Biomarkers For Detection Of Cancer Research Articles

Metabolomics: A Tool to Envisage Biomarkers in Clinical Interpretation of Cancer.

Cancer is amongst the most dreadful ailments of modern times, and its impact continuously worsens global health systems. Early diagnosis and suitable therapeutic agents are the prime keys to managing this disease. Metabolomics deals with the complete profiling of cells and physiological phenomena in their organelles, thus helping in keen knowledge of the pathological status of the disease. It has been proven to be one of the best strategies in the early screening of cancer. This review has covered the recent updates on the promising role of metabolomics in the identification of significant biochemical markers in cancer-prone individuals that could lead to the identification of cancer in the early stages. The literature was collected through various databases, like Scopus, PubMed, and Google Scholar, with stress laid on the last ten years' publications. It was assessed in this review that early recognition of cancerous growth could be achieved via complete metabolic profiling in association with transcriptomics and proteomics. The outcomes are rooted in various clinical studies that anticipated various biomarkers like tryptophan, phenylalanine, lactates, and different metabolic pathways associated with the Warburg effect. This metabolite imaging has been a fundamental step for the target acquisition, evaluation of predictive cancer biomarkers for early detection, and outlooks into cancer therapy along with critical evaluation. Significant efforts should be made to make this technique most reliable and easy.

Potential of pre-diagnostic metabolomics for colorectal cancer risk assessment or early detection

This systematic review investigates the efficacy of metabolite biomarkers for risk assessment or early detection of colorectal cancer (CRC) and its precursors, focusing on pre-diagnostic biospecimens. Searches in PubMed, Web of Science, and SCOPUS through December 2023 identified relevant prospective studies. Relevant data were extracted, and the risk of bias was assessed with the QUADAS-2 tool. Among the 26 studies included, significant heterogeneity existed for case numbers, metabolite identification, and validation approaches. Thirteen studies evaluated individual metabolites, mainly lipids, while eleven studies derived metabolite panels, and two studies did both. Nine panels were internally validated, resulting in an area under the curve (AUC) ranging from 0.69 to 0.95 for CRC precursors and 0.72 to 1.0 for CRC. External validation was limited to one panel (AUC = 0.72). Metabolite panels and lipid-based biomarkers show promise for CRC risk assessment and early detection but require standardization and extensive validation for clinical use.

Tumor Initiation and Progression in People Living on Antiretroviral Therapies

Antiretroviral therapy (ART) has significantly extended the lifespan of people living with Human Immunodeficiency Virus (HIV) or Acquired Immunodeficiency Syndrome (AIDS), thereby transforming the disease into a manageable chronic condition. However, this increased longevity has led to a higher incidence of non-AIDS-defining cancers (NADCs) among this population. In this holistic review, we explore the complex interactions between HIV, ART, and cancer development, focusing on how ART influences tumor initiation and progression in people living with HIV/AIDS (PLWHA). Our findings from this reveal several critical aspects of cancer risk in PLWHA. Firstly, while ART restores immune function, it does not fully normalize it. Chronic immune activation and persistent inflammation continue to be prevalent, creating a conducive environment for oncogenesis. Additionally, PLWHA are more susceptible to persistent infections with oncogenic viruses such as human papillomavirus (HPV) and Epstein–Barr virus (EBV), further increasing cancer risk. Some ART drugs have been implicated in genotoxicity and mitochondrial dysfunction, potentially promoting tumorigenesis. ART-induced metabolic changes, including insulin resistance and dyslipidemia, are also associated with heightened cancer risk. Common NADCs in PLWHA include lung cancer, liver cancer, anal cancer, and Hodgkin lymphoma, each with distinct etiologies linked to both HIV-related and ART-related factors. The interplay between HIV infection, chronic inflammation, immune restoration via ART, and the direct effects of ART drugs creates a unique cancer risk profile in PLWHA. Although ART reduces the incidence of AIDS-defining cancers, it does not confer the same protective effect against NADCs. Persistent HIV-related inflammation and immune activation, despite viral suppression, are key factors in cancer development. Additionally, long-term exposure to ART may introduce new oncogenic risks. These insights highlight the need for integrated cancer screening and prevention strategies tailored to PLWHA. Future research is needed to focus on identifying biomarkers for early cancer detection and developing ART regimens with lower oncogenic potential. Healthcare providers should be vigilant in monitoring PLWHA for cancer and adopt comprehensive screening protocols to mitigate the increased cancer risk associated with ART.

