A multiplex blood-based assay targeting DNA methylation in PBMCs enables early detection of breast cancer

Systems epigenetic approach towards non-invasive breast cancer detection

No study has systematically compared the suitability of DNA methylation (DNAme) profiles in non-invasive samples for the detection of breast cancer (BC). We assess non-tumour DNAme in 1,100 cervical, buccal, and blood samples from BC cases and controls and find that cervical samples exhibit the largest nuber of differentially methylated sites, followed by buccal samples. No sites were significant in blood after FDR adjustment. Deriving DNAme-based classifiers for BC detection in each sample type (WID-buccal-, cervical-, or blood-BC), we achieve validation AUCs of 0.75, 0.66, and 0.51, respectively. Buccal and cervical BC-associated DNAme alterations distinguish between BC cases and controls in both surrogate and breast tissue (AUC > 0.88), yet individual sites and the directionality of methylation changes are not identical between these two sample types, and buccal sample DNAme aligns with breast methylation changes more closely. Pending additional validation, these insights may have the potential to improve non-invasive personalized BC prevention.

Development and validation of a 14-CpG DNA methylation signature and drug targets for prognostic prediction in breast cancer

Background

Breast cancer (BC) is the most prevalent cancer among women and a leading cause of cancer-related deaths worldwide. Emerging evidence suggests that DNA methylation, a well-studied epigenetic modification, regulates various cellular processes critical for cancer development and progression and holds promise as a biomarker for cancer diagnosis and prognosis, potentially enhancing the efficacy of precision therapies.

Methods

We developed a robust prognostic model for BC based on DNA methylation and clinical data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). We analyzed the association of the model with clinicopathological features, survival outcomes, and chemotherapy drug sensitivity.

Results

A set of 216 differentially methylated CpGs was identified by intersecting three datasets (TCGA, GSE22249, and GSE66695). Using univariate Cox proportional hazard and LASSO Cox regression analyses, we constructed a 14-CpG model significantly associated with progression-free interval (PFI), disease-specific survival (DSS), and overall survival (OS) in BC patients. Kaplan-Meier (KM) survival analysis, receiver operating characteristic (ROC) analysis, and nomogram validation confirmed the clinical value of the signature. The Cox analysis showed a significant association between the signature and PFI and DSS in BC patients. KM analysis effectively distinguished high-risk from low-risk patients, while ROC analysis demonstrated high sensitivity and specificity in predicting BC prognosis. A nomogram based on the signature effectively predicted 5- and 10-year PFI and DSS. Additionally, combining our model with clinical risk factors suggested that patients in the I-II & M+ subgroup could benefit from adjuvant chemotherapy regarding PFI, DSS, and OS. Gene Ontology (GO) functional enrichment and KEGG pathway analyses indicated that the top 3,000 differentially expressed genes (DEGs) were enriched in pathways related to DNA replication and repair and cell cycle regulation. Patients in the high-risk group might benefit from drugs targeting DNA replication and repair processes in tumor cells.

Conclusion

The 14-CpG model serves as a useful biomarker for predicting prognosis in BC patients. When combined with TNM staging, it offers a potential strategy for individualized clinical decision-making, guiding personalized therapeutic regimen selection for clinicians.

Comparative epigenomics to clinical trials in human breast cancer and canine mammary tumor

Epigenetics and epigenomics are captivating fields of molecular biology, dedicated to the exploration of heritable alterations in gene expression and cellular phenotypes, which transpire devoid of any discernible modifications to the fundamental DNA sequence. This intricate regulatory apparatus encompasses multiple mechanisms, prominently featuring DNA methylation, histone modifications, and the involvement of non-coding RNA molecules in pivotal roles. To achieve a comprehensive grasp of these diverse mechanisms, it is imperative to conduct research employing animal models as proxies for human studies. Since experimental animal models like mice and rats struggle to replicate the diverse environmental conditions experienced by humans, this review focuses on comparing common epigenetic alterations in naturally occurring tumors in canine models, which share the human environment, with those in humans. Through this, we emphasize the importance of an epigenetic regulation in the comparative medical approach to a deeper understanding of cancers and further development of cancer treatments. Additionally, we elucidate epigenetic modifications pertinent to specific developmental stages, the ageing process, and the progression of various diseases.

