Cancer Diagnostic Biomarkers Research Articles

Diagnostic and prognostic value of CD44v9 and TIM3 expression in CK‑ and CK+ regions in gastric cancer tissues.

The specificity and sensitivity of the current diagnostic and prognostic biomarkers for gastric cancer (GC) are limited. The present study aimed to evaluate the diagnostic and prognostic significance of cluster-of-differentiation gene 44 variant isoform 9 (CD44v9) and T cell immunoglobulin and mucin domain-containing protein 3 (TIM3) expression levels alone or combined in the tumor tissues of patients with GC and reveal the roles of CD44v9 and TIM3 in the cytokeratin (CK)+ and CK- regions. Multiplex immunofluorescence staining was performed for CD44v9, TIM3 and CK using a tissue microarray. The tissues were divided into three regions based on CK expression: Total, CK+, and CK- regions. The diagnostic and prognostic value was evaluated using receiver operating characteristic curves, Kaplan-Meier and Cox regression analyses. The results demonstrated that the density of cells expressing CD44v9, TIM3 and co-expressing CD44v9 and TIM3 (CD44v9/TIM3) in both the CK+ and CK- regions of tumor tissues was significantly higher than those in normal tissues (P<0.001). Moreover, the expression of CD44v9 in the CK- region was significantly positively correlated with age and tumor grade (P<0.05), and the expression of CD44v9/TIM3 in the CK- region of tumor tissues was significantly positively correlated with age, tumor grade and metastasis (P<0.05). Furthermore, the area under the curve for TIM3 expression in the CK+ region was 0.709, with a sensitivity of 45.83% and a specificity of 85.54% (P<0.001). High expression of CD44v9 in the CK- region was also significantly associated with poor survival and independently predicted a poor prognosis in patients with GC (hazard ratio, 2.387; 95% confidence interval, 1.384-4.118; P<0.01). In conclusion, dividing tissue regions based on CK expression is important for the diagnosis of GC. The expression of TIM3 in the CK+ region demonstrated diagnostic potential for GC, and high expression of CD44v9 in the CK- region was an independent prognostic risk factor for patients with GC.

TopMarker: Computational screening biomarkers of hepatocellular carcinoma from transcriptome and interactome based on differential network topological parameters

Identifying diagnostic biomarkers for cancer is crucial in the field of personalized medicine. The available transcriptome and interactome provide unprecedented opportunities and challenges for biomarker screening. From a systematic perspective, network-based medicine methods provide alternative approaches to organizing the available high-throughput omics data for deciphering molecular interactions and their associations with phenotypic states. In this work, we propose a bioinformatics strategy named TopMarker for discovering diagnostic biomarkers by comparing the network topology differences in control and disease samples. Specifically, we build up gene-gene interaction networks in the two states of control and disease respectively. The network rewiring status across the two networks results in differential network topologies reflecting dynamics and changes in normal samples when compared with those in disease. Thus, we identify the potential biomarker genes with differential network topological parameters between the control and disease gene networks. For a proof-of-concept study, we introduce the computational pipeline of biomarker discovery in hepatocellular carcinoma (HCC). We prove the effectiveness of the proposed TopMarker method using these candidate biomarkers in classifying HCC samples and validate its signature capability across numerous independent datasets. We also compare the discriminant power of biomarker genes identified by TopMarker with those identified by other baseline methods. The higher classification performances and functional implications indicate the advantages of our proposed method for discovering biomarkers from differential network topology.

PUM1-TRAF3 fusion protein activates non-canonical NF-κB signaling via rescued NIK in biliary tract cancer

Discovery and verification of diagnostic or therapeutic biomarkers for biliary tract cancer (BTC) is challenging owing to the low prevalence of the disease. Here, we identified and investigated the clinical impact of a fusion gene, Pumilio1-tumor necrosis factor receptor-associated factor 3 (PUM1-TRAF3), caused by 1;14 chromosomal translocation in BTC. PUM1-TRAF3 was initially identified in the RNA-sequencing of five BTC surgical tissues and confirmed by fluorescence in situ hybridization. Expression of the fusion gene was validated in an expanded cohort (5/55, 9.1%). Establishment and molecular assessment of PUM1-TRAF3 expressing BTC cells revealed that PUM1-TRAF3 activates non-canonical NF-κB signaling via NF-κB-inducing kinase (NIK). Abnormal TRAF3 activity, driven by competitive binding of PUM1-TRAF3 and TRAF3 to NIK, led to NIK rescue followed by P52/RelB nuclear translocation, all of which were reverted by an NIK inhibitor. The elevated expression of NIK and activated NF-κB signaling was observed in the PUM1-TRAF3-expressing regions of patient tissues. Expression of the PUM1-TRAF3 fusion was significantly correlated with strong NIK expression, which is associated with a poorer prognosis for patients with BTC. Overall, our study identifies a new fusion gene, PUM1-TRAF3, that activates NIK and non-canonical NF-κB signaling, which may be beneficial for developing precise treatment strategies for BTC.