Optical Biosensors for Detection of Cancer Biomarkers: Current and Future Perspectives.

Optical biosensors are emerging as a promising technique for the sensitive and accurate detection of cancer biomarkers, enabling significant advancements in the field of early diagnosis. This study elaborates on the latest developments in optical biosensors designed for detecting cancer biomarkers, highlighting their vital significance in early cancer diagnosis. When combined with targeted nanoparticles, the bio-fluids can help in the molecular stage diagnosis of cancer. This enhances the discrimination of disease from the normal subjects drastically. The optical sensor methods that are involved in the disease diagnosis and imaging of cancer taken for the present review are surface plasmon resonance, localized surface plasmon resonance, fluorescence resonance energy transfer, surface-enhanced Raman spectroscopy and colorimetric sensing. The article meticulously describes the specific biomarkers and analytes that optical biosensors target. Beyond elucidating the underlying principles and applications, this article furnishes an overview of recent breakthroughs and emerging trends in the field. This encompasses the evolution of innovative nanomaterials and nanostructures designed to augment sensitivity and the incorporation of microfluidics for facilitating point-of-care testing, thereby charting a course towards prospective advancements.

Adenomatous Polyposis Coli (APC) Promoter Gene Methylation in Urine-Derived DNA: A Non-invasive Biomarker for Early Bladder Cancer Detection and Tumor Aggressiveness

Adenomatous Polyposis Coli (APC) Promoter Gene Methylation in Urine-Derived DNA: A Non-invasive Biomarker for Early Bladder Cancer Detection and Tumor Aggressiveness

The Multifaceted Role of miR-23a in Cancer and Disease Progression

Abstract: MicroRNAs (miRNAs) are small, non-coding RNAs that play a crucial role in post-transcriptional gene regulation by modulating mRNA stability and translation. These evolutionarily conserved molecules undergo processing by ribonucleases Drosha and Dicer, ultimately joining the RNA-induced silencing complex to silence gene expression. Among them, miR-23a, located on chromosome 19, is significant for its roles in cell growth, differentiation, and various diseases, including cancer. Depending on the cancer type, miR-23a can function as both an oncogene and a tumour suppressor. While its overexpression often correlates with aggressive tumours, miR-23a holds promise as a biomarker for early cancer detection and a therapeutic target. Its diverse functions in cancer include promoting tumour growth and hindering immune responses, highlighting its potential for personalized medicine. Beyond cancer, miR-23a is involved in blood sugar regulation, insulin resistance, muscle atrophy, and other diseases. It modulates pathways in type 2 diabetes mellitus, muscle atrophy, leukemia, epilepsy, and osteoarthritis. This paper aims to comprehensively analyze the roles of miR-23a in cancer and other diseases, focusing on its regulatory mechanisms, target genes, and pathways. It also evaluates the potential of miR-23a as a biomarker and therapeutic target. Despite its significance, research gaps remain, particularly in understanding the interactions of miR-23a with other miRNAs and the detailed mechanisms underlying its role in various diseases. More research into miR-23a clustering and how it works with other miRNAs could help us learn more about it and find better ways to use it to diagnose and treat diseases.

The Influence of Temperature on the Spatial Distribution of AuNPs on a Ceramic Substrate for Biosensing Applications

In this study, we investigated the spatial distribution and homogeneity of gold nanoparticles (AuNPs) on an alumina (Al2O3; AAO) substrate for potential application as surface-enhanced Raman scattering (SERS) sensors. The AuNPs were synthesized through thermal treatment at 450 °C at varying times (5, 15, 30, and 60 min), and their distribution was characterized using field-emission scanning electron microscopy (FE-SEM) and scanning transmission electron microscopy (STEM). The FE-SEM and STEM analyses revealed that the size and interparticle distance of the AuNPs were significantly influenced by the duration of thermal treatment, with shorter times promoting smaller and more closely spaced nanoparticles, and longer times resulting in larger and more dispersed particles. Raman spectroscopy, using Rhodamine 6G (R6G) as a probe molecule, was employed to evaluate the SERS enhancement provided by the AuNPs on the AAO substrate. Raman mapping (5 µm × 5 µm) was conducted on five sections of each sample, demonstrating improved homogeneity in the SERS effect across the substrate. The topological features of the AuNPs before and after R6G incubation were analyzed using atomic force microscopy (AFM), confirming the correlation between a decrease in surface roughness and an increase in R6G adsorption. The reproducibility of the SERS effect was quantified using the maximum intensity deviation (D), which was found to be below 20% for all samples, indicating good reproducibility. Among the tested conditions, the sample synthesized for 15 min exhibited the most favorable characteristics, with the smallest average nanoparticle size and interparticle distance, as well as the most consistent SERS enhancement. These findings suggest that AuNPs on AAO substrates, particularly those synthesized under the optimized condition of 15 min at 450 °C, are promising candidates for use in SERS-based sensors for detecting cancer biomarkers. This could be attributed to temperature propagation promoted at the time of synthesis. The results also provide insights into the influence of thermal treatment on the spatial distribution of AuNPs and their subsequent impact on SERS performance.

