Biomarkers For Detection Of Cancer Research Articles

Mex3a promoter hypomethylation can be utilized to diagnose HBV-associated hepatocellular carcinoma: a randomized controlled trial

BackgroundHepatocellular carcinoma remains a health challenge for humanity. Therefore, there is an urgent need to develop novel biomarkers with high efficiency yet fast ability to meet the requirements of hepatocellular carcinoma treatment.MethodsA total of 229 patients with HBV-associated hepatocellular carcinoma (HCC), 298 patients with chronic hepatitis B (CHB), and 96 healthy controls were retrospectively analyzed. Methylation levels of the Mex3a promoter in peripheral blood mononuclear cells (PBMCs) were measured using MethyLight to obtain clinical and laboratory parameters.ResultsThe Mex3a promoter methylation level in HCC patients (median: 0.289% and interquartile range: 0.126%–0.590%) was significantly lower than that in CHB patients (median: 0.999%, interquartile range: 0.417%–1.268%, and p < 0.001) and healthy people (median: 2.172%, interquartile range: 1.225%–3.098%, and p < 0.001). The Mex3a mRNA levels in HCC patients (median: 12.198 and interquartile range: 3.112–18.996) were significantly higher than those in CHB patients (median: 1.623 and interquartile range: 0.066–6.000, and p < 0.001) and healthy controls (median: 0.329, interquartile range: 0.031–1.547, and p < 0.001). MethyLight data were expressed as a percentage of the methylated reference (PMR) value. The Mex3a PMR value was negatively correlated with the mRNA expression level (Spearman’s R = −0.829 and p < 0.001). The Mex3a PMR value of HCC patients was significantly correlated with age (Spearman’s R = 0.113 and p = 0.044), and the mRNA level was significantly correlated with ALT (Spearman’s R = 0.132 and p = 0.046). The Mex3a promoter methylation levels and mRNA levels were also independent factors in the development of liver cancer. The Mex3a promoter methylation and mRNA levels were better at distinguishing HCC from CHB than AFP [area under the receiver operating characteristic curve (AUC) for predicting HCC vs. CHB: 0.915 vs. 0.715: p < 0.001]. The combined use of AFP and Mex3a methylation levels and mRNA levels further improved the area under the receiver operating characteristic curve.ConclusionThe presence of Mex3a promoter hypomethylation in hepatocellular carcinoma can be used as a non-invasive biomarker for the early detection of liver cancer.

Molecular Imaging Biomarkers for Early Cancer Detection: A Systematic Review of Emerging Technologies and Clinical Applications

Background: Early cancer detection is crucial for improving patient outcomes. Molecular imaging biomarkers offer the potential for non-invasive, early-stage cancer diagnosis. Objectives: To evaluate the effectiveness and accuracy of molecular imaging biomarkers for early cancer detection across various imaging modalities and cancer types. Methods: A comprehensive search of PubMed/MEDLINE, Embase, Web of Science, Cochrane Library, and Scopus was performed, covering the period from January 2010 to December 2023. Eligibility criteria included original research articles published in English on molecular imaging biomarkers for early cancer detection in humans. The risk of bias for included studies was evaluated using the QUADAS-2 tool. The findings were synthesized through narrative synthesis, with quantitative analysis conducted where applicable. Results: In total, 50 studies were included. Positron emission tomography (PET)-based biomarkers showed the highest sensitivity (mean: 89.5%, range: 82–96%) and specificity (mean: 91.2%, range: 85–100%). Novel tracers such as [68Ga]-PSMA for prostate cancer and [18F]-FES for breast cancer demonstrated promising outcomes. Optical imaging techniques showed high specificity in intraoperative settings. Conclusions: Molecular imaging biomarkers show significant potential for improving early cancer detection. Integration into clinical practice could lead to earlier interventions and improved outcomes. Further research is needed to address standardization and cost-effectiveness.

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.

Photonic-Metamaterial-Based, Near-Field-Enhanced Biosensing Approach for Early Detection of Lung and Ovarian Cancer

Early detection of lung and ovarian cancers relies heavily on identifying tumor biomarkers, but current methods require large blood samples and complex genetic testing. This study presents a novel photonic-metamaterial-based biosensing approach that leverages near-field radiative enhancement to detect cancer biomarkers (CA 125, CEA, and CYFRA 21-1) with high sensitivity. By utilizing structured photonic metamaterials, we optimize specific wavelengths to identify these biomarkers in interstitial fluid, which can be easily collected via minimally invasive microneedle arrays. Integrating near-field interactions with wavelength-selective metamaterials amplifies the thermal response at the nanoscale, allowing for the detection of deficient concentrations of biomarkers. This photonic metamaterial technique provides a faster, more accessible, and affordable alternative to conventional blood-based methods, significantly improving early detection and monitoring of cancer. Ultimately, this approach offers a transformative tool for clinical and research applications in cancer diagnostics.