Screening of gastric cancer diagnostic biomarkers in the homologous recombination signaling pathway and assessment of their clinical and radiomic correlations.

Homologous recombination plays a vital role in the occurrence and drug resistance of gastric cancer. This study aimed to screen new gastric cancer diagnostic biomarkers in the homologous recombination pathway and then used radiomic features to construct a prediction model of biomarker expression to guide the selection of chemotherapy regimens. Gastric cancer transcriptome data were downloaded from The Cancer Genome Atlas database. Machine learning methods were used to screen for diagnostic biomarkers of gastric cancer and validate them experimentally. Computed Tomography image data of gastric cancer patients and corresponding clinical data were downloaded from The Cancer Imaging Archive and our imaging centre, and then the Computed Tomography images were subjected to feature extraction, and biomarker expression prediction models were constructed to analyze the correlation between the biomarker radiomics scores and clinicopathological features. We screened RAD51D and XRCC2 in the homologous recombination pathway as biomarkers for gastric cancer diagnosis by machine learning, and the expression of RAD51D and XRCC2 was significantly positively correlated with pathological T stage, N stage, and TNM stage. Homologous recombination pathway blockade inhibits gastric cancer cell proliferation, promotes apoptosis, and reduces the sensitivity of gastric cancer cells to chemotherapeutic drugs. Our predictive RAD51D and XRCC2 expression models were constructed using radiomics features, and all the models had high accuracy. In the external validation cohort, the predictive models still had decent accuracy. Moreover, the radiomics scores of RAD51D and XRCC2 were also significantly positively correlated with the pathologic T, N, and TNM stages. The gastric cancer diagnostic biomarkers RAD51D and XRCC2 that we screened can, to a certain extent, reflect the expression status of genes through radiomic characteristics, which is of certain significance in guiding the selection of chemotherapy regimens for gastric cancer patients.

CTHRC1 is associated with BRAF(V600E) mutation and correlates with prognosis, immune cell infiltration, and drug resistance in colon cancer, thyroid cancer, and melanoma.

Colon cancer, thyroid cancer, and melanoma are common malignant tumors that seriously threaten human health globally. The B-Raf proto-oncogene, serine/threonine kinase (BRAF)(V600E) mutation is an important driver gene mutation in these cancer types. In this study, we identified that collagen triple helix repeat containing 1 (CTHRC1) expression was associated with the BRAF(V600E) mutation in colon cancer, thyroid cancer, and melanoma. Based on database analysis and clinical tissue studies, CTHRC1 was verified to correlate with poor prognosis and worse clinicopathological features in colon cancer and thyroid cancer patients, but not in patients with melanoma. Several signaling pathways, immune cell infiltration, and immunotherapy markers were associated with CTHRC1 expression. Additionally, a high level of CTHRC1 was correlated with decreased sensitivity to antitumor drugs (vemurafenib, PLX-4720, dabrafenib, and SB-590885) targeting the BRAF(V600E) mutation. This study provides evidence of a significant correlation between CTHRC1 and the BRAF(V600E) mutation, suggesting its potential utility as a diagnostic and prognostic biomarker in human colon cancer, thyroid cancer, and melanoma.

Gut Microbiota Signatures in Colorectal Cancer as a Potential Diagnostic Biomarker in the Future: A Systematic Review.

The gut microbiota has acquired significant attention in recent years for its potential as a diagnostic biomarker for colorectal cancer (CRC). In this literature review, we looked at the studies exploring alterations in gut microbiota composition associated with CRC, the potential mechanisms linking gut dysbiosis to CRC development, and the diagnostic approaches utilizing gut microbiota analysis. Our research has led to the conclusion that individuals with CRC often display alterations in their gut microbiota composition compared to healthy individuals. These alterations can include changes in the diversity, abundance, and type of bacteria present in the gut. While the use of gut microbiota as a diagnostic biomarker for CRC holds promise, further research is needed to validate its effectiveness and standardize testing protocols. Additionally, considerations such as variability in the microbiota composition among individuals and potential factors must be addressed before microbiota-based tests can be widely implemented in clinical practice.

