Diagnostic Power of DNA Methylation Classifiers for Early Detection of Cancer

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.

Liquid biopsy: An arsenal for tumour screening and early diagnosis

Cancer has become the second leading cause of death in the world, and more than 50% of cancer patients are diagnosed at an advanced stage. Early diagnosis of tumours is the key to improving patient quality of life and survival time and reducing the socioeconomic burden. However, there is still a lack of reliable early diagnosis methods in clinical practice. In recent years, liquid biopsy technology has developed rapidly. It has the advantages of noninvasiveness, easy access to sample sources, and reproducibility. It has become the main focus of research on the early diagnosis methods of tumours. This review summarises the research progress of existing liquid biopsy markers, such as circulating tumour DNA, circulating viral DNA, DNA methylation, circulating tumour cells, circulating RNA, exosomes, and tumour education platelets in early diagnosis of tumours, and analyses the current advantages and limitations of various markers, providing a direction for the application and transformation of liquid biopsy research in early diagnosis of clinical tumours.

Proteomic characterization of head and neck paraganglioma and its molecular classification

Background

Head and neck paragangliomas (HNPGLs) are rare neuroendocrine tumors that pose significant challenges in both diagnosis and treatment. The pathogenic mechanism remains unclear, and there is no proteomic analysis-based molecular classification. Therefore, gaining a deeper understanding of this disease from the protein level is crucial because proteins play a fundamental role in the occurrence and development of tumors.

Methods

We collected 44 tumor samples from patients diagnosed with HNPGL. The adrenal paraganglioma tissue (N = 46) was used as the disease control group and the chorda tympani nerves (N = 18) were used as the control group. High-pH reversed-phase liquid chromatography and liquid chromatography with tandem mass spectrometry analyses were used to build an integrated protein database of tumor samples. We then obtained two sets of differentially expressed proteins between the tumor group and the control group to identify the unique proteomic signatures of HNPGLs. Ingenuity pathway analysis annotations were used to perform the functional analysis. Subsequently, we developed a clinically relevant molecular classification for HNPGLs that connected the clinical characteristics with meaningful proteins and pathways to explain the varied clinical manifestations.

Results

We identified 6,640 proteins in the HNPGL group, and 314 differentially expressed proteins unique to HNPGL were discovered via inter-group comparison. We identified two HNPGL subgroups that significantly differed in clinical manifestation and proteomic characteristics. On the basis of the proteomic results, we proposed a pathogenic mechanism underlying HNPGL.

Conclusion

We conducted a comprehensive analysis of the molecular mechanisms of HNPGL to build, for the first time, a clinically relevant molecular classification. By focusing on differential proteomic analyses between different types of paragangliomas, we were able to obtain a comprehensive description of the proteomic characteristics of HNPGL, which will be valuable for the search for significant biomarkers as a new treatment method for HNPGL.

Hypermethylated TAGMe as a universal-cancer-only methylation marker and its application in diagnosis and recurrence monitoring of urothelial carcinoma

BACKGROUND

Urothelial carcinoma (UC) is the second most common urological malignancy. Despite numerous molecular markers have been evaluated during the past decades, no urothelial markers for diagnosis and recurrence monitoring have shown consistent clinical utility.

METHODS

The methylation level of tissue samples from public database and clinical collected were analyzed. Patients with UC and benign diseases of the urinary system (BUD) were enrolled to establish TAGMe (TAG of Methylation) assessment in a training cohort (n = 567) using restriction enzyme-based bisulfite-free qPCR. The performance of TAGMe assessment was further verified in the validation cohort (n = 198). Urine samples from 57 UC patients undergoing postoperative surveillance were collected monthly for six months after surgery to assess the TAGMe methylation.

RESULTS

We identified TAGMe as a potentially novel Universal-Cancer-Only Methylation (UCOM) marker was hypermethylated in multi-type cancers and investigated its application in UC. Restriction enzyme-based bisulfite-free qPCR was used for detection, and the results of which were consistent with gold standard pyrosequencing. Importantly, hypermethylated TAGMe showed excellent sensitivity of 88.9% (95% CI: 81.4-94.1%) and specificity of 90.0% (95% CI: 81.9-95.3%) in efficiently distinguishing UC from BUD patients in urine and also performed well in different clinical scenarios of UC. Moreover, the abnormality of TAGMe as an indicator of recurrence might precede clinical recurrence by three months to one year, which provided an invaluable time window for timely and effective intervention to prevent UC upstaging.

CONCLUSION

TAGMe assessment based on a novel single target in urine is effective and easy to perform in UC diagnosis and recurrence monitoring, which may reduce the burden of cystoscopy. Trial registration ChiCTR2100052507. Registered on 30 October 2021.

Combining non-invasive liquid biopsy and a methylation analysis to assess surgical risk for early esophageal cancer

Background

While the widespread use of endoscopic submucosal dissection (ESD) has significantly reduced the incidence of early esophageal cancer (ESCA), the limited ability of ESD to strip deep infiltrating esophageal lesions results in a considerable risk of intraoperative perforation. Circulating-free DNA (cfDNA) is widely used in modern tumor screening due to its non-invasive detection capabilities. A methylation analysis offers vital insights into the condition and advancement of malignancies due to its unique positioning, such as a marker of cancer. This study investigated the potential of combining a non-invasive liquid biopsy technique, along with a methylation analysis, to assess the surgical perforation risk of ESCA patients.

Methods

In this study, we conducted an analysis of gene expression differences between stage I esophageal squamous carcinoma samples and healthy tissue samples using data from The Cancer Genome Atlas (TCGA) database. We also identified the genes associated with progression-free survival (PFS) in esophageal squamous carcinoma. Integrating the framework of the methylation analysis, we explored the methylated sites of these distinct genes. To refine this process, we used the Shiny Methylation Analysis Resource Tool (SMART) to conduct a comprehensive analysis of these sites. We then confirmed the stability of the methylation sites in different lesion conditions using methylation-specific quantitative polymerase chain reaction (MS-qPCR) with paraffin tissue samples collected after ESD.

Results

We analyzed RNA-sequencing data from 42 early stage ESCA patients and 17 controls, identifying 1,263 up-regulated and 460 down-regulated genes. Functional analyses revealed involvement in key pathways such as cell cycle regulation and immune responses. Furthermore, we identified 38 differentially expressed genes associated with PFS. Using SMART analysis, we found 217 hyper-methylated regions in 38 genes, suggesting potential early markers for ESCA. Validation experiments confirmed the reliability of 29 hyper-methylated regions in FFPE tissue samples and 6 regions in cfDNA. A LunaCAM model showed high accuracy [area under the curve (AUC) =0.89] in discriminating early ESCA. Integrated assessment of six highly methylated regions significantly improved predictive performance, with 90.56% sensitivity, highlighting the importance of combinatorial biomarker evaluation for early cancer detection.

Conclusions

This study established a novel approach that integrates non-invasive testing with a methylation analysis to assess the surgical risk of early ESCA patients. The significance of changes in methylation sites in relation to lesion status should not be underestimated, as they have the potential to offer vital insights for proactive risk assessments before surgery.

Evaluating circulating cell-free DNA and DNA integrity index as biomarkers in non-small cell lung cancer

BACKGROUND

Analysis of free DNA molecules shed from tumour cells in plasma of patients referred as circulating tumour DNA (ctDNA) with reference to physiological circulating cell-free DNA (cfDNA) is nowadays exploited as liquid biopsy and is considered a new emerging promising biomarker for diagnosis, selection of proper treatment, and prognosis of cancer. DNA integrity index (DII) is assessed by calculating the ratio between the concentration of long cfDNA strands released from tumour cells (ALU247) and the short strands released from normal cells (ALU115). The aim of the current study was to evaluate DII as a potential diagnostic and prognostic biomarker of NSCLC.

METHODS

Our study included 48 NSCLC patients diagnosed as primary NSCLC before starting treatment, 30 COPD patients diagnosed clinically, radiologically, and subjected to chest high-resolution computerized tomography, and 40 healthy controls. cfDNA concentration and DII were measured by quantitative real-time polymerase chain reaction (qPCR).

