Potential Cancer Biomarkers Research Articles

Identification of fibrosis-associated biomarkers in heart failure and human cancers

BackgroundHeart failure (HF) and cancer share common risk factors and pathophysiological mechanisms, including fibrosis. Identifying biomarkers and therapeutic targets for both conditions is crucial.Materials and methodsRNA sequencing data from HF patients were analyzed to identify 12 genes associated with myocardial fibrosis. Validation was performed using public datasets, and functional enrichment analyses were conducted. Gene expression patterns and prognostic value in various cancers were assessed.ResultsFibromodulin (FMOD), Periostin (POSTN), Latent Transforming Growth Factor Beta Binding Protein 2 (LTBP2), Collagen Type I Alpha 1 Chain (COL1A1), Collagen Type VIII Alpha 1 Chain (COL8A1), Asporin (ASPN), and Hemoglobin Subunit Beta (HBB) showed significant dysregulation in heart failure tissues and were implicated in multiple cancer types. Pan-cancer analysis revealed associations between these genes and prognosis. Correlations with cancer-associated fibroblasts were also observed.ConclusionFMOD, POSTN, LTBP2, COL1A1, COL8A1, ASPN, and HBB are potential biomarkers for HF and cancer with fibrotic microenvironments. Targeting fibrosis may offer novel therapeutic approaches. Further validation and mechanistic studies are needed. This study contributes to understanding HF and cancer at the molecular level and suggests personalized treatment strategies.

Maleylpyruvic Acid-Inducible Gene Expression System and Its Application for the Development of Gentisic Acid Biosensors.

Gentisic acid is a secondary plant metabolite, known for its health benefits, not only widely used as a supplement but also implicated as a potential biomarker for cancer-associated metabolism alterations. To advance bioproduction and detection of this compound or its derivatives, cell-based approaches have become of interest in recent years. However, the lack of tools for high-throughput gentisic acid monitoring and compound-metabolizing organism screening limits the progress in this area. Here, we analyzed the gene cluster responsible for gentisic acid metabolism in Cupriavidus necator H16. The transcriptional regulator GtdR-based inducible gene expression system CnGtdR/PgtdA was elucidated, showing that it was activated when C. necator cells were subjected to gentisic acid. Subsequently, a 3-maleylpyruvic acid was identified as a primary inducer for this inducible system. Furthermore, genes gtdA and gtdT, encoding for gentisate 1,2-dioxygenase and MFS transporter, were shown to be essential for inducible system activation in the presence of gentisic acid with GtdA enabling conversion of this phenolic acid into the inducer. The CnGtdRAT/PgtdA-based inducible system was employed to develop a whole-cell biosensor for the intracellular and extracellular detection of gentisic acid. The potential of the 3-maleylpyruvic acid-inducible system was demonstrated by its application in metabolic pathway research, detection of highly unstable 3-maleylpyruvic acid, and development of biosensors for the intracellular or extracellular determination of gentisic acid. In addition, the utility of the biosensor was emphasized by its application for detection of gentisic acid as a potential biomarker for cancer in urine samples.

TMEM158, as plasma cfRNA marker, promotes proliferation and doxorubicin resistance in ovarian cancer.

The current study aimed to identify the potential biomarker for the diagnosis of ovarian cancer within plasma cell-free RNA (cfRNA) species and to characterize their oncogenic properties. cfRNAs were isolated from the peripheral blood of ovarian cancer patients and sequenced using an NGS platform. Principal component analysis (PCA) was performed using Salmon software. Gene ontology (GO) analysis was conducted with clusterProfiler. The relative abundance of TMEM158 transcripts was determined by real-time PCR. Cell viability and proliferation was monitored using the MTT and cell counting assays, respectively. The protein levels of TMEM158 and ABCG2 were quantified by immunoblotting. We observed a clear separation of cfRNAs between ovarian cancer patients and healthy individuals. Additionally, we identified TMEM158 as the most significantly differential gene in both peripheral blood and tumor tissues. Overexpression of TMEM158 stimulated cell viability and promoted cell proliferation in ovarian cancer cells. Notably, the aberrant upregulation of TMEM158 was closely associated with doxorubicin resistance in ovarian cancer. Mechanistically, we demonstrated that TMEM158 positively regulates ABCG2 expression, which consequently contributes to drug resistance. In summary, we identified cfRNA TMEM158 as a potential diagnostic biomarker for ovarian cancer and elucidated the critical involvement of TMEM158-ABCG2 signaling axis in the development of doxorubicin resistance.