Differential expression of long non-coding RNAs in colon cancer: Insights from transcriptomic analysis

BackgroundColon Cancer (CC) incidence has sharply grown in recent years. Long non-coding RNAs (lncRNA) are produced by a group of non-protein-coding genes, and have important functions in controlling gene expression and impacting the biological features of various malignancies including CC. MethodsOur research focused on examining the function of lncRNAs in the development of colon cancer. To this end, we selected and analyzed a dataset (GSE104836) from the GEO database, which contained information about the expression of mRNAs and lncRNAs in both colon cancer tissues and normal adjacent paired tumor tissues. The DESeq2 R package in Bioconductor was used to identify differentially expressed lncRNAs (DElncRNAs) and mRNAs (DEmRNAs) that showed differences in expression levels. Next, by literature review of previous studies, we chose two lncRNAs (FENDRR and LINC00092) for additional studies. To validate our findings, a series of tests were performed on a total of 31 tumor tissues and normal paired adjacent tumor tissues. The lncRNA expression levels were assessed in tumor tissues as well as in surrounding normal tumor tissues. ResultsThe data confirmed that just two particular lncRNAs, FENDRR and LINC00092, had considerably decreased expression levels throughout all stages of cancer. In addition, the survival assay was conducted using the GEPIA2 software, revealing that a reduced expression of FENDRR is correlated with a reduced overall survival. Furthermore, our investigation using receiver operating characteristic (ROC) methodology revealed that these two lncRNAs had significant discriminatory ability between colon cancer and normal tissues. To determine the cause of the decrease in the activity of these two long non-coding RNAs (lncRNAs), we used methylation-specific PCR (MSP) to examine the methylation pattern of their promoter regions. Our investigation revealed hypermethylation in the promoter regions of FENDRR and LINC00092 within tumor tissues compared to normal adjacent tumor tissues. ConclusionTaken together, our findings revealed the lncRNAs signatures as potential therapeutic targets and molecular diagnostic biomarkers in colon cancer. Furthermore, the evidence provided substantiates the important role of promoter methylation in regulating the expression levels for both of these lncRNAs.

Urinary Metabolite Diagnostic and Prognostic Liquid Biopsy Biomarkers of Lung Cancer in Nonsmokers and Tobacco Smokers.

Nonsmokers account for 10% to 13% of all lung cancer cases in the United States. Etiology is attributed to multiple risk factors including exposure to secondhand smoking, asbestos, environmental pollution, and radon, but these exposures are not within the current eligibility criteria for early lung cancer screening by low-dose CT (LDCT). Urine samples were collected from two independent cohorts comprising 846 participants (exploratory cohort) and 505 participants (validation cohort). The cancer urinary biomarkers, creatine riboside (CR) and N-acetylneuraminic acid (NANA), were analyzed and quantified using liquid chromatography-mass spectrometry to determine if nonsmoker cases can be distinguished from sex and age-matched controls in comparison with tobacco smoker cases and controls, potentially leading to more precise eligibility criteria for LDCT screening. Urinary levels of CR and NANA were significantly higher and comparable in nonsmokers and tobacco smoker cases than population controls in both cohorts. Receiver operating characteristic analysis for combined CR and NANA levels in nonsmokers of the exploratory cohort resulted in better predictive performance with the AUC of 0.94, whereas the validation cohort nonsmokers had an AUC of 0.80. Kaplan-Meier survival curves showed that high levels of CR and NANA were associated with increased cancer-specific death in nonsmokers as well as tobacco smoker cases in both cohorts. Measuring CR and NANA in urine liquid biopsies could identify nonsmokers at high risk for lung cancer as candidates for LDCT screening and warrant prospective studies of these biomarkers.

The Long Noncoding RNA PANDAR as a Prognostic and Diagnostic Biomarker in Panceratic Cancer ‏‏.