RESULTS

ALU115, ALU247, and DII were significantly higher in NSCLC compared to COPD patients (p < 0.0001) and controls (p < 0.0001) and in COPD patients compared to control subjects (p < 0.0001). DII positively correlated with the stage of tumour (p = 0.01), tumour metastasis (p = 0.004), and with adenocarcinoma compared to other histopathological types (p = 0.02). To evaluate clinical utility of DII in NSCLC, ROC curve analysis demonstrated an AUC of 0.91 at a cut-off value of 0.44 with total accuracy = 85.6%, sensitivity = 90%, specificity = 83%, PPV = 78.1%, and NPV = 92.1%.

CONCLUSION

cfDNA and DII represent a promising diagnostic and prognostic tool in NSCLC. This type of noninvasive liquid biopsy revealed its chance in the screening, early diagnosis, and monitoring of NSCLC.

Running in the FAMILY: understanding and predicting the intergenerational transmission of mental illness

Over 50% of children with a parent with severe mental illness will develop mental illness by early adulthood. However, intergenerational transmission of risk for mental illness in one's children is insufficiently considered in clinical practice, nor is it sufficiently utilised into diagnostics and care for children of ill parents. This leads to delays in diagnosing young offspring and missed opportunities for protective actions and resilience strengthening. Prior twin, family, and adoption studies suggest that the aetiology of mental illness is governed by a complex interplay of genetic and environmental factors, potentially mediated by changes in epigenetic programming and brain development. However, how these factors ultimately materialise into mental disorders remains unclear. Here, we present the FAMILY consortium, an interdisciplinary, multimodal (e.g., (epi)genetics, neuroimaging, environment, behaviour), multilevel (e.g., individual-level, family-level), and multisite study funded by a European Union Horizon-Staying-Healthy-2021 grant. FAMILY focuses on understanding and prediction of intergenerational transmission of mental illness, using genetically informed causal inference, multimodal normative prediction, and animal modelling. Moreover, FAMILY applies methods from social sciences to map social and ethical consequences of risk prediction to prepare clinical practice for future implementation. FAMILY aims to deliver: (i) new discoveries clarifying the aetiology of mental illness and the process of resilience, thereby providing new targets for prevention and intervention studies; (ii) a risk prediction model within a normative modelling framework to predict who is at risk for developing mental illness; and (iii) insight into social and ethical issues related to risk prediction to inform clinical guidelines.

Exploring TSPAN4 promoter methylation as a diagnostic biomarker for tuberculosis

Background

Tuberculosis (TB), caused by Mycobacterium tuberculosis (Mtb), is a persistent infectious disease threatening human health. The existing diagnostic methods still have significant shortcomings, including a low positivity rate in pathogen-based diagnoses and the inability of immunological diagnostics to detect active TB. Hence, it is urgent to develop new techniques to detect TB more accurate and earlier. This research aims to scrutinize and authenticate DNA methylation markers suitable for tuberculosis diagnosis. Concurrently, Providing a new approach for tuberculosis diagnosis.

Methods

Blood samples from patients with newly diagnosed tuberculosis and healthy controls (HC) were utilized in this study. Examining methylation microarray data from 40 whole blood samples (22TB + 18HC), we employed two procedures: signature gene methylated position analysis and signature region methylated position analysis to pinpoint distinctive methylated positions. Based on the screening results, diagnostic classifiers are constructed through machine learning, and validation was conducted through pyrosequencing in a separate queue (22TB + 18HC). Culminating in the development of a new tuberculosis diagnostic method via quantitative real-time methylation specific PCR (qMSP).

Results

The combination of the two procedures revealed a total of 10 methylated positions, all of which were located in the promoter region. These 10 signature methylated positions facilitated the construction of a diagnostic classifier, exhibiting robust diagnostic accuracy in both cross-validation and external test sets. The LDA model demonstrated the best classification performance, achieving an AUC of 0.83, specificity of 0.8, and sensitivity of 0.86 on the external test set. Furthermore, the validation of signature methylated positions through pyrosequencing demonstrated high agreement with screening outcomes. Additionally, qMSP detection of 2 potential hypomethylated positions (cg04552852 and cg12464638) exhibited promising results, yielding an AUC of 0.794, specificity of 0.720, and sensitivity of 0.816.

Conclusion

Our study demonstrates that the validated signature methylated positions through pyrosequencing emerge as plausible biomarkers for tuberculosis diagnosis. The specific methylation markers in the TSPAN4 gene, identified in whole blood samples, hold promise for improving tuberculosis diagnosis. This approach could significantly enhance diagnostic accuracy and speed, offering a new avenue for early detection and treatment.

Novel 3D-Printed Microfluidic Magnetic Platform for Rapid DNA Isolation

This study presents a novel miniaturized device as a 3D-printed microfluidic magnetic platform specifically designed to manipulate magnetic microparticles in a microfluidic chip for rapid deoxyribonucleic acid (DNA) isolation. The novel design enables the movement of the magnetic particles in the same or opposite directions with the flow or suspends them in continuous flow. A computational model was developed to assess the effectiveness of the magnetic manipulation of the particles. Superparamagnetic monodisperse silica particles synthesized in-house are utilized for the isolation of fish sperm DNA and human placenta DNA. It was demonstrated that the proposed platform can perform DNA isolation within 10 min with an isolation efficiency of 50% at optimum operating conditions.

MethMarkerDB: a comprehensive cancer DNA methylation biomarker database

DNA methylation plays a crucial role in tumorigenesis and tumor progression, sparking substantial interest in the clinical applications of cancer DNA methylation biomarkers. Cancer-related whole-genome bisulfite sequencing (WGBS) data offers a promising approach to precisely identify these biomarkers with differentially methylated regions (DMRs). However, currently there is no dedicated resource for cancer DNA methylation biomarkers with WGBS data. Here, we developed a comprehensive cancer DNA methylation biomarker database (MethMarkerDB, https://methmarkerdb.hzau.edu.cn/), which integrated 658 WGBS datasets, incorporating 724 curated DNA methylation biomarker genes from 1425 PubMed published articles. Based on WGBS data, we documented 5.4 million DMRs from 13 common types of cancer as candidate DNA methylation biomarkers. We provided search and annotation functions for these DMRs with different resources, such as enhancers and SNPs, and developed diagnostic and prognostic models for further biomarker evaluation. With the database, we not only identified known DNA methylation biomarkers, but also identified 781 hypermethylated and 5245 hypomethylated pan-cancer DMRs, corresponding to 693 and 2172 genes, respectively. These novel potential pan-cancer DNA methylation biomarkers hold significant clinical translational value. We hope that MethMarkerDB will help identify novel cancer DNA methylation biomarkers and propel the clinical application of these biomarkers.

Critical Factors in the Analytical Work Flow of Circulating Tumor DNA-Based Molecular Profiling

BACKGROUND

Liquid biopsy testing, especially molecular tumor profiling of circulating tumor DNA (ctDNA) in cell-free plasma, has received increasing interest in recent years as it serves as a reliable alternative for the detection of tumor-specific aberrations to guide treatment decision-making in oncology. Many (commercially available) applications have been developed, however, broad divergences in (pre)analytical work flows and lack of universally applied guidelines impede routine clinical implementation. In this review, critical factors in the blood-based ctDNA liquid biopsy work flow are evaluated.

CONTENT

In the preanalytical phase, several aspects (e.g., blood collection tubes [BCTs], plasma processing, and extraction method) affect the quantity and quality of the circulating cell-free DNA (ccfDNA) applicable for subsequent molecular analyses and should meet certain standards to be applied in diagnostic work flows. Analytical considerations, such as analytical input and choice of assay, might vary based on the clinical application (i.e., screening, primary diagnosis, minimal residual disease [MRD], response monitoring, and resistance identification). In addition to practical procedures, variant interpretation and reporting ctDNA results should be harmonized. Collaborative efforts in (inter)national consortia and societies are essential for the establishment of standard operating procedures (SOPs) in attempts to standardize the plasma-based ctDNA analysis work flow.

SUMMARY

Development of universally applicable guidelines regarding the critical factors in liquid biopsy testing are necessary to pave the way to clinical implementation for routine diagnostics.

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.