Comprehensive analysis of the metabolomics and transcriptomics uncovers the dysregulated network and potential biomarkers of Triple Negative Breast Cancer

Triple-negative breast cancer (TNBC) is known for its aggressive nature, lack of effective diagnostic tools and treatments, and generally poor prognosis. The objective of this study was to investigate metabolic changes in TNBC using metabolomics approaches and explore the underlying mechanisms through integrated analysis with transcriptomics. In this study, serum untargeted metabolic profiles were first examined between 18 TNBC patients and 21 healthy control (HC) subjects using liquid chromatography-mass spectrometry (LC-MS), identifying a total of 22 significantly differential metabolites (DMs). Subsequently, receiver operating characteristic analysis revealed that 7-methylguanine could serve as a potential biomarker for TNBC in both the discovery and validation sets. Additionally, transcriptomic datasets were retrieved from the GEO database to identify differentially expressed genes (DEGs) between TNBC and normal tissues. An integrative analysis of the DMs and DEGs was conducted, uncovering potential molecular mechanisms underlying TNBC. Notably, three pathways—tyrosine metabolism, phenylalanine metabolism, and glycolysis/gluconeogenesis—were enriched, providing insight into the energy metabolism disorders in TNBC. Within these pathways, two DMs (4-hydroxyphenylacetaldehyde and oxaloacetic acid) and six DEGs (MAOA, ADH1B, ADH1C, AOC3, TAT, and PCK1) were identified as key components. In summary, this study highlights metabolic biomarkers that could potentially be used for the diagnosis and screening of TNBC. The comprehensive analysis of metabolomics and transcriptomics data offers a validated and in-depth understanding of TNBC metabolism.

Circulating tumor HPV DNA as a specific biomarker for cervical cancer.

The aim of this study was to determine whether circulating tumor human papillomavirus (HPV) DNA is a potential specific biomarker for cervical cancer (CC). This retrospective matched study included 87 patients with cervical intraepithelial neoplasia (CIN), 29 CC patients (FIGO IA1-IVA) and 29 HPV-negative controls at Yuhuangding Hospital of Qingdao University (from July 2022 to September 2023). The digital droplet PCR (ddPCR) was used to detect and quantify ctHPV DNA in the plasma of patients with HPV16, 18, 33, 52, or 58-associated CC. The ctHPV DNA was exclusively detectable in HPV-positive samples, with no detection in patients across various CIN stages (n = 87) or HPV-negative controls (n = 29). Additionally, ctHPV DNA was identified in nine out of 10 late-stage patients (90%) and six out of 19 early-stage patients (31.6%). The ctHPV DNA serves as a specific biomarker for the diagnosis CC. Additionally, this discovery addresses the knowledge gap in ctHPV DNA research in the early stages of CC and promotes clinical diagnosis and treatment strategies.