Pancreatic cancer (PC) is a lethal complication in the world, affecting around half a million individuals each year. The treatment of PC is relatively difficult due to the difficulty in making an early diagnosis. Most PC patients are confronted with locally metastatic or advanced diseases in the asymptomatic phase, and about 80% have late diagnosis with metastasis. Recently, long noncoding RNAs (lncRNAs) have drawn attention as a novel biological regulation layer. They take part in the regulation of mRNA and can be used as a prognostic factor or drug target. Based on their functions as regulators of PC initiation and progress, the lncRNAs can be categorized as tumor suppressors or oncogenic. They can be considered as a target for finding new biomarkers for prognosis, diagnosis, monitoring, and treating drug response in PC. Therefore, the present study summarizes the lncRNAs role in PC and the probable strategies to deal with their expression and controlling tumorigenesis and detection of the prognosis of PC.

Synergistic powering of DNA walker movement by endogenous dual enzymes for constructing dual-mode biosensors

To achieve highly sensitive and reliable detection of apurinic/apyrimidinic endonuclease 1 (APE1), a critical cancer diagnostic biomarker, we designed a DNA walker-based dual-mode biosensor, utilizing cellular endogenous dual enzymes (APE 1 and Flap endonuclease 1 (FEN 1)) to collaborate in activating and propelling DNA walker motion on DNA-functionalized Au nanoparticles. Incorporating both fluorescence and electrochemical detection modes, this system leverages signal amplification from DNA walker movement and cascade amplification through tandem hybridization chain reactions (HCR), achieving highly sensitive detection of APE 1. In the fluorescence mode, continuous DNA walker movement, initiated by APE1 and driven by FEN1, generates a robust signal response within a concentration range of 0.01–500 U mL−1, presenting a good linearity in the concentration range of 0.01–10 U mL−1, with a detection limit of 0.01 U mL−1. In the electrochemical detection module, the cascade upstream DNA walker and downstream HCR dual signal amplification strategy further enhances the sensitivity of APE1 detection, extending the linear range to 0.01–50 U mL−1 and reducing the detection limit to 0.002 U mL−1. Rigorous validation demonstrates the biosensor's specificity and anti-interference capability against multiple enzymes. Moreover, it effectively distinguishes cancer cells from normal cell lysates, exhibiting excellent stability and consistency in the dual-modes. Overall, our findings underscore the efficacy of the developed dual-mode biosensor for detecting APE1 in serum and cell lysates samples, indicating its potential for clinical applications in disease diagnosis.

Extraction and characterization of exosomes from the exhaled breath condensate and sputum of lung cancer patients and vulnerable tobacco consumers—potential noninvasive diagnostic biomarker source

Noninvasive sample sources of exosomes, such as exhaled breath and sputum, which are in close proximity to the tumor microenvironment and may contain biomarkers indicative of lung cancer, are far more permissive than invasive sample sources for biomarker screening. Standardized exosome extraction and characterization approaches for low-volume noninvasive samples are critically needed. We isolated and characterized exhaled breath condensate (EBC) and sputum exosomes from healthy nonsmokers (n = 30), tobacco smokers (n = 30), and lung cancer patients (n = 40) and correlated the findings with invasive sample sources. EBC samples were collected by using commercially available R-Tubes. To collect sputum samples the participants were directed to take deep breaths, hold their breath, and cough in a collection container. Dynamic light scattering, nanoparticle tracking analysis, and transmission electron microscopy were used to evaluate the exosome morphology. Protein isolation, western blotting, exosome quantification via EXOCET, and Fourier transform infrared spectroscopy were performed for molecular characterization. Exosomes were successfully isolated from EBC and sputum samples, and their yields were adequate and sufficiently pure for subsequent downstream processing and characterization. The exosomes were confirmed based on their size, shape, and surface marker expression. Remarkably, cancer exosomes were the largest in size not only in the plasma subgroups, but also in the EBC (p < 0.05) and sputum (p = 0.0036) subgroups, according to our findings. A significant difference in exosome concentrations were observed between the control sub-groups (p < 0.05). Our research confirmed that exosomes can be extracted from noninvasive sources, such as EBC and sputum, to investigate lung cancer diagnostic biomarkers for research, clinical, and early detection in smokers.