Recent insights into the nutritional immunomodulation of cancer-related microRNAs

Cancer is the most common cause of death worldwide, following cardiovascular diseases. Cancer is a multifactorial disease and many reasons such as physical, chemical, biological, and lifestyle-related factors. Nutrition, which is one of the various factors that play a role in the prevention, development, and treatment of many types of cancer, affects the immune system, which is characterized by disproportionate pro-inflammatory signaling in cancer. Studies investigating the molecular mechanisms of this effect have shown that foods rich in bioactive compounds, such as green tea, olive oil, turmeric, and soybean play a significant role in positively changing the expression of miRNAs involved in the regulation of genes associated with oncogenic/tumor-suppressing pathways. In addition to these foods, some diet models may change the expression of specific cancer-related miRNAs in different ways. While Mediterranean diet has been associated with anticancer effects, a high-fat diet, and a methyl-restricted diet are considered to have negative effects. This review aims to discuss the effects of specific foods called "immune foods," diet models, and bioactive components on cancer by changing the expression of miRNAs in the prevention and treatment of cancer.

Detection of diagnostic and prognostic methylation-based signatures in liquid biopsy specimens from patients with meningiomas

Recurrence of meningiomas is unpredictable by current invasive methods based on surgically removed specimens. Identification of patients likely to recur using noninvasive approaches could inform treatment strategy, whether intervention or monitoring. In this study, we analyze the DNA methylation levels in blood (serum and plasma) and tissue samples from 155 meningioma patients, compared to other central nervous system tumor and non-tumor entities. We discover DNA methylation markers unique to meningiomas and use artificial intelligence to create accurate and universal models for identifying and predicting meningioma recurrence, using either blood or tissue samples. Here we show that liquid biopsy is a potential noninvasive and reliable tool for diagnosing and predicting outcomes in meningioma patients. This approach can improve personalized management strategies for these patients.

Diagnostic value of exfoliated tumor cells combined with DNA methylation in bronchoalveolar lavage fluid for lung cancer

BACKGROUND

To evaluate the diagnostic value of exfoliated tumor cells (ETCs) numbers combined with DNA methylation levels in bronchoalveolar lavage fluid (BALF) in lung cancer.

METHODS

BALF samples were collected from 43 patients with lung cancer and 23 with benign lung disease. ETCs were detected by the nano-enrichment method, and the methylation status of the short stature homeobox gene 2 (SHOX2) and the RAS association domain family 1, isoform A (RASSF1A) gene were detected by RT-PCR. The diagnostic value of each metric was evaluated by receiver operating characteristic curve analysis, specificity and sensitivity.

RESULTS

The sensitivity/specificity of RASSF1A and SHOX2 methylation detection were 44.12%/76.47% and 93.75%/87.50%, respectively. When "RASSF1A/SHOX2 methylation" was used as a positive result, the sensitivity increased to 88.24%, and the specificity decreased to 81.25%. When "RASSF1A + SHOX methylation" was used as positive, the sensitivity was reduced to 32.35%, but the specificity was increased to 100.00%. The sensitivity and specificity of ETCs detection in BALF were 89.47% and 16.67%, respectively. When "SHOX2/RASSF1A methylation + ETCs was used as a positive result, the sensitivity and specificity of the detection were 79.31% and 81.82%, respectively. When "SHOX2 + RASSF1A + ETCs" was used as positive, the sensitivity was 34.48% and the specificity was 90.91%. Receiver operating characteristic curve analysis showed that when SHOX2, RASSF1A methylation and ETCs were combined, the diagnostic sensitivity increased to 0.778.

CONCLUSION

ETCs counting in combination with SHOX2 and RASSF1A methylation assays in BALF samples has demonstrated excellent sensitivity for lung cancer diagnosis and is an effective complementary tool for clinical diagnosis of lung cancer.

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

The immune system can monitor tumor development, and DNA methylation is involved in the body's immune response to tumors. In this work, we investigate whether DNA methylation alterations in peripheral blood mononuclear cells (PBMCs) could be used as markers for early detection of breast cancer (BC) from the perspective of tumor immune alterations. We identify four BC-specific methylation markers by combining Infinium 850 K BeadChips, pyrosequencing and targeted bisulfite sequencing. Based on the four methylation markers in PBMCs of BC, we develop an efficient and convenient multiplex methylation-specific quantitative PCR assay for the detection of BC and validate its diagnostic performance in a multicenter cohort. This assay was able to distinguish early-stage BC patients from normal controls, with an AUC of 0.940, sensitivity of 93.2%, and specificity of 90.4%. More importantly, this assay outperformed existing clinical diagnostic methods, especially in the detection of early-stage and minimal tumors.

A systematic review of neuroimaging epigenetic research: calling for an increased focus on development

Epigenetic mechanisms, such as DNA methylation (DNAm), have gained increasing attention as potential biomarkers and mechanisms underlying risk for neurodevelopmental, psychiatric and other brain-based disorders. Yet, surprisingly little is known about the extent to which DNAm is linked to individual differences in the brain itself, and how these associations may unfold across development - a time of life when many of these disorders emerge. Here, we systematically review evidence from the nascent field of Neuroimaging Epigenetics, combining structural or functional neuroimaging measures with DNAm, and the extent to which the developmental period (birth to adolescence) is represented in these studies. We identified 111 articles published between 2011-2021, out of which only a minority (21%) included samples under 18 years of age. Most studies were cross-sectional (85%), employed a candidate-gene approach (67%), and examined DNAm-brain associations in the context of health and behavioral outcomes (75%). Nearly half incorporated genetic data, and a fourth investigated environmental influences. Overall, studies support a link between peripheral DNAm and brain imaging measures, but there is little consistency in specific findings and it remains unclear whether DNAm markers present a cause, correlate or consequence of brain alterations. Overall, there is large heterogeneity in sample characteristics, peripheral tissue and brain outcome examined as well as the methods used. Sample sizes were generally low to moderate (median nall = 98, ndevelopmental = 80), and attempts at replication or meta-analysis were rare. Based on the strengths and weaknesses of existing studies, we propose three recommendations on how advance the field of Neuroimaging Epigenetics. We advocate for: (1) a greater focus on developmentally oriented research (i.e. pre-birth to adolescence); (2) the analysis of large, prospective, pediatric cohorts with repeated measures of DNAm and imaging to assess directionality; and (3) collaborative, interdisciplinary science to identify robust signals, triangulate findings and enhance translational potential.

Diagnostic performance of RASSF1A and SHOX2 methylation combined with EGFR mutations for differentiation between small pulmonary nodules

BACKGROUND AND AIM

Aberrant methylation of Ras association domain family 1, isoform A (RASSF1A), and short-stature homeobox gene 2 (SHOX2) promoters has been validated as a pair of valuable biomarkers for diagnosing early lung adenocarcinomas (LUADs). Epidermal growth factor receptor (EGFR) is the key driver mutation in lung carcinogenesis. This study aimed to investigate the aberrant promoter methylation of RASSF1A and SHOX2, and the genetic mutation of EGFR in 258 specimens of early LUADs.

METHODS

We retrospectively selected 258 paraffin-embedded samples of pulmonary nodules measuring 2 cm or less in diameter and evaluated the diagnostic performance of individual biomarker assays and multiple panels between noninvasive (group 1) and invasive lesions (groups 2A and 2B). Then, we investigated the interaction between genetic and epigenetic alterations.

RESULTS

The degree of RASSF1A and SHOX2 promoter methylation and EGFR mutation was significantly higher in invasive lesions than in noninvasive lesions. The three biomarkers distinguished between noninvasive and invasive lesions with reliable sensitivity and specificity: 60.9% sensitivity [95% confidence interval (CI) 52.41-68.78] and 80.0% specificity (95% CI 72.14-86.07). The novel panel biomarkers could further discriminate among three invasive pathological subtypes (area under the curve value > 0.6). The distribution of RASSF1A methylation and EGFR mutation was considerably exclusive in early LUAD (P = 0.002).

CONCLUSION

DNA methylation of RASSF1A and SHOX2 is a pair of promising biomarkers, which may be used in combination with other driver alterations, such as EGFR mutation, to support the differential diagnosis of LUADs, especially for stage I.

Pan-cancer analysis of aldolase B gene as a novel prognostic biomarker for human cancers

Aldolase B (ALDOB) gene is essential for the process of glycolysis and differentially expressed in cancers. The aims of this study were to explore the potential role of ALDOB in pan-cancer, in order to deepen the research on the pathological mechanism of cancer. Hence, we used several online tools (TIMER2, GEPIA2, UALCAN, cBioPortal, and MXPRESS) and R language to identify the correlation between the ALDOB expression and survival analysis, genetic alteration, DNA methylation, and immune cell infiltration based on The Cancer Genome Atlas project. The results showed that ALDOB was lowly expressed in pan-cancer. Survival analysis revealed that low expression of ALDOB was markedly related with poor clinical prognosis, while the genetic alteration within ALDOB changed along with the difference of overall survival (OS) and disease-free survival (DFS) prognosis in several cancers. A possible relationship between DNA methylation and ALDOB expression for several tumors was found. Besides, ALDOB expression was confirmed to be associated with tumor immune cell infiltration, especially in breast invasive carcinoma (BRCA), esophageal carcinoma (ESCA), and testicular germ cell tumors (TGCT) cases. Further, the enrichment analysis demonstrated that metabolic pathway was closely related to ALDOB expression. Our results provide a comprehensive pan-cancer analysis and suggest ALDOB could act as a promising tumor predictive biomarker for human cancer.