Development of oxidative stress- and ferroptosis-related prognostic signature in gastric cancer and identification of CDH19 as a novel biomarker

BackgroundFerroptosis is a unique mode of cell death that is iron-dependent and associated with oxidative stress and lipid peroxidation. Oxidative stress and ferroptosis are essential mechanisms leading to metabolic abnormalities in cells and have been popular areas in cancer research.MethodsInitially, 76 oxidative stress and ferroptosis-related genes (OFRGs) were acquired by intersecting the gene sets from oxidative stress and ferroptosis. Afterwards, optimal OFRGs were screened using PPI networks, and individuals were separated into two OFRG subtypes (K = 2). Subsequently, we successfully constructed and verified a prognostic signature comprising SLC7A2, Cadherin 19 (CDH19), and CCN1. To further uncover potential biomarkers of gastric cancer (GC), we examined the expression level of CDH19, investigated the effects of knocking down CDH19 on the biological behavior of GC cells, and explored whether CDH19 is involved in ferroptosis and oxidative stress processes.ResultsAccording to the findings, individuals in the low-risk scoring group have less infiltration of immune suppressive cells, fewer occurrences of immune escape and dysfunction, greater efficacy in chemotherapy and immunotherapy, and better survival outcomes. The qRT-PCR assay indicated that CDH19 expression was significantly higher in GC cells. Through experiments, we demonstrated that knocking down CDH19 can affect the transcription levels of ACSL4 and GPX4, increase intracellular iron ion concentration and accumulation of reactive oxygen species (ROS), and inhibit the proliferation and migration of GC cells.ConclusionWe developed an OFRG-related signature to predict the prognosis and treatment responsiveness of individuals with GC and identified CDH19 as a possible therapeutic target for GC.

Untargeted metabolomic profiling of small extracellular vesicles reveals potential new biomarkers for triple negative breast cancer.

Breast Cancer (BC) is one of the most diagnosed malignancies among women and the second leading cause of cancer related death in North America. Triple Negative BC (TNBC), one of the most severe subtypes of BC, is extremely aggressive and has a higher chance of occurrence in women under 50 years of age. Due to a lack of regular mammographic testing in women under 50, many individuals with TNBC are diagnosed late which can decrease their survival rate. Currently, liquid biopsy is being investigated as a potentially less-invasive alternative to traditional breast tissue biopsy, but this approach is not completely reliable. Blood contains extracellular vesicles (EVs), which carry biomolecular cargo and play a role in BC progression and metastasis. Examination of small EVs could potentially yield metabolite biomarkers for early BC diagnosis. We aim to study metabolites in small EVs to find biomarkers for BC diagnosis. In this work, an untargeted nano-LC MS/MS metabolomics approach was used to analyze metabolites from small EVs derived from metastatic MDA-MB-231 and compare it with a non-cancerous MCF10A cell line. Two metabolites, LysoPC 22:6/0:0 and N-acetyl-L-Phenylalanine, unique to sEVs of MDA-MB-231, were identified, validated, and proposed as potential BC biomarkers. Metabolites from sEVs may be used for BC diagnosis.

Comprehensive Analysis and Experimental Validation of HEPACAM2 as a Potential Prognosis Biomarker and Immunotherapy Target in Colorectal Cancer.

The role of HEPACAM family member 2 (HEPACAM2) is unclear in colorectal cancer (CRC). The objective of this study was to perform an extensive examination of HEPACAM2 and validate it experimentally in CRC. This study investigated the significance of HEPACAM2 in CRC and its potential diagnostic utility utilizing data from the Cancer Genome Atlas (TCGA) database. Additionally, the study examined potential regulatory networks involving HEPACAM2, including its associations with immune infiltration, immune checkpoint genes, tumor mutational burden (TMB), microsatellite instability (MSI), mRNA expression-based stemness index (mRNAsi), and drug sensitivity in CRC. The expression of HEPACAM2 was further validated using the GSE89076 dataset, and quantitative reverse transcription PCR (qRT-PCR) was employed to confirm HEPACAM2 expression levels in six pairs of CRC tissue samples. HEPACAM2 exhibited abnormal expression patterns in various types of cancer, including CRC. A decrease in HEPACAM2 expression levels in CRC was found to be significantly correlated with the T stage (p < 0.001). Reduced HEPACAM2 expression in CRC patients was also linked to poorer overall survival (OS) (p = 0.007). The expression levels of HEPACAM2 in CRC patients were identified as an independent prognostic factor (p = 0.016). Furthermore, HEPACAM2 was associated with TCF-dependent signaling in response to WNT, G2/M checkpoints, and other pathways. The expression of HEPACAM2 in CRC was found to be associated with immune infiltration, immune checkpoint genes, TMB / MSI, and mRNAsi. Additionally, the expression of HEPACAM2 in CRC was significantly and inversely correlated with the drug sensitivities to gw772405x and 6-phenyl-6h-indeno[1,2-c]isoquinoline-5,11-dione. qRT-PCR confirmed that the expression level of HEPACAM2 was found to be lowly expressed in CRC tissues. These findings suggest that HEPACAM2 may serve as a potential prognostic biomarker and immunotherapeutic target for CRC patients.

