Tissue- and liquid-biopsy based NGS profiling in advanced non-small-cell lung cancer in a real-world setting: the IMMINENT study.

Introduction: To date, for all non-small cell lung cancer (NSCLC) cases, it is recommended to test for driver alterations to identify actionable therapeutic targets. In this light, comprehensive genomic profiling (CGP) with next generation sequencing (NGS) has progressively gained increasing importance in clinical practice. Here, with the aim of assessing the distribution and the real-world frequency of gene alterations and their correlation with patient characteristics, we present the outcomes obtained using FoundationOne (F1CDx) and FoundationLiquid CDx (F1L/F1LCDx) NGS-based profiling in a nationwide initiative for advanced NSCLC patients. Methods: F1CDx (324 genes) was used for tissue samples, and F1L (70 genes) or F1LCDx (324 genes) for liquid biopsy, aiming to explore the real-world occurrence of molecular alterations in aNSCLC and their relationship with patients' characteristics. Results: Overall, 232 advanced NSCLC patients from 11 Institutions were gathered [median age 63 years; never/former or current smokers 29.3/65.9%; adenocarcinoma/squamous 79.3/12.5%; F1CDx/F1L+F1LCDx 59.5/40.5%]. Alterations were found in 170 different genes. Median number of mutated genes per sample was 4 (IQR 3-6) and 2 (IQR 1-3) in the F1CDx and F1L/F1LCDx cohorts, respectively. TP53 (58%), KRAS (22%), CDKN2A/B (19%), and STK11 (17%) alterations were the most frequently detected. Actionability rates (tier I and II) were comparable: 36.2% F1CDx vs. 34% ctDNA NGS assays (29.5% and 40.9% F1L and F1LCDx, respectively). Alterations in KEAP1 were significantly associated with STK11 and KRAS, so as TP53 with RB1. Median tumor mutational burden was 6 (IQR 3-10) and was significantly higher in smokers. Median OS from metastatic diagnosis was 23 months (IQR 18.5-19.5) and significantly lower in patients harboring ≥3 gene mutations. Conditional three-year survival probabilities increased over time for patients profiled at initial diagnosis and exceeded those of individuals tested later in their clinical history after 12 months. Conclusion: This study confirms that NGS-based molecular profiling of aNSCLC on tissue or blood samples offers valuable predictive and prognostic insights.

Clinical application of liquid biopsy in colorectal cancer: detection, prediction, and treatment monitoring.

Colorectal cancer (CRC) is one of the most prevalent malignancies affecting the gastrointestinal tract and is ranked third among cancers with the highest incidence and second-highest mortality rate worldwide. CRC exhibits a slow progression providing a wide treatment window. The currently employed CRC screening methods have shown great potential to prevent CRC and reduce CRC-related morbidity and mortality. The diagnosis of CRC is achieved by colonoscopy and tissue biopsy, with studies showing that liquid biopsy is more effective in detecting and diagnosing early CRC patients. Increasing number of studies have shown that the tumor components shed into circulating blood can be detected in liquid form, and can be applied in the clinical management of CRC. Analysis of circulating tumor cells (CTCs), circulating tumor DNA (ctDNA), or tumor-associated platelets (TEPs) in the blood can be used for early screening and diagnosis of CRC, aid tumor staging, treatment response monitoring, and prediction of CRC recurrence and metastasis in a minimally invasive manner. This chapter provides an updated review of CTCs, ctDNA, and TEPs as novel biomarkers for CRC, highlighting their strengths and limitations.

Targeting genomic receptors in voided urine for confirmation of benign prostatic hyperplasia.