A novel photoelectrochemical biosensor for sensitive detection of nucleic acids based on recombinase polymerase amplification and 3D-array titania nanorods

Nucleic acids detection is essential for diagnosing pathogens; however, traditional methods usually face challenges such as low sensitivity, lengthy reaction times, and strict temperature requirements. This study develops a novel photoelectrochemical (PEC) biosensor that integrates recombinase polymerase amplification (RPA) with a 3D-array titania (TiO2) nanorods nanorod electrode, addressing the challenge of achieving sensitive detection of RPA-amplified nucleic acids products, thereby enabling earlier and more reliable pathogen detection. The biosensor utilizes a triple-binding mode involving FITC antibodies, target nucleic acids, and an HRP-streptavidin sandwich structure, significantly improving the bio-functionalization of the electrode surface. The isothermal RPA process amplifies DNA at 37 °C within 20 min, while the TiO2 nanorods ensure efficient photoelectric conversion. The oxidation of 4-chloro-1-naphthol (4-CN) generates a signal-reducing benzo-4-chlorohexadienone (4-CD), enabling precise and sensitive detection. This PEC-RPA biosensor successfully detects Orientia tsutsugamushi (Ot) nucleic acids with a detection limit of 15 copies/μL within 60 min, demonstrating robust performance. The study provides a promising strategy for advancing pathogen nucleic acids diagnostic platforms and offers a versatile approach adaptable for detecting diverse pathogens.

Renal Clearable Chiral Manganese Oxide Supraparticles for In Vivo Detection of Metalloproteinase-9 in Early Cancer Diagnosis

In this study, polypeptide TGGGPLGVARGKGGC-induced chiral manganese dioxide supraparticles (MnO2 SPs) are prepared for sensitive quantification of matrix metalloproteinase-9 (MMP-9) in vitro and in vivo. The results show that L-type manganese dioxide supraparticles (L-MnO2 SPs) exhibited twice the affinity for the cancer cell membrane receptor CD47 (cluster of differentiation, integrin-associated protein) than D-type manganese dioxide supraparticles (D-MnO2 SPs) to accumulate at the tumor site after surface modification of the internalizing arginine-glycine-aspartic acid (iRGD) ligand, specifically reacting with the MMP-9, disassembling into ultrasmall nanoparticles (NPs), and efficiently underwent renal clearance. Furthermore, L-MnO2 facilitates the quantification of MMP-9 in mouse tumor xenografts, as demonstrated by circular dichroism (CD) and magnetic resonance imaging (MRI) within 2 h. A strong linear relationship is observed between MMP-9 concentration and both CD and MRI intensity, ranging from 0.01 to 10 ng mL-1. The corresponding limits of detection (LOD) are 0.0054 ng mL-1 for CD and 0.0062 ng mL-1 for MRI, respectively. hese SPs provide a new approach for exploring chiral advanced biosensors for early diagnosis of cancer.

Sensitive detection of K-ras gene by a dual-mode "on-off-on" sensor based on bipyridine ruthenium-MOF and bis-enzymatic cleavage technology

This study developed a dual-mode "on-off-on" sensor based on a bipyridine ruthenium metal-organic framework (Ru-MOF) and dual enzyme cleavage technology for the sensitive detection of the K-ras gene. The sensor combines electrogenerated chemiluminescence (ECL) and fluorescence (FL) detection modes, achieving high sensitivity and specificity in detecting the K-ras gene through catalytic hairpin assembly (CHA) and dual enzyme cleavage reactions. Experimental results showed that the detection limits for the K-ras gene were 0.044 fM (ECL) and 0.16 fM (FL), demonstrating excellent selectivity and stability during detection. Through testing actual samples, the sensor has shown potential for application in complex biological environments. This method offers an efficient and reliable new tool for cancer diagnosis and treatment.

Causality-driven candidate identification for reliable DNA methylation biomarker discovery

Despite vast data support in DNA methylation (DNAm) biomarker discovery to facilitate health-care research, this field faces huge resource barriers due to preliminary unreliable candidates and the consequent compensations using expensive experiments. The underlying challenges lie in the confounding factors, especially measurement noise and individual characteristics. To achieve reliable identification of a candidate pool for DNAm biomarker discovery, we propose a Causality-driven Deep Regularization framework to reinforce correlations that are suggestive of causality with disease. It integrates causal thinking, deep learning, and biological priors to handle non-causal confounding factors, through a contrastive scheme and a spatial-relation regularization that reduces interferences from individual characteristics and noises, respectively. The comprehensive reliability of the proposed method was verified by simulations and applications involving various human diseases, sample origins, and sequencing technologies, highlighting its universal biomedical significance. Overall, this study offers a causal-deep-learning-based perspective with a compatible tool to identify reliable DNAm biomarker candidates, promoting resource-efficient biomarker discovery.