Insight of Employing Molecular Junctions for Sensor Applications.

Molecular junctions (MJs) exhibit distinct charge transport properties and have the potential to become the next generation of electronic devices. Advancing molecular electronics for practical uses, such as sensors, is crucial to propel its progress to the next level. In this review, we discussed how MJs can serve as a sensor for detecting a wide range of analytes with exceptional sensitivity and specificity. The primary advances and potential of molecular junctions for the various kinds of sensors including photosensors, explosives (DNTs, TNTs), cancer biomarker detection (DNA, mRNA), COVID detection, biogases (CO, NO, NH), environmental pH, practical chemicals, and water pollutants are listed and examined here. The fundamental ideas of molecular junction formation as well as the sensing mechanism have been examined here. This review demonstrates that MJ-based sensors hold significant promise for real-time and on-site detection. It provides valuable insights into current research and outlines potential future directions for advancing molecular junction-based sensors for practical applications.

Serum exosomal small nucleolar RNA (snoRNA) signatures as a predictive biomarker for benign and malignant pulmonary nodules

Low-dose CT (LDCT) is increasingly recognized as the preferred method for detecting pulmonary nodules. However, distinguishing whether a nodule is benign or malignant often necessitates repeated scans or invasive tissue sampling procedures. Therefore, there is a pressing need for non-invasive techniques to minimize unnecessary interventions. This study aim to investigate the expression profile of exosomal snoRNA in the serum of patients with benign and malignant pulmonary nodules. We identified a total of 278 snoRNAs in serum exosomes, revealing significant differences in snoRNA levels between patients with malignant and benign nodules. Specifically, the upregulated snoRNAs U78 and U37 were validated through qRT-PCR and were found significantly elevated in the serum of patients with malignant pulmonary nodules, positioning them as promising biomarkers for the early detection of lung cancer. This study underscores the potential of serum exosomal U78 and U37 as critical tools for assessing the risk of pulmonary nodules identified through CT screening.

Numerical Investigation of a Highly Sensitive Plasmonic Refractive Index Sensor for the Detection of Breast and Cervical Cancer Biomarkers

Numerical Investigation of a Highly Sensitive Plasmonic Refractive Index Sensor for the Detection of Breast and Cervical Cancer Biomarkers

Recent advances in surface plasmon resonance for the detection of ovarian cancer biomarkers: a thorough review.

Early detection of ovarian cancer (OC) is crucial for effective management and treatment, as well as reducing mortality rates. However, the current diagnostic methods for OC are time-consuming and have low accuracy. Surface plasmon resonance (SPR) biosensors offer a promising alternative to conventional techniques, as they enable rapid and less invasive screening of various circulating indicators. These biosensors are widely used for biomolecular interaction analysis and detecting tumor markers, and they are currently being investigated as a rapid diagnostic tool for early-stage cancer detection. Our main focus is on the fundamental concepts and performance characteristics of SPR biosensors. We also discuss the latest advancements in SPR biosensors that enhance their sensitivity and enable high-throughput quantification of OC biomarkers, including CA125, HE4, CEA, and CA19-9. Finally, we address the future challenges that need to be overcome to advance SPR biosensors from research to clinical applications. The ultimate goal is to facilitate the translation of SPR biosensors into routine clinical practice for the early detection and management of OC.

Robust prediction of colorectal cancer via gut microbiome 16S rRNA sequencing data.