Bioinformatics investigation of the prognostic value and mechanistic role of CD9 in glioma

In recent years, CD9 has been extensively studied as a potential biomarker for cancer. However, the biological role of CD9 in gliomas remains unclear. This study investigates the function of CD9 in gliomas and its molecular mechanisms. Utilizing pan-cancer analysis with TCGA, CGGA, and GEO databases, differential expression of CD9 was observed in 11 tumor types within the TCGA cohort, and it was associated with patient survival rates. Analysis of the CGGA glioma database revealed that patients with high CD9 expression had lower survival rates. The area under the ROC curve (AUC) for GSE16011 was greater than 0.7, indicating a high discriminative ability. Through gene set enrichment analysis (GSEA), immune-related analysis, and CD9 mutation detection, CD9 was found to have the strongest correlation with neutrophil involvement (cor = 0.30, P < 0.05), and the high CD9 expression group exhibited higher rejection responses and TIDE scores, suggesting a lower likelihood of successful immunotherapy. The high CD9 expression group was more sensitive to 81 drugs, indicating potential therapeutic effects for gliomas. Furthermore, overexpression of CD9 in gliomas may be associated with gene mutations. Down-regulation or up-regulation of CD9 expression in the glioblastoma cell line LN229 showed that CD9 could positively regulate the migratory ability of LN229 cells. Further, several marker genes, such as VEGFR-2, TGF-β1, CASP1 and PI3K, were down regulated in CD9 knockdown cell lines and up regulated in CD9 overexpression cell lines, compared with control cell line. This study preliminarily explores the role of CD9 in gliomas and its prognostic value, providing new insights for personalized treatment strategies in glioma therapy.

Some Glycoproteins Expressed on the Surface of Immune Cells and Cytokine Plasma Levels Can Be Used as Potential Biomarkers in Patients with Colorectal Cancer

Colorectal cancer (CRC) is a leading cause of mortality worldwide. Its incidence holds a major position among the most common life-threatening diseases. Hence, the early identification and precise characterization of disease activity based on proper biomarkers are of utmost importance for therapeutic strategy and patient survival. The identification of new biomarkers for colorectal cancer or disease-specific levels/combinations of biomarkers will significantly contribute to precise diagnosis and improved personalized treatment of patients. Therefore, the present study aims to identify colorectal cancer-specific immunological biomarkers. The plasma levels of several cytokines (interleukin-1β /IL-1β/, IL-2, IL-4, IL-10, IL-12, IL-15, TGFβ and IFNγ) of 20 patients with colorectal cancer and 21 healthy individuals were determined by ELISA. The expression of several types of glycoproteins on the surface of peripheral blood leukocytes isolated from CRC patients and healthy volunteers was evaluated by flow cytometry. Correlations between cytokine levels and cell surface glycoprotein expression were analyzed. The obtained results demonstrated significantly elevated levels of CD80, CD86, CD279 and CD274 expressing leukocyte populations in the cancer patient group, while the numbers of NK cells and CD8- and CD25-positive cells were decreased. Based on these data and the correlations with cytokine levels, it can be concluded that CD25, CD80, CD86, CD274 and CD279 glycoproteins combined with specific plasma levels of IL-1β, IL-2, IL-15 and TGFβ could represent potential biomarkers for colorectal cancer.