Combined detection of serum EFNA1 and MMP13 as diagnostic biomarker for gastric cancer

We previously identified that serum EFNA1 and MMP13 were potential biomarker for early detection of esophageal squamous cell carcinoma. In this study, our aim is to explore the diagnostic value of serum EFNA1 and MMP13 for gastric cancer. We used enzyme-linked immunosorbent assay (ELISA) to detect the expression levels of serum EFNA1 and MMP13 in 210 GCs and 223 normal controls. The diagnostic value of EFNA1 and MMP13 was evaluated in an independent cohorts of GC patients and normal controls (n = 238 and 195, respectively). Receiver operating characteristics were used to calculate diagnostic accuracy. In training and validation cohorts, serum EFNA1 and MMP13 levels in the GC groups were significantly higher than those in the normal controls (P < 0.001). The area under the curve (AUC) of the combined detection of serum EFNA1 and MMP13 for GC was improved (0.794), compared with single biomarker used. Similar results were observed in the validation cohort. Importantly, the combined measurement of serum EFNA1 and MMP13 to detect early-stage GC also had acceptable diagnostic accuracy in training and validation cohort. Combined detection of serum EFNA1 and MMP13 could help identify early-stage GC, suggesting that it may be a promising tool for the early detection of GC.

ECM1 and ANXA1 in urinary extracellular vesicles serve as biomarkers for breast cancer.

Although urinary extracellular vesicles (uEVs) have been extensively studied in various cancers, their involvement in breast cancer (BC) remains largely unexplored. The non-invasive nature of urine as a biofluid and its abundant protein content offer considerable potential for the early detection of breast cancer. This study analyzed the proteomic profiles of uEVs from BC patients and healthy controls (HC). The dysregulation of ECM1 and ANXA1 in the uEVs was validated in a larger cohort of 128 BC patients, 25 HC and 25 benign breast nodules (BBN) by chemiluminescence assay (CLIA). The expression levels of ECM1 and ANXA1 were also confirmed in the uEVs of MMTV-PyMT transgenic breast cancer mouse models. LC-MS/MS analysis identified 571 dysregulated proteins in the uEVs of BC patients. ECM1 and ANXA1 were selected for validation in 128 BC patients, 25 HC and 25 BBN using CLIA, as their fold change showed a significant difference of more than 10 with p-value<0.05. Protein levels of ECM1 and ANXA1 in uEVs were significantly increased in BC patients. In addition, the protein levels of ECM1 and ANXA1 in the uEVs of MMTV-PyMT transgenic mice were observed to increase progressively with the progression of breast cancer. We developed a simple and purification-free assay platform to isolate uEVs and quantitatively detect ECM1 and ANXA1 in uEVs by WGA-coupled magnetic beads and CLIA. Our results suggest that ECM1 and ANXA1 in uEVs could potentially serve as diagnostic biomarkers for breast cancer.

Novel diagnostic biomarkers for pancreatic cancer: assessing methylation status with epigenetic-specific peptide nucleic acid and KRAS mutation in cell-free DNA.

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive tumor with a poor prognosis that poses challenges for diagnosis using traditional tissue-based techniques. DNA methylation alterations have emerged as potential and promising biomarkers for PDAC. In this study, we aimed to assess the diagnostic potential of a novel DNA methylation assay based on epigenetic-specific peptide nucleic acid (Epi-sPNA) in both tissue and plasma samples for detecting PDAC. The study involved 46 patients with PDAC who underwent surgical resection. Epi-TOP pancreatic assay was used to detect PDAC-specific epigenetic biomarkers. The Epi-sPNA allowed accurate and rapid methylation analysis without bisulfite sample processing. Genomic DNA extracted from paired normal pancreatic and PDAC tissues was used to assess the diagnostic efficacy of epigenetic biomarkers for PDAC. Subsequent validation was conducted on cell-free DNA (cfDNA) extracted from plasma samples, with 10 individuals represented in each group: PDAC, benign pancreatic cystic neoplasm, and healthy control. The combination of seven epigenetic biomarkers (HOXA9, TWIST, WT1, RPRM, BMP3, NPTX2, and BNC1) achieved 93.5% sensitivity and 96.7% specificity in discerning normal pancreatic from PDAC tissues. Plasma cfDNA, analyzed using these markers and KRAS mutations, exhibited a substantial 90.0% sensitivity, 95.0% specificity, and an overall 93.3% accuracy for discriminating PDAC. Notably, cancer antigen 19-9 and carcinoembryonic antigen both had an accuracy of 90.0%. Our study suggests that analyzing seven differentially methylated genes with KRAS mutations in cfDNA using the novel Epi-TOP pancreatic assay is a potential blood-based biomarker for the diagnosis of PDAC.