DNA Methylation Profile in Buffy Coat Identifies Methylation Differences Between Cirrhosis with and Without Hepatocellular Carcinoma

BACKGROUND/OBJECTIVES

Cirrhosis is the precursor to most cases of hepatocellular carcinoma (HCC). Understanding the mechanisms leading to the transition from cirrhosis to HCC and identifying key biomarkers is crucial to developing effective screening strategies and reducing HCC-related mortality. DNA methylation is associated with gene inactivation and plays an important role in physiological and pathological processes; however, its role in cirrhosis progression to HCC is unknown.

METHODS

We performed genome-wide DNA methylation profiling using Illumina Infinium MethylationEPI BeadChip in pre-diagnostic samples from 22 cirrhosis patients who subsequently developed HCC and 22 cirrhosis patients who remained HCC-free during an average 4-year follow-up. In a secondary analysis, we examined a subset of patients without hepatitis C virus (HCV) infection.

RESULTS

We identified three differentially methylated positions (DMPs) located in ADAM12 (cg13674437) and PSD3 (cg06758847 and cg24595678) that show a strong association with HCC risk (lower median vs. higher median hazards ratio (HR): HR cg13674437 = 0.34, 95% CI = 0.14-0.83; HR cg06758847 = 4.89, 95% CI = 1.79-13.33; HR cg24595678 = 11.19, 95% CI = 3.27-38.35). After excluding all HCV-active patients from our analysis, the HR for the DMPs remained significant.

CONCLUSIONS

In conclusion, the findings in this study support the theory that buffy coat-derived DNA methylation markers could be used to identify biomarkers among cirrhosis patients at high risk for HCC before clinical symptoms appear. A further study with a large prospective cohort is required to validate these findings.

Multisite DNA methylation alterations of peripheral blood mononuclear cells serve as novel biomarkers for the diagnosis of AIS/stage I lung adenocarcinoma: a multicenter cohort study

BACKGROUND

Early diagnosis remains an obstacle for improving the outcome of lung adenocarcinoma (LUAD). DNA methylation changes in peripheral blood mononuclear cells (PBMCs) could reflect an immune response to tumorigenesis, providing the theoretical basis for early cancer diagnosis based on immune cell profiling.

METHODS

This multi-center study evaluated the DNA methylation patterns based on PBMCs samples from 1115 individuals at nine medical centers. Genome-wide DNA methylation profiling of PBMCs in a discovery cohort (35 LUAD patients and 50 healthy controls) was performed using Illumina 850K microarray. Candidate differentially methylated CpG positions (DMPs) were selected and validated in a two-step DMPs screening cohort (65 LUAD patients and 80 healthy controls) by pyrosequencing and multiple target region methylation enrichment sequencing (MTRMES). Then, an early LUAD Diagnostic Panel (LDP score) based on multisite methylation-specific chip-based digital PCR was constructed in a training set and then confirmed in a validation set from the LDP score development cohort (389 AIS/stage I LUAD patients and 293 healthy controls). Besides, we included 157 other cancer patients, including 52 gastric cancer (GC) patients, 50 breast cancer (BC) patients, and 55 colorectal cancer (CRC) patients to assess the specificity of the LDP score. In addition, we also evaluated the early warning ability of LDP score for LUAD in a prospective cohort (46 people who were at high-risk of developing LC).

RESULTS

A total of 1415 LUAD-specific DMPs were identified. Then, six DMPs were selected for validation and three DMPs were finally verified. The LDP score was constructed by combining the three DMPs, age, and sex, and showed an AUC of 0.916, sensitivity of 88.17%, and specificity of 80.20% in a combined set, outperforming traditional methods, such as CEA and CT (detection rate: 87.79% vs. 4.69%; 87.79% vs. 35.21%). This diagnostic performance was confirmed in sub-types of LUAD with clinical challenges, such as 6-20 mm LUAD (AUC: 0.914, 95% CI: 0.889-0.934) and ground-glass nodules (AUC: 0.916, 95% CI: 0.889-0.938). Importantly, our LDP score had significant improvement in terms of selecting high-risk individuals who should receive low-dose computed tomography (87.80% vs. 9.28%). Remarkably, the LDP score could predict LUAD around 2 years before clinical diagnosis in our prospective cohort.