How a mixture of microRNA-29a (miR-29a) and microRNA-144 (miR-144) cancer biomarkers interacts with a graphene quantum dot

MicroRNAs (miRNAs) which are small non-coding RNAs have been reported to be potential cancer biomarker. However, it is difficult to extract such short RNA from a sample matrix. New effective strategies are required. Recently, graphene quantum dots (GQDs) have been used to detect nucleotides in many biosensor platforms, but their applications for miRNA extraction remain limited. GQD was reported to be able to collect short miRNA, but its performance to collect miRNAs with different structure remains unknown. Thus, in this work, the capability of GQD to interact with two different miRNAs is investigated. A mixture of hairpin-like miR-29a and circular miR-144 molecules are used as a representative of two miRNA morphologies. Two systems (a miRNA mixture, comprising 4 of miR-29a and 4 of miR-144, with (miR_GQD) and without GQD (miR)) were studied in comparison. MiRNAs in a mixture (miR) can aggregate, but no permanent miRNA assembly is captured. In contrast, the presence of GQD can rapidly and spontaneously activate the permanent miRNA/GQD clustering. This finding highlights the ability of GQD to be a miRNA collector. Interestingly, all GQD-bound miRNAs do not unfold. This allows the easy accessibility for probes. Also, nano-sized GQD seems to prefer hairpin miR-29a. The free 5’ terminus of miR-29a acts as the sticky end to adhere on GQD. This work highlights the importance of RNA secondary structure on GQD/miRNA aggregation capability. An insight obtained here will be useful for further design of miRNA isolation strategies.

Acetylation of Histone H3 in Cancer Progression and Prognosis.

Cancer is a multifactorial disease resulting from both genetic factors and epigenetic changes. Histone acetylation, a post-translational modification, which alters chromatin architecture and regulates gene expression is associated with cancer initiation, development and progression. Aberrations in global histone acetylation levels are observed in various cancer cells and are also associated with patients' tumor aggressiveness. Therefore, histone acetylation may have prognostic utility and serve as a potential biomarker of cancer progression and patients' prognosis. The reversible modification of histones by an acetyl group is versatile. One particular histone can be acetylated on different lysine residues, subsequently resulting in different biological outcomes. Here, we discuss recent findings on the acetylation of the highly conserved histone protein H3 in the context of cancer biology. Specifically, we review the acetylation of particular H3 residues in various cancer types. We further highlight the significance of H3 acetylation levels as a potential cancer biomarker with prognostic implications.

Single-cell sequencing analysis revealed that NEAT1 was a potential biomarker and therapeutic target of prostate cancer.

Prostate cancer (PCa) usually manifests atypical symptoms in the early stage, and once symptoms appear, most PCa patients have developed to the advanced stage, failing to undergo radical surgery. In this study, PCa occurrence-related biomarkers were explored based on single-cell RNA sequencing (scRNA-seq) data. scRNA-seq data of prostate normal (Normal), benign prostatic hyperplasia (BPH), and PCa (Tumor) samples were acquired from the Gene Expression Omnibus (GEO). Cellular subsets associated with PCa occurrence were obtained using cell annotation. Additionally, the mRNA expression of nuclear enriched abundant transcript 1 (NEAT1) was detected by quantitative real-time PCR (qRT-PCR). The effects of NEAT1 on cell proliferation and apoptosis were analyzed by 5-ethynyl-2-deoxyuridine (EdU) and flow cytometry. Subsequently, cell-derived xenograft (CDX) models were constructed and divided into the LV-NC and LV-shNEAT1 groups. After the tumor tissues of CDX model mice in each group were extracted, the cell growth and Ki67 expression were observed separately using hematoxylin-eosin (H&E) staining and immunohistochemistry (IHC). Ten cellular subsets were obtained via cell annotation, and significantly differential changes were observed between Basal intermediate and Luminal during the course of BPH to PCa. NEAT1-Luminal was highly recruited in the Tumor group with low stemness and high malignancy scores. Matrix metallopeptidase 7 (MMP7)- keratin 17 (KRT17)-Basal intermediate had high ratios in the Tumor group with low stemness and high malignancy scores. The results of pseudotime analysis revealed that NEAT1-Luminal in the Tumor group were consistently distributed with tumor stage cells. In vitro assays showed that NEAT1 expression was elevated in PCa cells, and NEAT1 knockdown could inhibit cell proliferation and induce apoptosis. CDX assays indicated that silencing NEAT1 could reduce the growth rate of PCa tumor volume in CDX model mice. H&E staining results showed that nuclei of tumor cells were reduced and exhibited lighter color in the LV-shNEAT1 group compared with the LV-NC group. IHC results showed that Ki67 positivity was significantly lower in the LV-shNEAT1 group than in the LV-NC group. NEAT1 expression is increased in PCa, and NEAT1 can be a potential biomarker and therapeutic target for PCa.