Introduction. The study addresses the challenge of utilizing human gut microbiome data for the early detection of colorectal cancer (CRC). The research emphasizes the potential of using machine learning techniques to analyze complex microbiome datasets, providing a non-invasive approach to identifying CRC-related microbial markers.Hypothesis/Gap Statement. The primary hypothesis is that a robust machine learning-based analysis of 16S rRNA microbiome data can identify specific microbial features that serve as effective biomarkers for CRC detection, overcoming the limitations of classical statistical models in high-dimensional settings.Aim. The primary objective of this study is to explore and validate the potential of the human microbiome, specifically in the colon, as a valuable source of biomarkers for colorectal cancer (CRC) detection and progression. The focus is on developing a classifier that effectively predicts the presence of CRC and normal samples based on the analysis of three previously published faecal 16S rRNA sequencing datasets.Methodology. To achieve the aim, various machine learning techniques are employed, including random forest (RF), recursive feature elimination (RFE) and a robust correlation-based technique known as the fuzzy forest (FF). The study utilizes these methods to analyse the three datasets, comparing their performance in predicting CRC and normal samples. The emphasis is on identifying the most relevant microbial features (taxa) associated with CRC development via partial dependence plots, i.e. a machine learning tool focused on explainability, visualizing how a feature influences the predicted outcome.Results. The analysis of the three faecal 16S rRNA sequencing datasets reveals the consistent and superior predictive performance of the FF compared to the RF and RFE. Notably, FF proves effective in addressing the correlation problem when assessing the importance of microbial taxa in explaining the development of CRC. The results highlight the potential of the human microbiome as a non-invasive means to detect CRC and underscore the significance of employing FF for improved predictive accuracy.Conclusion. In conclusion, this study underscores the limitations of classical statistical techniques in handling high-dimensional information such as human microbiome data. The research demonstrates the potential of the human microbiome, specifically in the colon, as a valuable source of biomarkers for CRC detection. Applying machine learning techniques, particularly the FF, is a promising approach for building a classifier to predict CRC and normal samples. The findings advocate for integrating FF to overcome the challenges associated with correlation when identifying crucial microbial features linked to CRC development.

Plasmonics-enhanced spikey nanorattle-based biosensor for direct SERS detection of mRNA cancer biomarkers.

We present a plasmonics-enhanced spikey nanorattle-based biosensor for direct surface-enhanced Raman scattering (SERS) detection of mRNA cancer biomarkers. Early detection of cancers such as head and neck squamous cell carcinoma (HNSCC) is critical for improving patient outcomes in regions with limited access totraditional diagnostic methods. Our method targets Keratin 14 (KRT14), a promising diagnostic mRNA biomarker for HNSCC, using a sandwich hybridization approach with magnetic beads and SERS spikey nanorattles (SpNR). We synthesized SpNR with a core-gap-shell structure to enhance SERS signals, achieving a limit of detection of 90 femtomolar. A pilot study using clinical samples demonstrated the efficacy of our biosensor in distinguishing between tissue with positive or negative diagnosis for HNSCC, highlighting its potential for rapid and sensitive cancer diagnostics in low-resource settings. This plasmonic assay offers a promising avenue for portable and high-specificity detection of nucleic acid biomarkers, with implications for early cancer detection and improved patient care, especially in middle and low-resource settings.

Enhanced Cancer Biomarker Detection using Fe3O4 Magnetic Nanoparticles: Synthesis, Surface Modifications and Diagnostic Applications: A Review

Fe3O4 magnetic nanoparticles exhibit significant potential for cancer detection due to their unique magnetic properties and versatility. This review examines their role in enhancing cancer biomarker detection, focusing on synthesis methods, surface modifications and diagnostic accuracy. Fe3O4 nanoparticles serve as sensitive MRI contrast agents, facilitating early cancer diagnosis and improving patient prognosis. Synthesis techniques influence their properties, morphology and dimensions, which affect performance. Surface modifications enhance targeting and reduce immunological reactions, enabling precise biomarker detection and effective drug delivery to tumours, minimizing damage to healthy tissue. Despite these advantages, challenges remain in optimizing delivery efficiency and overcoming medication resistance. Further research is required to understand the pharmacokinetics and pharmacodynamics of these nanoparticles, including their distribution, metabolism and physiological impacts. This review provides insights into the potential of Fe3O4 magnetic nanoparticles as cancer detection agents, aiming to guide future research towards developing safer and more efficient applications in medical diagnostics and treatment. HIGHLIGHTS Fe3O4 magnetic nanoparticles exhibit unique magnetic properties that are highly effective in detecting cancer biomarkers. These nanoparticles enable early cancer diagnosis by identifying biomarkers at low concentrations with high sensitivity. The review assesses various synthesis techniques for Fe3O4 magnetic nanoparticles to optimize their detection capabilities. Exploration of surface modification strategies to enhance the functionality and efficacy of Fe3O4 nanoparticles in cancer biomarker detection. Enhanced diagnostic accuracy through the application of Fe3O4 magnetic nanoparticles, promising improved outcomes in cancer detection technologies. GRAPHICAL ABSTRACT

Evaluation of the role of EGFR exon 19 747-750 deletion mutation and plasma amino acid profile in the development of lung cancer.