CONCLUSIONS

The novel developed LDP score represented a convenient and effective assay for the detection of AIS/stage I LUAD with high sensitivity and specificity, and had demonstrated unique advantages over traditional detection methods.

DNA Methylation-Based Diagnosis and Treatment of Breast Cancer

DNA methylation is a key epigenetic modifier involved in tumor formation, invasion, and metastasis. The development of breast cancer is a complex process, and many studies have now confirmed the involvement of DNA methylation in breast cancer. Moreover, the number of genes identified as aberrantly methylated in breast cancer is rapidly increasing, and the accumulation of epigenetic alterations becomes a chronic factor in the development of breast cancer. The combined effects of external environmental factors and the internal tumor microenvironment promote epigenetic alterations that drive tumorigenesis. This article focuses on the relevance of DNA methylation to breast cancer, describing the role of detecting DNA methylation in the early diagnosis, prediction, progression, metastasis, treatment, and prognosis of breast cancer, as well as recent advances. The reversibility of DNA methylation is utilized to target specific methylation aberrant promoters as well as related enzymes, from early prevention to late targeted therapy, to understand the journey of DNA methylation in breast cancer with a more comprehensive perspective. Meanwhile, methylation inhibitors in combination with other therapies have a wide range of prospects, providing hope to drug-resistant breast cancer patients.

Recent Advancements of Nanomedicine in Breast Cancer Surgery

Breast cancer surgery plays a pivotal role in the multidisciplinary approaches. Surgical techniques and objectives are gradually shifting from tumor complete resection towards prolonging survival, improving cosmetic outcomes, and restoring the social and psychological well-being of patients. However, surgical treatment still faces challenges such as inadequate sensitivity in sentinel lymph node localization, the need to improve intraoperative tumor boundary localization imaging, postoperative scar healing, and the risk of recurrence, necessitating other adjunct measures for improvement. To address these challenges, specificity-optimized nanomedicines have been introduced into the surgical therapeutic landscape of breast cancer. In particular, this review involves starting with an overview of breast structure and the composition of the tumor microenvironment and then introducing the guiding principle and foundation for the design of nanomedicine. Moreover, we will take the order process of breast cancer surgery diagnosis and treatment as the starting point, and adaptively propose the roles and advantages of nanomedicine in addressing the corresponding issues. Furthermore, we also involved the prospects of utilizing advanced technological approaches. Overall, this review seeks to uncover the sophisticated design and strategies of nanomedicine from a clinical standpoint, address the challenges faced in surgical treatment, and provide insights into this subject matter.

Epigenetic biomarkers in Alzheimer's disease: Diagnostic and prognostic relevance

Alzheimer's disease (AD) is a leading cause of cognitive decline in the aging population, presenting a critical need for early diagnosis and effective prognostic tools. Epigenetic modifications, including DNA methylation, histone modifications, and non-coding RNAs, have emerged as promising biomarkers for AD due to their roles in regulating gene expression and potential for reversibility. This review examines the current landscape of epigenetic biomarkers in AD, emphasizing their diagnostic and prognostic relevance. DNA methylation patterns in genes such as APP, PSEN1, and PSEN2 are highlighted for their strong associations with AD pathology. Alterations in DNA methylation at specific CpG sites have been consistently observed in AD patients, suggesting their utility in early detection. Histone modifications, such as acetylation and methylation, also play a crucial role in chromatin remodelling and gene expression regulation in AD. Dysregulated histone acetylation and methylation have been linked to AD progression, making these modifications valuable biomarkers. Non-coding RNAs, including microRNAs (miRNAs) and long non-coding RNAs (lncRNAs), further contribute to the epigenetic regulation in AD. miRNAs can modulate gene expression post-transcriptionally and have been found in altered levels in AD, while lncRNAs can influence chromatin structure and gene expression. The presence of these non-coding RNAs in biofluids like blood and cerebrospinal fluid positions them as accessible and minimally invasive biomarkers. Technological advancements in detecting and quantifying epigenetic modifications have propelled the field forward. Techniques such as next-generation sequencing, bisulfite sequencing, and chromatin immunoprecipitation assays offer high sensitivity and specificity, enabling the detailed analysis of epigenetic changes in clinical samples. These tools are instrumental in translating epigenetic research into clinical practice. This review underscores the potential of epigenetic biomarkers to enhance the early diagnosis and prognosis of AD, paving the way for personalized therapeutic strategies and improved patient outcomes. The integration of these biomarkers into clinical workflows promises to revolutionize AD management, offering hope for better disease monitoring and intervention.