Telomere Length and Telomerase Activity as Potential Biomarkers for Gastrointestinal Cancer.

Gastrointestinal (GI) cancers, such as colorectal and gastric cancers, pose significant global health challenges due to their high rates of incidence and mortality. Even with advancements in treatment and early detection, many patients still face poor outcomes, highlighting the critical need for new biomarkers and therapeutic targets. Telomere length (TL) and telomerase activity (TA) have gained attention in this context. Telomeres, protective nucleotide sequences at chromosome ends, shorten with each cell division, leading to cellular aging. Telomerase, a ribonucleoprotein enzyme, counteracts this shortening by adding telomeric repeats, a process tightly regulated in normal cells but often dysregulated in cancer. This review critically evaluates the role of TL and TA in the pathogenesis of GI cancers, examining their potential as diagnostic, prognostic, and predictive biomarkers. It explores how alterations in telomere biology contribute to the initiation and progression of GI tumors and assesses the therapeutic implications of targeting telomerase. By integrating findings from diverse studies, this review aims to elucidate the intricate relationship between telomere dynamics and gastrointestinal carcinogenesis, offering insights into how TL and TA could be leveraged to enhance the early detection, treatment, and prognosis of GI cancers.

NCLN as a potential prognosis biomarker in endometrial cancer

Endometrial cancer (ECs) stands as one of the three major malignancies impacting females globally, with its incidence steadily increasing. ECs can be categorized into two types based on their clinicopathological features. Type I ECs typically exhibit low stage, favorable histological types, and low histological grade, correlating with a more favorable prognosis. Conversely, Type II ECs present with advanced-stage disease, aggressive behavior, and poorer histological types, resulting in a worse prognosis.The expression level of progesterone receptors (PR) holds significant importance in determining the prognosis of patients with ECs. Elevated levels of PR are linked to a more favorable prognosis, primarily attributed to progesterone's inhibitory influence on cancer cell proliferation and invasion. Moreover, progesterone promotes cell cycle inhibition through its regulation of PR, further contributing to improved outcomes in ECs.Nicalin (NCLN) plays a crucial role in facilitating the translocation of multichannel membrane proteins to the endoplasmic reticulum membrane and is implicated in embryonic development. Structurally akin to NODAL Modulator (NOMO), NCLN antagonizes NOMO during embryogenesis, forming a complex that antagonizes the Nodal pathway, thereby influencing mesoderm development. However, the precise relationship between NCLN and ECs remains incompletely understood.Our research findings reveal that NCLN actively stimulates the proliferation of ECs cells and exhibits a positive correlation with PR, albeit without impacting ER. Moreover, the expression levels of NCLN in ECs demonstrate associations with distinct histological types. These observations suggest that NCLN could emerge as a promising marker in the histological classification of ECs.

Meta-analysis of FTO expression on the clinicopathologic characteristics and prognosis of gastric cancer.