Lung cancer (LC) is the most common form of cancer in the world. Of the proteins involved in cell differentiation and proliferation, the epidermal growth factor receptor (EGFR) is among the most significant. Amino acids play a crucial role in cell physiology as metabolic regulators. The benefits of liquid biopsies are their non-invasive nature, ease of collection, and ability to depict the entire tumor's status. The present study is designed to detect the relation between the EGFR exon 19 747-750 deletion mutation and lung cancer and investigate the patterns of alterations of plasma-free amino acids (PFAA) in lung cancer patients of different histopathological types and stages as biomarkers for early detection of lung cancer. The study sample comprised 60 lung cancer patients and 60 age- and sex-matched healthy individuals as the control group. Polymerase chain reaction and restriction fragment length polymorphism (PCR-RFLP) were used to examine the EGFR exon 19 747-750 deletion mutation, and an AA analyzer was used to quantify the plasma free amino acid (PFAA) profile. Compared with controls, LC patients had significantly higher levels of three AAs and significantly lower levels of fifteen AAs. Thirteen AAs varied significantly between stages I and II. In the lung cancer group, the percentage of cases of mutant EGFR exon-19 deletion increased to 30% from 13.3% in the control group. The histological forms of lung cancer did not significantly differ in this rise. Valine and citrulline plasma levels were substantially greater in the mutant than in the wild-type. Lysine, histidine, and methionine were the independent predictors of the LC group in multivariate analysis. Lung cancer development is influenced by the EGFR exon 19 747-750 deletion mutation, and the prognosis and early prediction of lung cancer are greatly affected by the amino acid profile concentrations.

A Zinc Oxide Nanorod-Based Electrochemical Aptasensor for the Detection of Tumor Markers in Saliva

Biosensors have emerged as a promising tool for the early detection of oral squamous cell carcinoma (OSCC) due to their rapid, sensitive, and specific detection of cancer biomarkers. Saliva is a non-invasive and easy-to-obtain biofluid that contains various biomarkers of OSCC, including the carcinoembryonic antigen (CEA). In this study, an electrochemical aptasensor for the detection of CEA in saliva has been developed towards the diagnosis and early screening of OSCC. This aptasensor utilized a CEA-sensitive aptamer as sensitive elements. A fluorine-doped Tin Oxide (FTO) chip with a surface modification of a zinc oxide nanorod was employed as a transducer. Electrochemical measurements were carried out to detect the responsive signals originating from the specific binding between aptamers and CEAs. The measurement results indicated that this aptasensor was responsive to different concentrations of CEA ranging from 1 ng/mL to 80 ng/mL in a linear relationship. The limit of detection (LOD) was 0.75 ng/mL. This aptasensor also showed very good specificity and regenerative capability. Stability testing over a 12-day period showed excellent performance of this aptasensor. All the results demonstrated that this aptasensor has great potential to be used for the detection of CEA in the saliva of OSCC patients. This aptasensor provides a promising method for the rapid detection of CEA with convenience, which has great potential to be used as a new method for clinical diagnoses and early screening of OSCC.

Functional inorganic nanoparticles in cancer: Biomarker detection, imaging, and therapy

Cancer poses a major global public health challenge. Developing more effective early diagnosis methods and efficient treatment techniques is crucial to enhance early detection sensitivity and treatment outcomes. Nanomaterials offer sensitive, accurate, rapid, and straightforward approaches for cancer detection, diagnosis, and treatment. Inorganic nanoparticles are widely used in medicine because of their high stability, large specific surface area, unique surface properties, and unique quantum size effects. Functional inorganic nanoparticles involve modifying inorganic nanoparticles to enhance their physical properties, enrichment capabilities, and drug-loading efficiency and to minimize toxicity. This Review provides an overview of various types of inorganic nanoparticles and their functionalization characteristics. We then discuss the progress of functional inorganic nanoparticles in cancer biomarker detection and imaging. Furthermore, we discuss the application of functional inorganic nanoparticles in radiotherapy, chemotherapy, gene therapy, immunotherapy, photothermal therapy, photodynamic therapy, sonodynamic therapy, and combination therapy, highlighting their characteristics and advantages. Finally, the toxicity and potential challenges of functional inorganic nanoparticles are analyzed. The purpose of this Review is to explore the application of functional inorganic nanoparticles in diagnosing and treating cancers, while also presenting a new avenue for cancer diagnosis and treatment.