Circulating tumor DNA methylation detection as biomarker and its application in tumor liquid biopsy: advances and challenges

Circulating tumor DNA (ctDNA) methylation, an innovative liquid biopsy biomarker, has emerged as a promising tool in early cancer diagnosis, monitoring, and prognosis prediction. As a noninvasive approach, liquid biopsy overcomes the limitations of traditional tissue biopsy. Among various biomarkers, ctDNA methylation has garnered significant attention due to its high specificity and early detection capability across diverse cancer types. Despite its immense potential, the clinical application of ctDNA methylation faces substantial challenges pertaining to sensitivity, specificity, and standardization. In this review, we begin by introducing the basic biology and common detection techniques of ctDNA methylation. We then explore recent advancements and the challenges faced in the clinical application of ctDNA methylation in liquid biopsies. This includes progress in early screening and diagnosis, identification of clinical molecular subtypes, monitoring of recurrence and minimal residual disease (MRD), prediction of treatment response and prognosis, assessment of tumor burden, and determination of tissue origin. Finally, we discuss the future perspectives and challenges of ctDNA methylation detection in clinical applications. This comprehensive overview underscores the vital role of ctDNA methylation in enhancing cancer diagnostic accuracy, personalizing treatments, and effectively monitoring disease progression, providing valuable insights for future research and clinical practice.

Potential Role of AKR1B1 Gene Methylation in Diagnosis of Patients With Breast Cancer

Background

In addition to the great challenge of early diagnosis and prognosis in breast cancer (BC), the role of gene promoters in BC remains largely unexplored. This study aimed to evaluate aldo-keto reductase family 1 member B1 (AKR1B1) methylation as noninvasive biomarker for early BC diagnosis.

Methods

A total of 200 (120 with BC, 40 with benign breast diseases, 40 healthy) Egyptian women were enrolled. AKR1B1 methylation level was determined using EpiTect Methyl II QPCR assay quantitative polymerase chain reaction.

Results

Findings revealed that hypermethylation AKR1B1 was reported to be associated (P < .0001) with BC cases (93.2 [75.4-98.6]) compared with benign (23.9 [22.6-48.3]) or healthy (15.5 [10.6-16]) controls. It had a great diagnostic power (area under the curve [AUC] = 0.909) that was superior to cancer antigen (CA) 15-3 (AUC = 0.681) and carcinoembryonic antigen (CEA) (AUC = 0.539). Interestingly, AKR1B1 hypermethylation was reported to be significant in identifying BC early stages (AUC = 0.899) and grades (AUC = 0.903). Independent to hormonal status and HER2neu expression, AKR1B1 hypermethylation was related to some tumor severity features, including advanced stages, high histological grades, and lymph node invasion. Also, AKR1B1 high degrees of methylation were significantly correlated with the increase in CEA (r = .195; P = .027), CA-15.3 (r = .351; P = .0001) and tumor stages (r = .274; P = .014), grades (r = .253; P = .024), and lymph node invasion (r = .275; P = .014).

Conclusions

This study revealed that aberrant AKR1B1 methylation could facilitate early BC detection from benign br0east disorders. Hypermethylated AKR1B1 was related to BC aggressiveness suggesting its potential role as diagnostic and prognostic BC biomarker.

The Advances in the Development of Epigenetic Modifications Therapeutic Drugs Delivery Systems

Epigenetic dysregulation can significantly trigger the onset and progression of various diseases, epigenetic therapy is a new treatment strategy by changing DNA methylation, histone modification, N6-methyladenosine, chromatin modification and other epigenetic modifications to regulate gene expression levels for therapeutic purposes. However, small-molecule epigenetic drugs face challenges in disease treatment, such as lack of selectivity, limited therapeutic efficacy, and insufficient safety. Nanomedicine delivery systems offer significant advantages in addressing these issues by enhancing drug targeting, improving bioavailability, and reducing nonspecific distribution. This help minimize side effects while increasing both therapeutic effectiveness and safety of epigenetic drugs. In this review, we focus on the mechanism and role of epigenetic regulatory factors in diseases, as well as the challenges faced by small molecule inhibitors in treatment strategies, especially the research advancements in epigenetic drug delivery systems, review and discuss the therapeutic potential and challenges of using nanotechnology to develop epigenetic drug delivery systems.

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.