Fat mass and obesity-related gene (FTO) is aberrantly expressed in various cancers including highly expressed in gastric cancer tissues. The aim of this meta-analysis was to explore the effect of FTO expression on clinicopathological and prognostic outcome of gastric cancer. China National Knowledge Infrastructure (CNK), Wanfang database, VIP database, Chinese biomedical literature database (CBM), PubMed, Web of Science, the Cochrane library and EMBASE database were searched to screen the literatures according to the inclusion criteria. The search time was the database establishment until May 2023. The two researchers independently searched and screened the literature, extracted pathological data, and conducted The Newcastle-Ottawa scale (NOS) quality evaluation. Analyze the correlation between FTO and pathological indicators of gastric cancer patients and the impact on prognosis, use and Stata 12.0, software for Meta-analysis. A total of 1619 patients were studied in this study. The results of the Meta-analysis showed that higher expression levels of FTO were associated with TMN stage (OR = 1.83, 95% CI: 1.11-3.03, P = .019), liver metastases (OR = 3.73, 95% CI: 1.49-9.31, P = .005), vascular invasion (OR = 2.22, 95% CI: 1.36-3.61, P = .001), poorer overall survival (OS) (HR = 0.46, 95% CI: 0.34-0.58, P < .001) and recurrence-free survival (HR = 0.56, 95% CI: 0.40-0.73, P < .001) in gastric cancer patients. There was no significant relationship with the degree of differentiation (OR = 1.08, 95% CI: 0.49-2.35, P = .852), age (OR = 0.89, 95% CI: 0.71-1.11, P = .306), and gender (OR = 0.92, 95% CI: 0.74-1.14, P = .432). High expression of FTO was associated with risk of distant metastases and poor prognosis for patients with gastric cancer. FTO may be a potential prognostic biomarker for gastric cancer, but due to the limited number of literature, the above results need further research.

Multi-view learning framework for predicting unknown types of cancer markers via directed graph neural networks fitting regulatory networks.

The discovery of diagnostic and therapeutic biomarkers for complex diseases, especially cancer, has always been a central and long-term challenge in molecular association prediction research, offering promising avenues for advancing the understanding of complex diseases. To this end, researchers have developed various network-based prediction techniques targeting specific molecular associations. However, limitations imposed by reductionism and network representation learning have led existing studies to narrowly focus on high prediction efficiency within single association type, thereby glossing over the discovery of unknown types of associations. Additionally, effectively utilizing network structure to fit the interaction properties of regulatory networks and combining specific case biomarker validations remains an unresolved issue in cancer biomarker prediction methods. To overcome these limitations, we propose a multi-view learning framework, CeRVE, based on directed graph neural networks (DGNN) for predicting unknown type cancer biomarkers. CeRVE effectively extracts and integrates subgraph information through multi-view feature learning. Subsequently, CeRVE utilizes DGNN to simulate the entire regulatory network, propagating node attribute features and extracting various interaction relationships between molecules. Furthermore, CeRVE constructed a comparative analysis matrix of three cancers and adjacent normal tissues through The Cancer Genome Atlas and identified multiple types of potential cancer biomarkers through differential expression analysis of mRNA, microRNA, and long noncoding RNA. Computational testing of multiple types of biomarkers for 72 cancers demonstrates that CeRVE exhibits superior performance in cancer biomarker prediction, providing a powerful tool and insightful approach for AI-assisted disease biomarker discovery.

A multichannel graph neural network based on multisimilarity modality hypergraph contrastive learning for predicting unknown types of cancer biomarkers.