Enhanced SERS detection of the colorectal cancer biomarker utilizing a two-dimensional silver substrate

To improve the sensitivity, accuracy and specificity of the assay, a two-dimensional silver substrate with EF=5.85×108 was first synthesized as a SERS substrate, on the surface of which DSP molecules were modified to form a DSP-antibody coupling through the activation of two N-hydroxy succinimide (NHS) esters to capture TNF-α. Subsequently, aptamerized silver-coated gold nanospheres (Au@TFMBA@Ag) were synthesized as Surface-Enhanced Raman Scattering (SERS) recognition probes. These probes were employed to create a sandwich structure for the quantitative detection of Tumor Necrosis Factor-alpha (TNF-α), utilizing the SERS signal intensity at 1374 cm−1. Quantitative detection of TNF-α was successfully accomplished within the concentration range of 10−4 to 10−10 mg·mL−1. Clinical serum samples were collected and subjected to testing. Significance analysis, conducted through the T-test (p < 0.0001), unequivocally showed the method's ability to differentiate between sera from normal individuals and those diagnosed with colon cancer.

Rapid Detection of Explicit Volatile Organic Compounds for Early Diagnosis of Lung Cancer Using MoSi2N4 Monolayer.

In this study, we investigate the adsorption of MoSi2N4) and MoSi2N4-VNtowards five potential lung cancer volatile organic compounds (VOCs).Density functional theory calculations reveal that MoSi2N4 weakly adsorb the mentioned VOCs, whereas introduction of nitrogen vacancies significantly enhances the adsorption energies ([[EQUATION]]), both in gas phase and aqueous medium. The MoSi2N4-VN monolayers exhibit a reduced bandgap and facilitate charge transfer upon VOCs adsorption, resulting in enhanced [[EQUATION]] values of -0.83, -0.76, -0.49, -0.61, and -0.50 eV for 2,3,4-trimethyl hexane, 4-methyl octane, o-toluidine, Aniline, and Ethylbenzene, respectively. Bader charge analysis and spin-polarized density of states (SPDOS) elucidate the charge redistribution and hybridization between MoSi2N4-VN and the adsorbed VOCs. The work function of MoSi2N4-VN is significantly reduced upon VOCs adsorption due to induced dipole moments, enabling smooth charge transfer and selective VOCs sensing. Notably, MoSi2N4-VN monolayers exhibit sensor responses ranging from 16.2% to 26.6% towards the VOCs, with discernible selectivity. Importantly, the recovery times of the VOCs desorption is minimal, reinforcing the suitability of MoSi2N4-VN as a rapid, and reusable biosensor platform for efficient detection of lung cancer biomarkers. Thermodynamic analysis based on Langmuir adsorption model shows improved adsorption and detection capabilities MoSi2N4-VN under diverse operating conditions of temperatures and pressures.

Plasma cell-free DNA methylome-based liquid biopsy for accurate gastric cancer detection.

Early detection plays a critical role in mitigating mortality rates linked to gastric cancer. However, current clinical screening methods exhibit suboptimal efficacy. Methylation alterations identified from cell-free DNA (cfDNA) present a promising biomarker for early cancer detection. Our study focused on identifying gastric cancer-specific markers from cfDNA methylation to facilitate early detection. We enrolled 150 gastric cancer patients and 100 healthy controls in this study, and undertook genome-wide methylation profiling of cfDNA using cell-free methylated DNA immunoprecipitation and high-throughput sequencing. We identified 21 differentially methylated regions (DMRs) between the gastric tumor and nontumor groups using multiple algorithms. Subsequently, using the 21 DMRs, we developed a gastric cancer detection model by random forest algorithm in the discovery set, and validated the model in an independent set. The model was able to accurately discriminate gastric cancer with a sensitivity and specificity of 93.90% and 95.15% in the discovery set, respectively, and 88.38% and 94.23% in the validation set, respectively. These results underscore the efficacy and accuracy of cfDNA-derived methylation markers in distinguishing early stage gastric cancer. This study highlighted the significance of cfDNA methylation alterations in early gastric cancer detection.