Proteomic analysis of peripheral blood mononuclear cells from OSCC patients reveals potential immune checkpoints to enable personalized treatment

Oral squamous cell carcinoma (OSCC) is one of the most prevalent cancers worldwide, with high mortality and prevalence rates. OSCC is defined as an immunogenic tumor with the potential to be recognized and targeted by the immune system. It is characterized by the extensive infiltration of immune cells and plays a vital role in tumorigenesis. Peripheral blood mononuclear cells (PBMC) are a functional subset of immune cells readily accessible through minimally invasive procedures. The molecular characterization of immune cells aids in understanding their functional roles in various pathophysiological conditions. Proteomic analysis of PBMCs from cancer patients provides insight into the mechanism of immunoregulation and the role of immune cells in impeding tumor development and progression. Therefore, the present study investigated the immune cell proteome of a cancer control cohort within OSCC, leveraging data-independent acquisition analysis by mass spectrometry (DIA-MS). Among the differentially abundant proteins in OSCC, we identified promising molecular targets, including LMNB1, CTSB, CD14, CD177, and SPI1. Further exploration of the signaling pathways related to the candidate molecules demonstrated their involvement in cancer immunomodulation. Therefore, this study can serve as a platform for identifying new candidate proteins to further investigate their potential as immunotherapeutic targets and prognostic markers.

Multi-omic analysis identifies metabolic biomarkers for the early detection of breast cancer and therapeutic response prediction

Reliable blood-based tests for identifying early-stage breast cancer remain elusive. Employing single-cell transcriptomic sequencing analysis, we illustrate a close correlation between nucleotide metabolism in the breast cancer and activation of regulatory T cells (Tregs) in the tumor microenvironment, which shows distinctions between subtypes of patients with triple-negative breast cancer (TNBC) and non-TNBC, and is likely to impact cancer prognosis through the A2AR-Treg pathway. Combining machine learning with absolute quantitative metabolomics, we have established an effective approach to the early detection of breast cancer, utilizing a four-metabolite panel including inosine and uridine. This metabolomics study, involving 1111 participants, demonstrates high accuracy across the training, test, and independent validation cohorts. Inosine and uridine prove predictive of the response to neoadjuvant chemotherapy (NAC) in patients with TNBC. This study deepens our understanding of nucleotide metabolism in breast cancer development and introduces a promising non-invasive method for early breast cancer detection and predicting NAC response in patients with TNBC.

Ion-sensitive field effect transistor biosensors for biomarker detection: current progress and challenges

The ion-sensitive field effect transistor (ISFET) has emerged as a crucial sensor device, owing to its numerous benefits such as label-free operation, miniaturization, high sensitivity, and rapid response time. Currently, ISFET technology excels in detecting ions, nucleic acids, proteins, and cellular components, with widespread applications in early disease screening, condition monitoring, and drug analysis. Recent advancements in sensing techniques, coupled with breakthroughs in nanomaterials and microelectronics, have significantly improved sensor performance. These developments are steering ISFETs toward a promising future characterized by enhanced sensitivity, seamless integration, and multifaceted detection capabilities. This review explores the structure and operational principles of ISFETs, highlighting recent research in ISFET biosensors for biomarker detection. It also examines the limitations of these sensors, proposes potential solutions, and anticipates their future trajectory. This review aims to provide a valuable reference for advancing ISFETs in the field of biomarker measurement.

Identification of circulating tumor DNA as a biomarker for diagnosis and response to therapies in cancer patients

The sampling of circulating biomarkers provides an opportunity for non-invasive evaluation and monitoring of cancer activity. In modern day practice, this has typically been in the form of circulating tumor DNA (ctDNA) detected in plasma. The field of ctDNA has been a burgeoning technology, with prominent applications for blood-based cancer screening and in disease status assessment, especially after curative-intent surgery to evaluate for minimal residual disease (MRD). Clinical applications for the latter show an incredibly high sensitivity in certain cancer types with a need for additional studies to determine how much clinical decision-making should be adapted based on ctDNA results and which cancer types, stages, and treatments are best informed by ctDNA results. This chapter provides an overview of ctDNA detection as tool for cancer screening, detecting MRD, and/or molecularly characterizing a cancer, highlighting the rapidly amassing research as a prognostic biomarker and emerging data on ctDNA as a predictive biomarker.