Increased MAGE-C Family Gene Expression Levels as a Biomarker of Colon Cancer Through the Demethylation Mechanism

Background/Objectives: Colon cancer (CC) in Saudi Arabia is associated with a high death rate and is commonly identified at a more progressive stage. Therefore, it is critical to identify and characterize potential novel cancer-specific biomarkers to enhance early CC diagnosis. The goal was to assess their potential use as cancer biomarkers for the early detection and improvement of CC treatment. Methods: MAGE-C1, MAGE-C2, and MAGE-C3 family gene expression levels were examined using RT-PCR and qRT-PCR assays in 26 adjacent normal colon (NC) and CC tissue samples from male and female Saudi patients. Using several cell lines and the qRT-PCR technique, epigenetic control was also investigated to determine whether reduced treatment with 5-aza-2′-deoxycytidine, which reduces DNA methyltransferase, can increase the expression of the MAGE-C gene. The expression levels, promoter methylation, and prognostic significance of MAGE-C1, MAGE-C2, and MAGE-C3 genes across various cancers were analyzed using The Cancer Genome Atlas (TCGA) data. Additionally, the prognostic significance of these genes was assessed through Kaplan–Meier survival analysis. Results: The RT-PCR results showed that MAGE-C1, MAGE-C2, and MAGE-C3 gene expressions were significantly higher in the CC and NC tissues. The MAGE-C1 expression level was the highest in CC tissues (p < 0.0001), followed by MAGE-C3 (p = 0.0004) and MAGE-C2 (p = 0.0020) in descending order. The 5-aza-2′-deoxycytidine treatment significantly increased the mRNA expression levels of the MAGE-C1, MAGE-C2, and MAGE-C3 genes in HCT116, Caco-2, MCF-7, and MCF-10A cells. Expression analyses of TCGA samples revealed significant upregulation of these genes in several cancer types, with notable differences between normal, tumor, and metastatic tissues. Promoter methylation indicates hypomethylation in cancerous tissues. Survival analyses show that high expression levels of MAGE-C1 correlate with better prognosis, while MAGE-C3 is associated with poorer outcomes. Conclusions: These results demonstrate that MAGE-C genes are viable prospective biomarkers of CC controlled by hypomethylating drugs, consequently offering a possible treatment target for CC in a specific population.

Overcoming the Challenges of Hyperpolarizing Substrates with Parahydrogen‐Induced Polarization in an MRI System

Hyperpolarization of 13C nuclei in biomolecules and their administration as imaging agents enables in‐vivo monitoring of metabolism. This approach has demonstrated potential for deriving imaging biomarkers for cancer detection, differentiation, and therapy efficacy assessment. The in situ generation of polarized substrates using a permanent addition of parahydrogen to an unsaturated precursor inside the bore of an MRI system used for subsequent imaging circumvents the need for a dedicated external polarizer. This approach reduces polarization loss associated with sample transfer, minimizes hardware requirements and cost, and results in reduced spatial requirements. However, performing INEPT‐like pulsed sequences for heteronuclear spin‐order transfer in the bore of an MRI system is challenged by poor uniformity of static and excitation magnetic field and molecular convection during the polarization transfer. Therefore, here we characterize these effects, implement a robust modification to the pulse sequence, and measure experimentally the polarization improvement upon modification of the sequence. After rigorous optimization of the parameters, we obtained a 13C polarization of 44.5% for 50 mM of the 1‐13C site of ethyl acetate‐d6. Our parahydrogen‐induced polarization approach enhances the accessibility to hyperpolarized MRI, circumventing the need for an external polarizer.

From photonic technologies to microfluidics-A review on the techniques which revolutionize liquid biopsy, opening a new era in cancer therapy.

Cancer therapy is one of the most researched upon medical field in the world. Non invasive technologies such as liquid biopsy are gaining more importance in cancer therapy because of their manifold advantages over traditional invasive biopsy methods. Liquid biopsy is used to analyze nucleic acids such as ctDNA, cfDNA and RNA, cellular and subcellular components such as proteins, extracellular vesicles and circulating tumor cells in various biological fluids such as blood, urine, cerebrospinal fluid, pleural fluid and ascites fluid for diagnosis of cancer. Liquid biopsy has a wide range of applications such as assessment of residual diseases and tumors which cannot be biopsied easily and prediction of CAR-T response and response to immune checkpoint inhibitors. It can also be used to know the efficacy of cancer drugs in a patient by analyzing multiple samples. Liquid biopsy is becoming more popular as it allows biopsy of those samples in which solid tumor biopsies are challenging or impracticable. To achieve comprehensive insight on the status of cancer in a patient, various cutting edge liquid biopsy techniques have been developed. Microfluidics and photonic technologies, along with PCR, next generation sequencing, advanced and innovative molecular and cell biology approaches and imaging techniques have expanded the domain of liquid biopsy and elevated the accuracy of liquid biopsy results. This review discusses about the contributions of some widely used methods along with microfluidics and photonic technologies in detection of cancer biomarkers by liquid biopsy.

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