Low-dose arecoline regulates distinct core signaling pathways in oral submucous fibrosis and oral squamous cell carcinoma

BACKGROUND

Betel nut chewing plays a role in the pathogenesis of oral submucous fibrosis (OSF) and oral squamous cell carcinoma (OSCC). As the major active ingredient of the betel nut, the effect of arecoline and its underlying mechanism to OSF and OSCC pathogenesis remain unclear.

METHODS

Next-generation sequencing-based transcriptome and dRRBS analysis were performed on OSF and OSCC cells under low-dose arecoline exposure. Functional analyses were performed to compare the different roles of arecoline during OSF and OSCC pathogenesis, and key genes were identified.

RESULTS

In this study, we identified that low-dose arecoline promoted cell proliferation of both NFs and OSCC cells via the acceleration of cell cycle progression, while high-dose arecoline was cytotoxic to both NFs and OSCC cells. We performed for the first time the transcriptome and methylome landscapes of NFs and OSCC cells under low-dose arecoline exposure. We found distinct transcriptome and methylome profiles mediated by low-dose arecoline in OSF and OSCC cells, as well as specific genes and signaling pathways associated with metabolic disorders induced by low-dose arecoline exposure. Additionally, low-dose arecoline displayed different functions at different stages, participating in the modulation of the extracellular matrix via Wnt signaling in NFs and epigenetic regulation in OSCC cells. After exposure to low-dose arecoline, the node roles of FMOD in NFs and histone gene clusters in OSCC cells were found. Meanwhile, some key methylated genes induced by arecoline were also identified, like PTPRM and FOXD3 in NFs, SALL3 and IRF8 in OSCC cells, indicating early molecular events mediated by arecoline during OSF and OSCC pathogenesis.

CONCLUSIONS

This study elucidated the contribution of low-dose arecoline to OSF and OSCC pathogenesis and identified key molecular events that could be targeted for further functional studies and their potential as biomarkers.

Minimally invasive approaches for the early detection of endometrial cancer

Endometrial cancer (EC) is one of the most common gynecologic cancers and its incidence is rising globally. Although advanced EC has a poor prognosis; diagnosing EC at an earlier stage could improve long-term patient outcomes. However, there is no consensus on the early detection strategies for EC and the current diagnostic practices such as transvaginal ultrasound, hysteroscopy and endometrial biopsy are invasive, costly and low in specificity. Thus, accurate and less invasive screening tests that detect EC in women with early stages of the disease are needed. Current research has revolutionized novel EC early detection methodologies in many aspects. This review aims to comprehensively characterizes minimally invasive screening techniques that can be applied to EC in the future, and fully demonstrate their potential in the early detection of EC.

Cell-free DNA methylation biomarker for the diagnosis of papillary thyroid carcinoma

BACKGROUND

Cell-free DNA (cfDNA) is being explored as biomarker for non-invasive diagnosis of cancer. We aimed to establish a cfDNA-based DNA methylation marker panel to differentially diagnose papillary thyroid carcinoma (PTC) from benign thyroid nodule (BTN).

METHODS

220 PTC- and 188 BTN patients were enrolled. Methylation markers of PTC were identified from patients' tissue and plasma by reduced representation bisulfite sequencing and methylation haplotype analyses. They were combined with PTC markers from literatures and were tested on additional PTC and BTN samples to verify PTC-detecting ability using targeted methylation sequencing. Top markers were developed into ThyMet and were tested in 113 PTC and 88 BTN cases to train and validate a PTC-plasma classifier. Integration of ThyMet and thyroid ultrasonography was explored to improve accuracy.

FINDINGS

From 859 potential PTC plasma-discriminating markers that include 81 markers identified by us, the top 98 most PTC plasma-discriminating markers were selected for ThyMet. A 6-marker ThyMet classifier for PTC plasma was trained. In validation it achieved an Area Under the Curve (AUC) of 0.828, similar to thyroid ultrasonography (0.833) but at higher specificity (0.722 and 0.625 for ThyMet and ultrasonography, respectively). A combinatorial classifier by them, ThyMet-US, improved AUC to 0.923 (sensitivity = 0.957, specificity = 0.708).

INTERPRETATION

The ThyMet classifier improved the specificity of differentiating PTC from BTN over ultrasonography. The combinatorial ThyMet-US classifier may be effective in preoperative diagnosis of PTC.

FUNDING

This work was supported by the grants from National Natural Science Foundation of China (82072956 and 81772850).

Development of novel DNAJB6-KIAA1522-p-mTOR three-protein prognostic prediction models for CRC

BACKGROUND

To evaluate the prognostic value of DNAJB6, KIAA1522, and p-mTOR expression for colorectal cancer (CRC) and to develop effective prognostic models for CRC patients.

METHODS

The expression of DNAJB6, KIAA1522, and p-mTOR (Ser2448) was detected using immunohistochemistry in 329 CRC specimens. The prognostic values of the three proteins in the training cohort were assessed using Kaplan-Meier curves and univariate and multivariate Cox proportional hazards models. Prediction nomogram models integrating the three proteins and TNM stage were constructed. Subsequently, calibration curves, receiver operating characteristic (ROC) curves, the concordance index (C-index), and decision curve analysis (DCA) were used to evaluate the performance of the nomograms in the training and validation cohorts.

RESULTS

The three proteins DNAJB6, KIAA1522, and p-mTOR were significantly overexpressed in CRC tissues (each P < 0.01), and their expression was an independent prognostic factor for overall survival (OS) and disease-free survival (DFS) (each P < 0.05). The area under the ROC curves (AUC) and C-index values were approximately 0.7. Additionally, the calibration curves showed that the predicted values and the actual values fit well. Furthermore, DCA curves indicated that the clinical value of the nomogram models was higher than that of TNM stage. Overall, the novel prediction models have good discriminability, sensitivity, specificity and clinical utility.

CONCLUSION

The nomograms containing DNAJB6, KIAA1522, and p-mTOR may be promising models for predicting postoperative survival in CRC.

Performance of a targeted methylation-based multi-cancer early detection test by race and ethnicity

Disparities in cancer screening and outcomes based on factors such as sex, socioeconomic status, and race and ethnicity in the United States are well documented. A blood-based multi-cancer early detection (MCED) test that detects a shared cancer signal across multiple cancer types and also predicts the cancer signal origin was developed and validated in the Circulating Cell-free Genome Atlas study (CCGA; NCT02889978). CCGA is a prospective, multicenter, case-control, observational study with longitudinal follow-up (overall N = 15,254). In this pre-specified, exploratory, descriptive analysis, test performance was evaluated among racial and ethnic groups. Overall, 4077 participants comprised the independent validation set with confirmed cancer status (cancer: n = 2823; non-cancer: n = 1254). Participants were stratified into the following racial/ethnic groups: Black (non-Hispanic), Hispanic (all races), Other (non-Hispanic), Other/unknown and White (non-Hispanic). Cancer and non-cancer participants were predominantly White (n = 2316, 82.0% and n = 996, 79.4%, respectively). Across groups, specificity for cancer signal detection ranged from 98.1% [n = 103; 95% CI: 93.2-99.5%] to 100% [n = 85; 95% CI: 95.7-100.0%]. The sensitivity for cancer signal detection across groups ranged from 43.9% [n = 57; 95% CI: 31.8-56.7%] to 63.0% [n = 192; 95% CI: 56.0-69.5%] and generally increased with clinical stage. The MCED test had consistently high specificity and similar sensitivity across racial and ethnic groups, though results are limited by sample size for some groups. Results support the broad applicability of this MCED test and clinical implementation on a population scale as a complement to standard screening.