An Artificial Intelligence (AI)-Integrated Approach to Enhance Early Detection and Personalized Treatment Strategies in Lung Cancer Among Smokers: A Literature Review

Lung cancer (LC) is a significant global health issue, particularly among smokers, and is characterized by high rates of incidence and mortality. This comprehensive review offers detailed insights into the potential of artificial intelligence (AI) to revolutionize early detection and personalized treatment strategies for LC. By critically evaluating the limitations of conventional methodologies, we emphasize the innovative potential of AI-driven risk prediction models and imaging analyses to enhance diagnostic precision and improve patient outcomes. Our in-depth analysis of the current state of AI integration in LC care highlights the achievements and challenges encountered in real-world applications, thereby shedding light on practical implementation. Furthermore, we examined the profound implications of AI on treatment response, survival rates, and patient satisfaction, addressing ethical considerations to ensure responsible deployment. In the future, we will outline emerging technologies, anticipate potential barriers to their adoption, and identify areas for further research, emphasizing the importance of collaborative efforts to fully harness the transformative potential of AI in reshaping LC therapy. Ultimately, this review underscores the transformative impact of AI on LC care and advocates for a collective commitment to innovation, collaboration, and ethical stewardship in healthcare.

Epigenome-850K-wide profiling reveals peripheral blood differential methylation in term low birth weight

Aim: We investigate the genome-wide DNA methylation (DNAm) patterns of term low birth weight (TLBW) neonates.Methods: In the discovery phase, we assayed 32 samples (TLBW/control:16/16) using the EPIC 850k BeadChip Array. Targeted pyrosequencing of in 60 samples (TLBW/control:28/32) using targeted pyrosequencing during the replication phase.Results: The 850K array identified TLBW-associated 144 differentially methylated positions (DMPs) and 149 DMRs. Nearly 77% DMPs exhibited hypomethylation, located in the opensea and gene body regions. The most significantly enriched pathway in KEGG is sphingolipid metabolism (hsa00600), and the genes GALC and SGMS1 related to this pathway both show hypomethylation.Conclusion: Our analysis provides evidence of genome-wide DNAm alterations in TLBW. Further investigations are needed to elucidate the functional significance of these DNAm changes.

DNA methylation in human diseases

Aberrant epigenetic modifications, particularly DNA methylation, play a critical role in the pathogenesis and progression of human diseases. The current review aims to reveal the role of aberrant DNA methylation in the pathogenesis and progression of diseases and to discuss the original data obtained from international research laboratories on this topic. In the review, we mainly summarize the studies exploring the role of aberrant DNA methylation as diagnostic and prognostic biomarkers in a broad range of human diseases, including monogenic epigenetics, autoimmunity, metabolic disorders, hematologic neoplasms, and solid tumors. The last section provides a general overview of the possibility of the DNA methylation machinery from the perspective of pharmaceutic approaches. In conclusion, the study of DNA methylation machinery is a phenomenal intersection that each of its ways can reveal the mysteries of various diseases, introduce new diagnostic and prognostic biomarkers, and propose a new patient-tailored therapeutic approach for diseases.

Methods for the Analysis of Multiple Epigenomic Mediators in Environmental Epidemiology

PURPOSE OF REVIEW

Epigenetic changes can be highly influenced by environmental factors and have in turn been proposed to influence chronic disease. Being able to quantify to which extent epigenomic processes are mediators of the association between environmental exposures and diseases is of interest for epidemiologic research. In this review, we summarize the proposed mediation analysis methods with applications to epigenomic data.

RECENT FINDINGS

The ultra-high dimensionality and high correlations that characterize omics data have hindered the precise quantification of mediated effects. Several methods have been proposed to deal with mediation in high-dimensional settings, including methods that incorporate dimensionality reduction techniques to the mediation algorithm. Although important methodological advances have been conducted in the previous years, key challenges such as the development of sensitivity analyses, dealing with mediator-mediator interactions, including environmental mixtures as exposures, or the integration of different omic data should be the focus of future methodological developments for epigenomic mediation analysis.

Important role of DNA methylation hints at significant potential in tuberculosis

Tuberculosis (TB), an infectious disease caused by Mycobacterium tuberculosis (Mtb) infection, has persisted as a major global public health threat for millennia. Until now, TB continues to challenge efforts aimed at controlling it, with drug resistance and latent infections being the two main factors hindering treatment efficacy. The scientific community is still striving to understand the underlying mechanisms behind Mtb's drug resistance and latent infection. DNA methylation, a critical epigenetic modification occurring throughout an individual's growth and development, has gained attention following advances in high-throughput sequencing technologies. Researchers have observed abnormal DNA methylation patterns in the host genome during Mtb infection. Given the escalating issue of drug-resistant Mtb, delving into the role of DNA methylation in TB's development is crucial. This review article explores DNA methylation's significance in human growth, development and disease, and its role in regulating Mtb's evolution and infection processes. Additionally, it discusses potential applications of DNA methylation research in tuberculosis.