Unveiling Diagnostic Biomarkers in High-Grade Serous Ovarian Cancer Through Bioinformatics Analysis

Unveiling Diagnostic Biomarkers in High-Grade Serous Ovarian Cancer Through Bioinformatics Analysis

FTO promotes the progression of bladder cancer via demethylating m6A modifications in PTPN6 mRNA

Bladder cancer (BC), a highly prevalent malignancy of the urinary system, necessitates further investigation into its progression mechanisms. N6-methyladenosine (m6A) RNA methylation, a prevalent modification in cellular RNA, has been implicated in the tumorigenesis and metastasis of various cancers. In this study, the upregulation of FTO in human BC samples and its association with poor prognosis were demonstrated using immunohistochemistry (IHC) on tissue sections collected from BC patients. The functional role of FTO in promoting the proliferation and metastasis abilities of BC cells was determined using a combination of in vitro and in vivo assays. In vitro, we conducted cell proliferation assays, such as the Cell Counting Kit-8 (CCK-8) assay, and metastasis assays, including the wound healing assay and transwell invasion assay. In vivo, we employed xenograft models to assess tumor growth and metastasis. Furthermore, our investigation into potential FTO targets in BC cells revealed that FTO modifies PTPN6 mRNA, leading to increased stability and expression of PTPN6, thereby enhancing proliferation and metastasis abilities. In conclusion, our findings indicate that FTO serves as an oncogenic factor in BC, suggesting its potential utility as a diagnostic or prognostic biomarker for bladder cancer.

Potential diagnostic, prognostic, and predictive biomarkers of gastric cancer.

Gastric cancer (GC), a malignant epithelial tumor, is the fourth leading cause of cancer-related death worldwide. Therapeutic strategies for GC, despite the biggest challenges, can significantly improve survival rates through early detection and effective screening methods. To provide brief information on the necessity of multiple specific diagnostic, prognostic, and predictive markers for GC. This review was conducted using a variety of search engines, including PubMed Central, Scopus, Web of Science, Google Scholar, and others. Some potential biomarkers that provide essential information include circulating tumor cells (CTCs), DNA methylation, claudin 18.2, fibroblast growth factor receptor 2 (FGFR2), long noncoding RNAs (lncRNAs), cell-free DNA (cfDNA), microRNAs, and serum pepsinogens. Multiple tumor markers are essential for screening, tumor identification, staging, prognostic assessment, and monitoring recurrence after therapy due to the absence of a single tumor indicator for diagnosing, prognosticating, and predicting GC.

Evaluation of miRNA 130a-3P and miRNA 301a-3P in Egyptian patients with urinary bladder carcinoma

ObjectivesTo study the role of microRNA 130a-3p and microRNA 301a-3p in urinary bladder carcinoma. BackgroundDespite the discovery of several clinical and molecular indicators for predicting outcomes in bladder cancer, it is unclear how to use these indicators in clinical practice. A recent study revealed that the miR-130 family may play a vital role in the occurrence and development of BC by regulating signal pathways through various target genes. We intend to apply them as novel, nonintrusive, and easily detectable bladder cancer indicators. Subjects and methodsThe current study involved one hundred subjects. Fifty subjects had bladder cancer diagnosed by cystoscope biopsy and histopathological examination, and the other fifty were age- and gender-matched healthy adults serving as a control group. All participants were subjected to complete history taking through medical examination and estimation of expression levels of plasma miRNA 130a-3p by reverse transcriptase – polymerase chain reaction (RT-PCR) through quantitative real-time technique. ResultsmiRNA 130a-3p and miRNA 301a-3p were expressed at higher levels in the plasma of bladder cancer patients than in the controls. The points for the diagnostic capacities of miR 130a-3p and miR 301a-3p for bladder cancer were > 0.921 and > 1.32, respectively, indicating that they are potential clinical diagnostic biomarkers for bladder cancer with good sensitivity and specificity. Moreover, stage IIIA versus stage IIIB can be discriminated as >0.96 (miR 130a-3p) and > 2.48 (miR 301a-3p), which can be utilized for estimating the clinical prognosis of bladder cancer. ConclusionmiRNA 130a-3p and miRNA 301a-3p expression levels in plasma can differentiate bladder cancer patients from healthy controls and discriminate between stage IIIA and stage IIIB. This finding may facilitate the clinical diagnosis of bladder cancer.

The EFNA4 gene is a potential prognostic biomarker in pancreatic cancer: a bioinformatics analysis.