A gene signature driven by abnormally methylated DEGs was developed for TP53 wild-type ovarian cancer samples by integrative omics analysis of DNA methylation and gene expression data

Background

Integrated omics analysis based on transcriptome and DNA methylation data combined with machine learning methods is very promising for the diagnosis, prognosis, and classification of cancer. In this study, the DNA methylation and gene expression data of ovarian cancer (OC) were analyzed to identify abnormally methylated differentially expressed genes (DEGs), screen potential therapeutic agents for OC, and construct a risk model based on the abnormally methylated DEGs to predict patient prognosis.

Methods

The gene expression and DNA methylation data of primary OC samples with tumor protein 53 (TP53) wild-type and normal samples were obtained from The Cancer Genome Atlas (TCGA) database. DEGs with aberrant methylation were analyzed by screening the intersection between DEGs and differentially methylated genes (DMGs). We attempted to search for potential drugs targeting DEGs with aberrant methylation by employing a network medicine framework. A gene signature based on the DEGs with aberrant methylation was constructed by regularized least absolute shrinkage and selection operator (LASSO) regression analysis.

Results

A total of 440 aberrant methylated DEGs were screened. Based on their gene expression profiles and methylation data from different regions, the results of both discriminative pattern recognition analysis and principal component analysis (PCA) showed a significant separation between tumor tissue and healthy ovarian tissue. In total, 126 potential therapeutic drugs were identified for OC by network-based proximity analysis. Five genes were identified in 440 aberrant methylated DEGs, which formed an aberrant methylated DEGs-driven gene signature. This signature could significantly distinguish the different overall survivals (OS) of OC patients and showed better predictive performance in both the training and validation sets.

Conclusions

In this study, the DNA methylation and gene expression data of OC were analyzed to identify abnormally methylated DEGs and potential therapeutic drugs, and a gene signature based on five aberrant methylation DEGs was constructed, which could better predict the risk of death in patients.

Using Circulating Tumor DNA as a Novel Biomarker to Screen and Diagnose Colorectal Cancer: A Meta-Analysis

(1) Background: Circulating tumor DNA (ctDNA) has emerged as a promising biomarker for many kinds of tumors. However, whether ctDNA could be an accurate diagnostic biomarker in colorectal cancer (CRC) remains to be clarified. The aim of this study was to evaluate the diagnostic accuracy of ctDNA in CRC. (2) Methods: PubMed, Web of Science, and Cochrane databases were searched to identify studies reporting the use of ctDNA to screen and diagnose CRC, and all relevant studies published until October 2022 were enrolled for our analysis. These studies were divided into three primer subgroups: the subgroup of quantitative or qualitative analysis of ctDNA and the subgroup of septin9 (SEPT9) methylation assay. (3) Results: A total of 79 qualified articles with 25,240 subjects were incorporated into our meta-analysis. For quantitative studies, the combined sensitivity (SEN), specificity (SPE), and diagnostic odds ratio (DOR) were 0.723 (95% CI: 0.623-0.803), 0.920 (95% CI: 0.827-0.966), and 23.305 (95% CI: 9.378-57.906), respectively, yielding an AUC of 0.860. The corresponding values for qualitative studies were 0.610 (95% CI: 0.566-0.651), 0.891 (95% CI: 0.878-0.909), 12.569 (95% CI: 9.969-15.848), and 0.823, respectively. Detection of SEPT9 methylation depicted an AUC of 0.879, with an SEN of 0.679 (95% CI: 0.622-0.732), an SPE of 0.903 (95% CI: 0.878-0.923), and a DOR of 20.121 (95% CI:14.404-28.106), respectively. (4) Conclusion: Blood-based ctDNA assay would be a potential novel biomarker for CRC screening and diagnosis. Specifically, quantitative analysis of ctDNA or qualitative analysis of SEPT9 methylation exhibited satisfying diagnostic efficiency. Larger sample studies are needed to further confirm our conclusions and to make the ctDNA approach more sensitive and specific.

Advances in early detection methods for solid tumors

During the last decade, non-invasive methods such as liquid biopsy have slowly replaced traditional imaging and invasive pathological methods used to diagnose and monitor cancer. Improvements in the available detection methods have enabled the early screening and diagnosis of solid tumors. In addition, advances in early detection methods have made the continuous monitoring of tumor progression using repeat sampling possible. Previously, the focus of liquid biopsy techniques included the following: 1) the isolation of circulating tumor cells, circulating tumor DNA, and extracellular tumor vesicles from solid tumor cells in the patient's blood; in addition to 2) analyzing genomic and proteomic data contained within the isolates. Recently, there has been a rapid devolvement in the techniques used to isolate and analyze molecular markers. This rapid evolvement in detection techniques improves their accuracy, especially when few samples are available. In addition, there is a tremendous expansion in the acquisition of samples and targets for testing; solid tumors can be detected from blood and other body fluids. Test objects have also expanded from samples taken directly from cancer to include indirect objects affected in cancer development. Liquid biopsy technology has limitations. Even so, this detection technique is the key to a new phase of oncogenetics. This review aims to provide an overview of the current advances in liquid biopsy marker selection, isolation, and detection methods for solid tumors. The advantages and disadvantages of liquid biopsy technology will also be explored.

MicroRNAs and long non-coding RNAs in pancreatic cancer: From epigenetics to potential clinical applications

MicroRNAs (miRNAs) and long non-coding RNAs (lncRNAs) are two relevant classes of non-coding RNAs (ncRNAs) that play a pivotal role in a number of molecular processes through different epigenetic regulatory mechanisms of gene expression. As a matter of fact, the altered expression of these types of RNAs leads to the development and progression of a varied range of multifactorial human diseases. Several recent reports elucidated that miRNA and lncRNAs have been implicated in pancreatic cancer (PC). For instance, dysregulation of such ncRNAs has been found to be associated with chemoresistance, apoptosis, autophagy, cell differentiation, tumor suppression, tumor growth, cancer cell proliferation, migration, and invasion in PC. Moreover, several aberrantly expressed miRNAs and lncRNAs have the potential to be used as biomarkers for accurate PC diagnosis. Additionally, miRNAs and lncRNAs are considered as promising clinical targets for PC. Therefore, in this review, we discuss recent experimental evidence regarding the clinical implications of miRNAs and lncRNAs in the pathophysiology of PC, their future potential, as well as the challenges that have arisen in this field of study in order to drive forward the design of ncRNA-based diagnostics and therapeutics for PC.

Transfer of blocker-based qPCR reactions for DNA methylation analysis into a microfluidic LoC system using thermal modeling

Changes in the DNA methylation landscape are associated with many diseases like cancer. Therefore, DNA methylation analysis is of great interest for molecular diagnostics and can be applied, e.g., for minimally invasive diagnostics in liquid biopsy samples like blood plasma. Sensitive detection of local de novo methylation, which occurs in various cancer types, can be achieved with quantitative HeavyMethyl-PCR using oligonucleotides that block the amplification of unmethylated DNA. A transfer of these quantitative PCRs (qPCRs) into point-of-care (PoC) devices like microfluidic Lab-on-Chip (LoC) cartridges can be challenging as LoC systems show significantly different thermal properties than qPCR cyclers. We demonstrate how an adequate thermal model of the specific LoC system can help us to identify a suitable thermal profile, even for complex HeavyMethyl qPCRs, with reduced experimental effort. Using a simulation-based approach, we demonstrate a proof-of-principle for the successful LoC transfer of colorectal SEPT9/ACTB-qPCR from Epi Procolon® colorectal carcinoma test, by avoidance of oligonucleotide interactions.

Circulating DNA methylation profile improves the accuracy of serum biomarkers for the detection of nonmetastatic hepatocellular carcinoma

Aim: This study exploited hepatocellular carcinoma (HCC)-specific circulating DNA methylation profiles to improve the accuracy of a current screening assay for HCC patients in high-risk populations. Methods: Differentially methylated regions in cell-free DNA between 58 nonmetastatic HCC and 121 high-risk patients with liver cirrhosis or chronic hepatitis were identified and used to train machine learning classifiers. Results: The model could distinguish HCC from high-risk non-HCC patients in a validation cohort, with an area under the curve of 0.84. Combining these markers with the three serum biomarkers (AFP, lectin-reactive AFP, des-γ-carboxy prothrombin) in a commercial test, μTASWako^®, achieved an area under the curve of 0.87 and sensitivity of 68.8% at 95.8% specificity. Conclusion: HCC-specific circulating DNA methylation markers may be added to the available assay to improve the early detection of HCC.