Intelligent scoring system based on dynamic optical breast imaging for early detection of breast cancer

Early detection of breast cancer can significantly improve patient outcomes and five-year survival in clinical screening. Dynamic optical breast imaging (DOBI) technology reflects the blood oxygen metabolism level of tumors based on the theory of tumor neovascularization, which offers a technical possibility for early detection of breast cancer. In this paper, we propose an intelligent scoring system integrating DOBI features assessment and a malignancy score grading reporting system for early detection of breast cancer. Specifically, we build six intelligent feature definition models to depict characteristics of regions of interest (ROIs) from location, space, time and context separately. Similar to the breast imaging-reporting and data system (BI-RADS), we conclude the malignancy score grading reporting system to score and evaluate ROIs as follows: Malignant (≥ 80 score), Likely Malignant (60-80 score), Intermediate (35-60 score), Likely Benign (10-35 score), and Benign (<10 score). This system eliminates the influence of subjective physician judgments on the assessment of the malignant probability of ROIs. Extensive experiments on 352 Chinese patients demonstrate the effectiveness of the proposed system compared to state-of-the-art methods.

Ultrasensitive and Quantitative DNA Methylation Detection Method Based on the MutS Protein

DNA methylation is closely related to cancer. It is generally accepted that DNA methylation detection is crucial in cancer diagnosis, prognosis, and treatment monitoring. Therefore, there is an urgent demand for developing a simple, rapid, highly sensitive, and highly specific methylation detection method to detect DNA methylation at specific sites quantitatively. In this work, we introduce a DNA methylation detection method based on MutS and methylation-specific PCR, named MutS-based methylation-specific PCR (MB-MSP), which has the advantages of simplicity, speed, high specificity, sensitivity, and broad applicability. Utilizing the MutS's ability to bind mismatched base pairs, we inhibit not only the amplification of unmethylated DNA but also nonspecific primer amplification. We achieved a detection sensitivity of 0.5% for the methylated genes of ACP1, CLEC11A, and SEPT9 by MB-MSP. It has a good linear relationship and a detection time of only 1.5 h. To validate the feasibility of the MB-MSP method in clinical application, we conducted methylation detection on plasma-circulating tumor DNA samples from 10 liver cancer patients and 5 healthy people, achieving a 100% accuracy rate. In conclusion, MB-MSP, as a novel and reliable DNA methylation detection tool, holds significant application value and potential for advancing early cancer diagnosis.

Ultrasensitive electrochemical detection and inhibition evaluation of DNA methyltransferase based on cascade strand displacement amplification

An electrochemical sensing approach for ultrasensitive DNA methyltransferase (MTase) activity assay is proposed. After specific cleavage reaction in the presence of a methylated state, strand displacement polymerization (SDP) is initiated in the solution. The product of upstream SDP further triggers downstream SDP, which enriches abundant electrochemical species at the electrode. The whole process is quite convenient with shared enzymes. Due to the cascade signal amplification, ultrahigh sensitivity is promised. Inhibitor screening results are also demonstrated to be good. Besides, target MTase can be accurately determined in human serum samples, confirming excellent practical utility. This work provides a reliable approach for the analysis of MTase activity, which is of vital importance for related biological studies and clinical applications.

Imaging and AI based chromatin biomarkers for diagnosis and therapy evaluation from liquid biopsies

Multiple genomic and proteomic studies have suggested that peripheral blood mononuclear cells (PBMCs) respond to tumor secretomes and thus could provide possible avenues for tumor prognosis and treatment evaluation. We hypothesized that the chromatin organization of PBMCs obtained from liquid biopsies, which integrates secretome signals with gene expression programs, provides efficient biomarkers to characterize tumor signals and the efficacy of proton therapy in tumor patients. Here, we show that chromatin imaging of PBMCs combined with machine learning methods provides such robust and predictive chromatin biomarkers. We show that such chromatin biomarkers enable the classification of 10 healthy and 10 pan-tumor patients. Furthermore, we extended our pipeline to assess the tumor types and states of 30 tumor patients undergoing (proton) radiation therapy. We show that our pipeline can thereby accurately distinguish between three tumor groups with up to 89% accuracy and enables the monitoring of the treatment effects. Collectively, we show the potential of chromatin biomarkers for cancer diagnostics and therapy evaluation.