Pancreatic cancer is a highly aggressive malignancy with poor prognosis, and there is an urgent need to understand its molecular mechanisms for early diagnosis and treatment. Despite surgical resection being the only effective treatment, most patients are diagnosed at an advanced stage, missing the optimal window for therapy. Identifying novel biomarkers is crucial for prognostic assessment, treatment planning, and early intervention. Ephrin A4 (EFNA4), a member of the receptor tyrosine kinase family, is involved in vascular and epithelial development via regulation of cell migration and rejection. However, the role of EFNA4 in pancreatic cancer has not been reported. Therefore, our study aimed to clarify the role of EFNA4 in pancreatic cancer through bioinformatics analysis and vitro experiments. The expression of EFNA4 and its potential value as a diagnostic and prognostic biomarker in pancreatic cancer was analyzed using data from The Cancer Genome Atlas (TCGA) and the Gene Expression Profiling Interactive Analysis (GEPIA) database. According to the expression level of EFNA4, patients were divided into high expression group and low expression group, and the correlation between overall survival (OS) and disease-free survival (DFS) with different expression levels of EFNA4 and clinical parameters were analyzed. Subsequently, reverse-transcription quantitative polymerase chain reaction (RT-qPCR) was performed to detect EFNA4 expression. The proliferation, invasion, and cloning ability of the cells were detected via Cell Counting Kit 8 (CCK8), Transwell, and plate cloning assays, respectively. EFNA4 is highly expressed in pancreatic cancer, and upregulation of EFNA4 is associated with poor prognosis. In this study, EFNA4 expression was correlated with T stage and TNM (tumor-node-metastasis) stage of pancreatic cancer, and the median survival time and progression-free survival (PFS) were worse in those with high EFNA4 expression (394 days) than in those with low expression (525 days) [hazard ratio (HR): 1.47, 95% confidence interval (CI): 1.00-2.16, P=0.047]. In addition, EFNA4 was also found to be involved in the regulation of signal pathways such as cell adhesion, cyclic AMP, insulin secretion, pancreatic secretion, and protein digestion and absorption. In vitro experiments demonstrated that EFNA4 knockdown significantly inhibited the proliferation, cloning ability, and invasiveness of the PANC-1 and SW1990 pancreatic cancer cell lines. The abnormal expression of EFNA4 in pancreatic cancer is associated with poor prognosis. Knockout of EFNA4 gene could significantly inhibit the proliferation and invasion of pancreatic cancer cells. Therefore, EFNA4 may be one of the molecular targets for poor prognosis of patients with pancreatic cancer.

Investigating the Association between LncRNA NR2F2-AS1, miR-320b, and BMI1 in Gastric Cancer: Insights into Expression Profiles as Potential Biomarkers for Disease Management.

This study aims to investigate the potential role of lncRNA NR2F2-AS1 in the development of gastric cancer by affecting the levels of miR-320b and BMI1. Gastric cancer is a high-mortality malignancy, and understanding the underlying molecular mechanisms is crucial. Non-coding RNAs play an important role in gene expression, and their dysregulation can lead to tumor initiation and progression. This study aims to determine the pathological role of LncRNA NR2F2-AS1 in gastric cancer progression and its association with the clinicopathological characteristics of patients. Bioinformatics databases were used to predict the expression levels and interactions between the studied factors to achieve this objective. The expression pattern of NR2F2-AS1/miR- 320b/BMI1 in 40 pairs of tumor and adjacent normal tissues was examined using RT-PCR, IHC, and western blot. The correlation, ROC curve, and survival analyses were also conducted for the aforementioned factors. The results showed an increase of more than 2-fold for BMI-1 and lncRNA NR2F2-AS1 in lower stages, and the elevation continued with the increasing stage of the disease. This correlated with significant downregulation of miR-320b and PTEN, indicating their association with gastric cancer progression and decreased patient survival. LncRNA NR2F2-AS1 acts as an oncogene by influencing the level of miR-320b, altering the amount of BMI1. A reduction in the amount of miR-320b against lncRNA NR2F2-AS1 and BMI1 directly correlates with a reduced overall survival rate of patients, especially if this disproportion is more than 3.0. ROC curve analysis indicated that alteration in the lncRNA NR2F2-AS1 level showed more than 98.0% sensitivity and specificity to differentiate the lower from higher stages of GC and predict the early onset of metastasis. In conclusion, these results suggest that NR2F2-AS1/miR-320b/BMI1 has the potential to be a prognostic as well as diagnostic biomarker for gastric cancer.