Epigenetics and ADHD: Reflections on Current Knowledge, Research Priorities and Translational Potential

Attention-deficit/hyperactivity disorder (ADHD) is a common and debilitating neurodevelopmental disorder influenced by both genetic and environmental factors, typically identified in the school-age years but hypothesized to have developmental origins beginning in utero. To improve current strategies for prediction, prevention and treatment, a central challenge is to delineate how, at a molecular level, genetic and environmental influences jointly shape ADHD risk, phenotypic presentation, and developmental course. Epigenetic processes that regulate gene expression, such as DNA methylation, have emerged as a promising molecular system in the search for both biomarkers and mechanisms to address this challenge. In this Current Opinion, we discuss the relevance of epigenetics (specifically DNA methylation) for ADHD research and clinical practice, starting with the current state of knowledge, what challenges we have yet to overcome, and what the future may hold in terms of methylation-based applications for personalized medicine in ADHD. We conclude that the field of epigenetics and ADHD is promising but is still in its infancy, and the potential for transformative translational applications remains a distant goal. Nevertheless, rapid methodological advances, together with the rise of collaborative science and increased availability of high-quality, longitudinal data make this a thriving research area that in future may contribute to the development of new tools for improved prediction, management, and treatment of ADHD.

Liquid biopsy for detecting epidermal growth factor receptor mutation among patients with non-small cell lung cancer treated with afatinib: a multicenter prospective study

Background

This study aimed to determine the effectiveness of liquid biopsy in detecting epidermal growth factor receptor (EGFR) mutations at diagnosis, disease progression, and intermediate stages.

Methods

This prospective, multicenter, observational study included 30 patients with non-small cell lung cancer treated with afatinib, harboring a major EGFR mutation confirmed by tumor tissue biopsy. We collected blood samples for liquid biopsy at diagnosis, intermediate stage, and progressive disease. Tissue and liquid biopsies were examined using Cobas ® EGFR Mutation Test v2.

Results

Liquid biopsy detected EGFR mutations in 63.6% of the patients at diagnosis. The presence of metastasis in the extrathoracic, brain, and adrenal glands correlated positively with the detection of EGFR mutations. Patients with positive EGFR mutations at diagnosis had significantly shorter overall and progression-free survival than patients with negative EGFR mutations. Four of the 18 patients (22.2%) who reached progressive disease had positive EGFR T790M mutations. Three of 10 patients (30.0%) with progressive disease were positive and negative for T790M using tumor re-biopsy and liquid biopsy, respectively. The results of EGFR mutation by tissue re-biopsy were the same as those of liquid biopsy in the three patients who were positive for significant EGFR mutations but negative for the T790M mutation using liquid biopsy at progressing disease. Only two patients were positive for major EGFR mutations at intermediate levels.

Conclusions

Liquid biopsy can be a prognostic factor in EGFR-tyrosine kinase inhibitor treatments at diagnosis. Tumor re-biopsy can be omitted in patients with positive EGFR mutations by liquid biopsy at PD.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-022-10135-z.

Early Detection of Cervical Cancer by Fluorescence Lifetime Imaging Microscopy Combined with Unsupervised Machine Learning

Cervical cancer has high morbidity and mortality rates, affecting hundreds of thousands of women worldwide and requiring more accurate screening for early intervention and follow-up treatment. Cytology is the current dominant clinical screening approach, and though it has been used for decades, it has unsatisfactory sensitivity and specificity. In this work, fluorescence lifetime imaging microscopy (FLIM) was used for the imaging of exfoliated cervical cells in which an endogenous coenzyme involved in metabolism, namely, reduced nicotinamide adenine dinucleotide (phosphate) [NAD(P)H], was detected to evaluate the metabolic status of cells. FLIM images from 71 participants were analyzed by the unsupervised machine learning method to build a prediction model for cervical cancer risk. The FLIM method combined with unsupervised machine learning (FLIM-ML) had a sensitivity and specificity of 90.9% and 100%, respectively, significantly higher than those of the cytology approach. One cancer recurrence case was predicted as high-risk several months earlier using this method as compared to using current clinical methods, implying that FLIM-ML may be very helpful for follow-up cancer care. This study illustrates the clinical applicability of FLIM-ML as a detection method for cervical cancer screening and a convenient tool for follow-up cancer care.

The Diagnostic Potential of SHOX2 and RASSF1A DNA Methylation in Early Lung Adenocarcinoma

Objective

Methylation of the promoters of SHOX2 and RASSF1A are potentially informative biomarkers for the diagnosis of early lung adenocarcinoma (LUAD). Abnormal methylation of SHOX2 and RASSF1A promoters may promote the occurrence and facilitate the progression of LUAD.

Materials and Methods

We selected 54 patients with early LUAD and 31 patients with benign lung nodules as a NJDT cohort and evaluated their DNA methylation and mRNA sequencing levels. The DNA methylation sequencing, mRNA sequencing, and clinical data for patients with LUAD were obtained from The Cancer Genome Atlas, and served as a TCGA cohort. We evaluated the diagnostic potential of a SHOX2 and RASSF1A combined promoter methylation assay for detection of early LUAD in the NJDT cohort. Then we explored the promoter methylation levels of SHOX2 and RASSF1A and their gene expression between normal and tumor samples at different stages in both cohorts. Pathways enriched between tumor and normal samples of methylation-positive patients in the NJDT cohort were analyzed.

Results

In the NJDT cohort, the sensitivity of the combined promoter methylation assay on tumor samples was 74.07%, the sensitivity on paired tumor and paracancerous samples was 77.78%, and the specificities in both contexts were 100%. The combined promoter methylation-positive patients had clinicopathologic features including older age, larger tumors, deeper invasion, and higher Ki-67 expression. In both cohorts, SHOX2 expression increased and RASSF1A expression decreased in tumor samples. The promoter methylation level of SHOX2 and RASSF1A was significantly higher in tumor samples at stage I-II than that in normal samples. The promoter methylation levels of these two genes were both negative associated with their expression in early tumor samples. In the NJDT cohort, methylation-positive patients of both individual SHOX2 and RASSF1A assays exhibited upregulation of folate acid metabolism and nucleotide metabolism in tumor samples. The SHOX2 methylation-positive and RASSF1A methylation-positive patients showed the downregulation of pathways related to cell proliferation and apoptosis and pathways involved in DNA repair, cell growth and cell adhesion, respectively.

Conclusion

The combined promoter methylation assay for SHOX2 and RASSF1A can be used for screening and diagnosis of early LUAD, with good sensitivity and specificity. The promoter methylation levels of SHOX2 and RASSF1A were associated with their abnormal mRNA expression, and affected DNA instability, cell proliferation, apoptosis and tumor microenvironment in patients with LUAD.

Loop-Mediated Isothermal Amplification as Point-of-Care Testing for EGFR-Mutated Lung Adenocarcinoma

Liquid biopsy has been adapted as a diagnostic test for EGFR mutations in patients with advanced or metastatic non-small cell lung cancer (NSCLC). Loop-mediated isothermal amplification (LAMP) has been widely used for the rapid detection of pathogens through DNA amplification. This study investigated the efficacy of an EGFR-LAMP assay using plasma samples of patients with resected NSCLC tumors. The EGFR status was investigated using both LAMP and next-generation sequencing (NGS) assays in cases that met the following criteria: (1) pulmonary adenocarcinoma with EGFR mutation detected by the Therascreen EGFR PCR Kit and (2) preoperative plasma samples contained enough DNA for the LAMP and NGS experiments. Among 51 specimens from patients with EGFR-mutated tumors or metastatic lymph nodes, the LAMP assay detected 1 EGFR mutation that was also detected in the NGS assay. However, a plasma sample that demonstrated EGFR wild type in the LAMP assay showed an EGFR mutant status in NGS. The detection rates (1.9% in LAMP and 3.9% in NGS) were very low in both assays, demonstrating a similar performance in detecting EGFR mutations in NSCLC tumors; therefore, it could be a more suitable test for the advanced stage, not the early stage. Notably, the LAMP assay was more time-saving, cost-effective, and straightforward. However, further investigation is required to develop a more sensitive assay.

