) scores.

Methods: The baseline data and clinical parameters were recorded within 24 h upon admission. Serum levels of the cytokines were quantified by the Luminex assay. Spearman correlation analysis were performed.

Results: Serum levels of IL-6, IL-7, IL-15, and tumor necrosis factor-α (TNF-α) were significantly higher in the nonsurvival group (P < .05). Correlations between serum levels of IL-7 and platelet-derived growth factor-AA (PDGF-AA), as well as correlations between IL-15, IL-6, and TNF-α were confirmed (P < .05). Both the serum levels of lactate and IL-15 correlated with the total counts of platelet (PLT) in the survival subgroup with low APACHE Ⅱ scores while the serum levels of IL-7, IL-15, and total counts of monocytes correlated with each other in the nonsurvival subgroup with different APACHE Ⅱ scores (P < .05).

Conclusion: Knowledge of the regulation networks between serum levels of IL-7, IL-15, lactate, and other cytokines may provide insights into potential mechanisms in the modulation of inflammation in elderly septic patients and facilitate more prompt and accurate treatment to reduce the mortality rate.

Objective: Colon cancer is associated with multiple levels of molecular heterogeneity. RNA processing converts primary transcriptional RNA to mature RNA, which drives tumourigenesis and its maintenance. The characterisation of RNA processing genes in colon cancer urgently needs to be elucidated.

Methods: In this study, we obtained 1033 relevant samples from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases to explore the heterogeneity of RNA processing phenotypes in colon cancer. Firstly, Unsupervised hierarchical cluster analysis detected 4 subtypes with specific clinical outcomes and biological features via analysis of 485 RNA processing genes. Next, we adopted the least absolute shrinkage and selection operator (LASSO) as well as Cox regression model with penalty to characterise RNA processing-related prognostic features.

Results: An RNA processing-related prognostic risk model based on 10 genes including FXR1, MFAP1, RBM17, SAGE1, SNRPA1, SRRM4, ADAD1, DDX52, ERI1, and EXOSC7 was identified finally. A composite prognostic nomogram was constructed by combining this feature with the remaining clinical variables including TNM, age, sex, and stage. Genetic variation, pathway activation, and immune heterogeneity with risk signatures were also analysed via bioinformatics methods. The outcomes indicated that the high-risk subgroup was associated with higher genomic instability, increased proliferative and cycle characteristics, decreased tumour killer CD8⁺ T cells and poorer clinical prognosis than the low-risk group.

Conclusion: This prognostic classifier based on RNA-edited genes facilitates stratification of colon cancer into specific subgroups according to TNM and clinical outcomes, genetic variation, pathway activation, and immune heterogeneity. It can be used for diagnosis, classification and targeted treatment strategies comparable to current standards in precision medicine. It provides a rationale for elucidation of the role of RNA editing genes and their clinical significance in colon cancer as prognostic markers.

Background: Colorectal cancer (CRC) prognosis is determined by the disease stage with low survival rates for advanced stages. Current CRC screening programs are mainly using colonoscopy, limited by its invasiveness and high cost. Therefore, non-invasive, cost-effective, and accurate alternatives are urgently needed.

Objective and design: This retrospective multi-center plasma proteomics study was performed to identify potential blood-based biomarkers in 36 CRC patients and 26 healthy volunteers by high-resolution mass spectrometry proteomics followed by the validation in an independent CRC cohort (60 CRC patients and 44 healthy subjects) of identified selected biomarkers.

Results: Among the 322 identified plasma proteins, 37 were changed between CRC patients and healthy volunteers and were associated with the complement cascade, cholesterol metabolism, and SERPIN family members. Increased levels in CRC patients of the complement proteins C1QB, C4B, and C5 as well as pro-inflammatory proteins, lipopolysaccharide-binding protein (LBP) and serum amyloid A4, constitutive (SAA4) were revealed for first time. Importantly, increased level of C5 was verified in an independent validation CRC cohort. Increased C4B and C8A levels were correlated with cancer-associated inflammation and CRC progression, while cancer-associated inflammation was linked to the acute-phase reactant leucine-rich alpha-2-glycoprotein 1 (LRG1) and ceruloplasmin. Moreover, a 4-protein signature including C4B, C8A, apolipoprotein C2 (APO) C2, and immunoglobulin heavy constant gamma 2 was changed between early and late CRC stages.

Conclusion: Our results suggest that C5 could be a potential biomarker for CRC diagnosis. Further validation studies will aid the application of these new potential biomarkers to improve CRC diagnosis and patient care.

Breast cancer is a heterogeneous disease with diverse histological and molecular subtypes. Luminal breast tumors are the most diagnosed subtype. In luminal breast cancer, hormone receptors (including ER, PR, HER2) play a diagnostic and prognostic role. Despite the effectiveness of endocrine therapy in luminal breast tumors, tumor recurrence and resistance occur, and this may highlight evolutionary strategies for survival driven by stemness. In this review we thus consider the association between estrogen signaling and stemness in mediating tumor processes. Many studies report stemness as one of the factors promoting tumor progression. Its association with estrogen signaling warrants further investigation and provides an opportunity for the identification of novel biomarkers which may be used for diagnostic, prognostic, and therapeutic purposes. Breast cancer stem cells have been characterized (CD44⁺ CD24^-) and their role in promoting treatment resistance and tumor recurrence widely studied; however, the complexity of tumor progression which also involve microenvironmental factors suggests the existence of more varied cell phenotypes which mediate stemness and its role in tumor progression.