Identifying potential cancer biomarkers is a key task in biomedical research, providing a promising avenue for the diagnosis and treatment of human tumors and cancers. In recent years, several machine learning-based RNA-disease association prediction techniques have emerged. However, they primarily focus on modeling relationships of a single type, overlooking the importance of gaining insights into molecular behaviors from a complete regulatory network perspective and discovering biomarkers of unknown types. Furthermore, effectively handling local and global topological structural information of nodes in biological molecular regulatory graphs remains a challenge to improving biomarker prediction performance. To address these limitations, we propose a multichannel graph neural network based on multisimilarity modality hypergraph contrastive learning (MML-MGNN) for predicting unknown types of cancer biomarkers. MML-MGNN leverages multisimilarity modality hypergraph contrastive learning to delve into local associations in the regulatory network, learning diverse insights into the topological structures of multiple types of similarities, and then globally modeling the multisimilarity modalities through a multichannel graph autoencoder. By combining representations obtained from local-level associations and global-level regulatory graphs, MML-MGNN can acquire molecular feature descriptors benefiting from multitype association properties and the complete regulatory network. Experimental results on predicting three different types of cancer biomarkers demonstrate the outstanding performance of MML-MGNN. Furthermore, a case study on gastric cancer underscores the outstanding ability of MML-MGNN to gain deeper insights into molecular mechanisms in regulatory networks and prominent potential in cancer biomarker prediction.

Dysbiosis in Human Urinary Microbiota May Differentiate Patients with a Bladder Cancer.

Recent interest in noninvasive diagnostic approaches has highlighted the potential of urinary microbiota as a novel biomarker for bladder cancer. This study investigated the urinary microbiota of 30 bladder cancer patients and 32 healthy controls using a specific NGS protocol that sequences eight hypervariable regions of the 16S rRNA gene, providing detailed insights into urinary microbiota composition. The relative abundance of microbial compositions in urine samples from cancer patients and healthy controls was analyzed across various taxonomic levels. No notable differences were highlighted at the phylum, class, order, and family levels. At the genus level, 53% of detected genera were represented in either cancer patients or healthy controls. Microbial diversity was significantly lower in cancer patients. The differential analysis identified five genera, Rhodanobacter, Cutibacterium, Alloscardovia, Moryella, and Anaeroglobus, that were significantly more abundant in cancer patients. Notably, Rhodanobacter was present in 20 cancer samples but absent in healthy controls. Conversely, 40 genera, including Lactobacillus, Propionibacterium, and Bifidobacterium, exhibited reduced abundance in cancer patients. These findings suggest that some genera may serve as potential biomarkers for bladder cancer, highlighting the need for further research to explore their roles in disease pathogenesis and their potential applications in diagnostics and therapeutics.

The aryl hydrocarbon receptor in environmentally induced cervical cancer: A Narrative review

The aryl hydrocarbon receptor (AhR) plays a crucial role in cellular responses to various environmental pollutants, including several known carcinogens. As a ligand-activated transcription factor, AhR activation modulates the expression of genes involved in critical cellular processes, including detoxification pathways, cell proliferation and differentiation, and immune system regulation. The AhR exhibits pleiotropic effects under normal physiological conditions, contributing to the development and function of various organ systems. AhR activity is important in angiogenesis, cardiomyocyte differentiation, oocyte maturation, oculomotor nerve formation, and hematopoietic stem cell maintenance. Additionally, AhR plays a role in regulating immune cell differentiation and function, maintaining the integrity of the intestinal epithelium and its associated immune system, and mediating UVB-induced DNA damage repair responses in the skin. It acts as a critical environmental sensor, mediating cellular responses to various exogenous ligands. Importantly, activation or inhibition of AhR affects distinct signaling pathways depending on the specific ligand and cellular context. Ligands for the AhR are divided into exogenous or endogenous and have agonistic or antagonistic activity. Recently, the AhR role was determined in cancer development. It can exert both tumor-promoting and tumor-suppressive effects depending on factors such as the specific ligand, cell type, and tissue microenvironment. Emerging evidence suggests that AhR may represent a promising target for immunotherapy and serve as a potential biomarker for cervical cancer. AhR interacts with apoptotic pathway, immune checkpoint system, steroid hormones, and immune cell regulation process in cervical cancer. Despite its potential significance, the precise role of AhR in cervical cancer development and progression is still unknown. In this review, we describe significant roles of AhR in gynecological cancers; e.g., in cervical cancer.