DNA methylation-based predictors of health: applications and statistical considerations

DNA methylation data have become a valuable source of information for biomarker development, because, unlike static genetic risk estimates, DNA methylation varies dynamically in relation to diverse exogenous and endogenous factors, including environmental risk factors and complex disease pathology. Reliable methods for genome-wide measurement at scale have led to the proliferation of epigenome-wide association studies and subsequently to the development of DNA methylation-based predictors across a wide range of health-related applications, from the identification of risk factors or exposures, such as age and smoking, to early detection of disease or progression in cancer, cardiovascular and neurological disease. This Review evaluates the progress of existing DNA methylation-based predictors, including the contribution of machine learning techniques, and assesses the uptake of key statistical best practices needed to ensure their reliable performance, such as data-driven feature selection, elimination of data leakage in performance estimates and use of generalizable, adequately powered training samples.

Tumor DNA Methylation Profiles Enable Diagnosis, Prognosis Prediction, and Screening for Cervical Cancer

Background

DNA-methylation-based machine learning algorithms have demonstrated powerful diagnostic capabilities, and these tools are currently emerging in many fields of tumor diagnosis and patient prognosis prediction. This work aimed to identify novel DNA methylation diagnostic biomarkers for differentiating cervical cancer (CC) from normal tissues, as well as a prognostic prediction model to predict survival of CC patients.

Methods

The methylation profiles with the available clinical characteristics were downloaded from the Gene Expression Omnibus (GEO) database and The Cancer Genome Atlas (TCGA) program. We first screened out the differential methylation sites in CC and normal tissues and performed multiple statistical analyses to discover DNA methylation diagnostic markers that are used to distinguish CC and normal control. Then, we developed a methylation-based survival model to improve risk stratification.

Results

A diagnostic prediction panel consists of five CpG markers that could predict cervical cancer versus normal tissue with highly correct rate of 100%, and cg16428251, cg22341310, and cg23316360 which in diagnostic prediction panel all could yield high sensitivity and specificity for detection of CC and normal in six cohorts (area under curve [AUC] > 0.8), in addition to excellent performance in discriminating between CC and normal sample. The diagnostic marker panel also effectively predicted the CIN3 versus normal tissue with high accuracy in two datasets (AUC = 0.80, 0.789, respectively). Furthermore, a prognostic prediction model aggregated two CpG markers that effectively stratified the prognosis of high-risk and low-risk groups (training cohort: hazard ratio [HR] 4, 95% CI: 1.7–9.6, P = 0.0021; testing cohort: hazard ratio [HR] 1.9, 95% CI: 1.2–3.1, P = 0.0072).

Conclusion

The findings of our study showed that DNA methylation markers are of great value in the diagnosis and prognosis of CC.

Kidney-Derived Methylated PAX2 Sequences in the Urine of Healthy Subjects as a Convenient Model for Optimizing Methylation-Based Liquid biopsy

Although urine-based liquid biopsy has received considerable attention, there is a lack of a simple model to optimize assay parameters, including cell-free DNA (cfDNA) extraction, bisulfite modification, and bis-DNA recovery after conversion for methylation analysis in urine. The primary aim of this work was to establish a practical model by developing a quantitative methylation-sensitive PCR (qMS-PCR) assay for PAX2 based on hypermethylated PAX2 cfDNA that could be detected in healthy human urine. We first studied the methylation status of PAX2 in kidney tissues and whole blood, followed by an assessment of commercial kits for bisulfite conversion and bis-DNA recovery. Furthermore, we investigated the influence of urine storage and collection conditions on the preservation of methylated PAX2 in urine samples by qMS-PCR. As expected, PAX2 methylation was identified in urine but not in blood. Two commercial kits (CellCook and Zymo Research) had similar conversion efficiency and bis-DNA recovery. Urine storage for up to 5 days did not change PAX2 methylation estimates. Overall, cold storage of urine samples and the CellCook urine container maintained higher levels of methylated PAX2 compared to urine kept at room temperature and the conventional tubes, respectively. These findings highlight the importance of using the correct approaches/kits and optimizing experimental conditions as a diagnostic tool in the clinical setting. Our study provides insights on the development of urine-based liquid biopsy with DNA methylation as a universal biomarker.

Tissue-Specific Methylation Biosignatures for Monitoring Diseases: An In Silico Approach

Tissue-specific gene methylation events are key to the pathogenesis of several diseases and can be utilized for diagnosis and monitoring. Here, we established an in silico pipeline to analyze high-throughput methylome datasets to identify specific methylation fingerprints in three pathological entities of major burden, i.e., breast cancer (BrCa), osteoarthritis (OA) and diabetes mellitus (DM). Differential methylation analysis was conducted to compare tissues/cells related to the pathology and different types of healthy tissues, revealing Differentially Methylated Genes (DMGs). Highly performing and low feature number biosignatures were built with automated machine learning, including: (1) a five-gene biosignature discriminating BrCa tissue from healthy tissues (AUC 0.987 and precision 0.987), (2) three equivalent OA cartilage-specific biosignatures containing four genes each (AUC 0.978 and precision 0.986) and (3) a four-gene pancreatic β-cell-specific biosignature (AUC 0.984 and precision 0.995). Next, the BrCa biosignature was validated using an independent ccfDNA dataset showing an AUC and precision of 1.000, verifying the biosignature's applicability in liquid biopsy. Functional and protein interaction prediction analysis revealed that most DMGs identified are involved in pathways known to be related to the studied diseases or pointed to new ones. Overall, our data-driven approach contributes to the maximum exploitation of high-throughput methylome readings, helping to establish specific disease profiles to be applied in clinical practice and to understand human pathology.

Opportunities for Early Cancer Detection: The Rise of ctDNA Methylation-Based Pan-Cancer Screening Technologies

The efficiency of conventional screening programs to identify early-stage malignancies can be limited by the low number of cancers recommended for screening as well as the high cumulative false-positive rate, and associated iatrogenic burden, resulting from repeated multimodal testing. The opportunity to use minimally invasive liquid biopsy testing to screen asymptomatic individuals at-risk for multiple cancers simultaneously could benefit from the aggregated diseases prevalence and a fixed specificity. Increasing both latter parameters is paramount to mediate high positive predictive value—a useful metric to evaluate a screening test accuracy and its potential harm-benefit. Thus, the use of a single test for multi-cancer early detection (stMCED) has emerged as an appealing strategy for increasing early cancer detection rate efficiency and benefit population health. A recent flurry of these stMCED technologies have been reported for clinical potential; however, their development is facing unique challenges to effectively improve clinical cost–benefit. One promising avenue is the analysis of circulating tumour DNA (ctDNA) for detecting DNA methylation biomarker fingerprints of malignancies—a hallmark of disease aetiology and progression holding the potential to be tissue- and cancer-type specific. Utilizing panels of epigenetic biomarkers could potentially help to detect earlier stages of malignancies as well as identify a tumour of origin from blood testing, useful information for follow-up clinical decision making and subsequent patient care improvement. Overall, this review collates the latest and most promising stMCED methodologies, summarizes their clinical performances, and discusses the specific requirements multi-cancer tests should meet to be successfully implemented into screening guidelines.

Chronological age or biological age: What drives the choice of adjuvant treatment in elderly breast cancer patients?

Ma and colleagues reported in their study on 12,004 elderly patients published on Breast J. 2020, that adjuvant chemotherapy was not associated with overall survival. Given the toxicities associated with systemic treatments, caution recommendation or omission of chemotherapy may be considered in elderly patient selection especially when comorbidities are present. We agree with authors final conclusions but we want to highlight that to define the adjuvant therapy in BC elderly patients several factors need to be taken into account. One of the main issues is the lack of universal and unique guidelines to define elderly patients. In clinical practice it can be very difficult to estimate the benefit/risk ratio in elderly patients because chemotherapy-induced toxicity is worse than in younger individuals. For these reasons, beyond comorbidities, the choice of adjuvant therapy for elderly patients must also be based both on chronological and biological age. Moreover, the multidisciplinary team for the elderly patient evaluation should include both the geriatrician and the molecular biologist.

Combined multimodal ctDNA analysis and radiological imaging for tumor surveillance in Non-small cell lung cancer

BACKGROUND

Radiology is the current standard for monitoring treatment responses in lung cancer. Limited sensitivity, exposure to ionizing radiations and related sequelae constitute some of its major limitation. Non-invasive and highly sensitive methods for early detection of treatment failures and resistance-associated disease progression would have additional clinical utility.

METHODS

We analyzed serially collected plasma and paired tumor samples from lung cancer patients (61 with stage IV, 48 with stages I-III disease) and 61 healthy samples by means of next-generation sequencing, radiological imaging and droplet digital polymerase chain reaction (ddPCR) mutation and methylation assays.

RESULTS

A 62% variant concordance between tumor-reported and circulating-free DNA (cfDNA) sequencing was observed between baseline liquid and tissue biopsies in stage IV patients. Interestingly, ctDNA sequencing allowed for the identification of resistance-mediating p.T790M mutations in baseline plasma samples for which no such mutation was observed in the corresponding tissue. Serial circulating tumor DNA (ctDNA) mutation analysis by means of ddPCR revealed a general decrease in ctDNA loads between baseline and first reassessment. Additionally, serial ctDNA analyses only recapitulated computed tomography (CT) -monitored tumor dynamics of some, but not all lesions within the same patient. To complement ctDNA variant analysis we devised a ctDNA methylation assay (^methcfDNA) based on methylation-sensitive restriction enzymes. cfDNA methylation showed and area under the curve (AUC) of > 0.90 in early and late stage cases. A decrease in ^methcfDNA between baseline and first reassessment was reflected by a decrease in CT-derive tumor surface area, irrespective of tumor mutational status.

CONCLUSION

Taken together, our data support the use of cfDNA sequencing for unbiased characterization of the molecular tumor architecture, highlights the impact of tumor architectural heterogeneity on ctDNA-based tumor surveillance and the added value of complementary approaches such as cfDNA methylation for early detection and monitoring.

High throughput proteomic and metabolic profiling identified target correction of metabolic abnormalities as a novel therapeutic approach in head and neck paraganglioma

Head and neck paragangliomas (HNPGLs) are rare neoplasms that represent difficult treatment paradigms in neurotology. Germline mutations in genes encoding succinate dehydrogenase (SDH) are the cause of nearly all familial HNPGLs. However, the molecular mechanisms underlying tumorigenesis remain unclear. Mutational analysis identified 6 out of 14 HNPGLs harboring clinicopathologic SDH gene mutations. The SDHB gene was most frequently mutated in these patients, and western blot showed loss of SDHB protein in tumors with SDHB mutations. The paraganglioma cell line (PGL-626) was established from a sample that harbored a missense SDHB mutation (c.649C > T). Spectrometric analysis using tandem mass tags identified 151 proteins significantly differentially expressed in HNPGLs compared with normal nerves. Bioinformatics analyses confirmed the high level of enrichment of oxidative phosphorylation and metabolism pathways in HNPGLs. The mitochondrial complex subunits NDUFA2, NDUFA10, and NDUFA4, showed the most significantly increased expression and were localized predominantly in the cytoplasm of PGL-626 cells. The mitochondrial complex I inhibitor metformin exerted dose-dependent inhibitory effects on PGL-626 cells via cooperative down-regulation of NDUFA2, 4, and 10, with a significant decrease in the levels of reactive oxygen species and mitochondrial membrane potential. Further metabolomic analysis of PGL-626 cells showed that metabolites involved in central carbon metabolism in cancer and sphingolipid signaling pathways, pantothenate and CoA biosynthesis, and tryptophan and carbon metabolism were significantly altered after metformin treatment. Thus, this study provides insights into the molecular mechanisms underlying HNPGL tumorigenesis and identifies target correction of metabolic abnormalities as a novel therapeutic approach for this disease.

Liquid Biopsy: A Family of Possible Diagnostic Tools

Liquid biopsies could be considered an excellent diagnostic tool, in different physiological or pathological conditions. The possibility of using liquid biopsies for non-invasive clinical purposes is quite an old idea: indeed many years ago it was already being used in the field of non-invasive prenatal tests (NIPT) for autosomal fetal aneuploidy evaluation. In 1997 Lo et al. had identified fetal DNA in maternal plasma and serum, showing that about 10–15% of cfDNA in maternal plasma is derived from the placenta, and biologic fluid represents an important and non-invasive technique to evaluate state diseases and possible therapies. Nowadays, several body fluids, such as blood, urine, saliva and other patient samples, could be used as liquid biopsy for clinical non-invasive evaluation. These fluids contain numerous and various biomarkers and could be used for the evaluation of pathological and non-pathological conditions. In this review we will analyze the different types of liquid biopsy, their potential role in clinical diagnosis and the functional involvement of extracellular vesicles in these fluids as carriers.

Methylation Status of Corticotropin-Releasing Factor (CRF) Receptor Genes in Colorectal Cancer

The corticotropin-releasing factor (CRF) system has been strongly associated with gastrointestinal pathophysiology, including colorectal cancer (CRC). We previously showed that altered expression of CRF receptors (CRFRs) in the colon critically affects CRC progression and aggressiveness through regulation of colonic inflammation. Here, we aimed to assess the potential of CRFR methylation levels as putative biomarkers in CRC. In silico methylation analysis of CRF receptor 1 (CRFR1) and CRF receptor 2 (CRFR2) was performed using methylome data derived by CRC and Crohn's disease (CD) tissues and CRC-derived circulating cell-free DNAs (ccfDNAs). In total, 32 and 33 differentially methylated sites of CpGs (DMCs) emerged in CRFR1 and CRFR2, respectively, between healthy and diseased tissues. The methylation patterns were verified in patient-derived ccfDNA samples by qMSP and associated with clinicopathological characteristics. An automated machine learning (AutoML) technology was applied to ccfDNA samples for classification analysis. In silico analysis revealed increased methylation of both CRFRs in CRC tissue and ccfDNA-derived datasets. CRFR1 hypermethylation was also noticed in gene body DMCs of CD patients. CRFR1 hypermethylation was further validated in CRC adjuvant-derived ccfDNA samples, whereas CRFR1 hypomethylation, observed in metastasis-derived ccfDNAs, was correlated to disease aggressiveness and adverse prognostic characteristics. AutoML analysis based on CRFRs methylation status revealed a three-feature high-performing biosignature for CRC diagnosis with an estimated AUC of 0.929. Monitoring of CRFRs methylation-based signature in CRC tissues and ccfDNAs may be of high diagnostic and prognostic significance in CRC.

The Potential of Aptamer-Mediated Liquid Biopsy for Early Detection of Cancer

The early detection of cancer favors a greater chance of curative treatment and long-term survival. Exciting new technologies have been developed that can help to catch the disease early. Liquid biopsy is a promising non-invasive tool to detect cancer, even at an early stage, as well as to continuously monitor disease progression and treatment efficacy. Various methods have been implemented to isolate and purify bio-analytes in liquid biopsy specimens. Aptamers are short oligonucleotides consisting of either DNA or RNA that are capable of binding to target molecules with high specificity. Due to their unique properties, they are considered promising recognition ligands for the early detection of cancer by liquid biopsy. A variety of circulating targets have been isolated with high affinity and specificity by facile modification and affinity regulation of the aptamers. In this review, we discuss recent progress in aptamer-mediated liquid biopsy for cancer detection, its associated challenges, and its future potential for clinical applications.

A 3-DNA methylation signature as a novel prognostic biomarker in patients with sarcoma by bioinformatics analysis

BACKGROUND

Tumor-specific DNA methylation can potentially be a useful indicator in cancer diagnostics and monitoring. Sarcomas comprise a heterogeneous group of mesenchymal neoplasms which cause life-threatening tumors occurring throughout the body. Therefore, potential molecular detection and prognostic evaluation is very important for early diagnosis and treatment.

METHODS

We performed a retrospective study analyzing DNA methylation of 261 patients with sarcoma from The Cancer Genome Atlas (TCGA) database. Cox regression analyses were conducted to identify a signature associated with the overall survival (OS) of patients with sarcoma, which was validated in a validation dataset.

RESULTS

Three DNA methylation signatures were identified to be significantly associated with OS. Kaplan-Meier analysis showed that the 3-DNA methylation signature could significantly distinguish the high- and low-risk patients in both training (first two-thirds) and validation datasets (remaining one-third). Receiver operating characteristic (ROC) analysis confirmed that the 3-DNA methylation signature exhibited high sensitivity and specificity in predicting OS of patients. Also, the Kaplan-Meier analysis and the area under curve (AUC) values indicated that the 3-DNA methylation signature was independent of clinical characteristics, including age at diagnosis, sex, anatomic location, tumor residual classification, and histological subtypes.

CONCLUSIONS

The current study showed that the 3-DNA methylation model could efficiently function as a novel and independent prognostic biomarker and therapeutic target for patients with sarcoma.