Objectives: The objective of this study is to validate a hypothesis that a non-invasive optical imaging assay targeting genomic VPAC receptors on malignant cells shed in voided urine will represent either benign prostatic hyperplasia (BPH) or prostatic cancer (PCa). Risk for BPH in men 50-70 years old is 50-70% and PCa is 17%. BPH and PCa can coexist in 20% of men with BPH. Most commonly practiced methods to diagnose BPH do not distinguish BPH from PCa. Patients or Materials and Methods: Males with BPH (N = 97, 60.8 ± 6.3 years, prostate-specific antigen 0.7 ± 0.4 ng/mL) and without oncologic disease (N = 35, 63.4 ± 5.8 years, prostate-specific antigen < 1.5 ng/mL) signed informed consent form and provided voided urine. Urine was cytocentrifuged, cells collected on glass slide, fixed, treated with VPAC specific fluorophore TP4303 (Kd 3.1 × 10-8M), washed, incubated with DAPI and observed using a fluorescence microscope. Cells with no VPAC did not fluoresce (BPH) and those with VPAC had red-orange fluorescence (PCa). Real-time polymerase chain reaction analyses for VPAC and NKX3.1 assay for cell origin were performed. Results: Eighty-seven subjects were negative for VPAC expression. Positive VPAC expression was noted in 10 subjects. Patient chart review for clinical data on these 10 VPAC positive subjects showed five had nephrolithiasis, three had renal cysts, one had prostatitis and one was being treated with finasteride. Real-time polymerase chain reaction analysis-VPAC expressions for 7 normal and 12 BPH subjects were 1.31 ± 1.26 and 0.94 ± 0.89, respectively (P = 0.46). NKX3.1 showed cells of prostate origin for finasteride-treated patient. Specificity for VPAC urine assay for excluding prostate cancer in this BPH cohort was 88.5%, positive predictive value 0.00% and negative predictive value 100%. Conclusion: VPAC assay may contribute extensively for BPH diagnosis and warrant continued investigation.

Current status and progress of PD-L1 detection: guiding immunotherapy for non-small cell lung cancer.

Non-small cell lung cancer (NSCLC) is the leading cause of cancer-related deaths and represents a substantial disease burden worldwide. Immune checkpoint inhibitors combined with chemotherapy are the standard first-line therapy for advanced NSCLC without driver mutations. Programmed death-ligand 1 (PD-L1) is currently the only approved immunotherapy marker. PD-L1 detection methods are diverse and have developed rapidly in recent years, such as improved immunohistochemical detection methods, the application of liquid biopsy in PD-L1 detection, genetic testing, radionuclide imaging, and the use of machine learning methods to construct PD-L1 prediction models. This review focuses on the detection methods and challenges of PD-L1 from different sources, and discusses the influencing factors of PD-L1 detection and the value of combined biomarkers. Provide support for clinical screening of immunotherapy-advantage groups and formulation of personalized treatment decisions.

Oligo cyc-DEP: On-chip cyclic immunofluorescence profiling of cell-derived nanoparticles.

We present a follow-on technique for the cyclic-immunofluorescence profiling of suspension particles isolated using dielectrophoresis. The original lab-on-chip technique ("cyc-DEP" [cyclic immunofluorescent imaging on dielectrophoretic chip]) was designed for the multiplex surveillance of circulating biomarkers. Nanoparticles were collected from low-volume liquid biopsies using microfluidic dielectrophoretic chip technology. Subsequent rounds of cyclic immunofluorescent labeling and quenching were imaged and quantified with a custom algorithm to detect multiple proteins. While cyc-DEP improved assay multiplicity, long runtimes threatened its clinical adoption. Here, we modify the original cyc-DEP platform to reduce assay runtimes. Nanoparticles were formulated from human prostate adenocarcinoma cells and collected using dielectrophoresis. Three proteins were labeled on-chip with a mixture of short oligonucleotide-conjugated antibodies. The sample was then incubated with complementary fluorophore-conjugated oligonucleotides, which were dehybridized using an ethylene carbonate buffer after each round of imaging. Oligonucleotide removal exhibited an average quenching efficiency of 98 ± 3% (n = 12 quenching events), matching the original cyc-DEP platform. The presented "oligo cyc-DEP" platform achieved clinically relevant sample-to-answer times, reducing the duration for three rounds of cyclic immunolabeling from approximately 20 to 6.5 h-a 67% decrease attributed to rapid fluorophore removal and the consolidated co-incubation of antibodies.

Translation of Epigenetics in Cell-Free DNA Liquid Biopsy Technology and Precision Oncology.

Technological advancements in cell-free DNA (cfDNA) liquid biopsy have triggered exponential growth in numerous clinical applications. While cfDNA-based liquid biopsy has made significant strides in personalizing cancer treatment, the exploration and translation of epigenetics in liquid biopsy to clinical practice is still nascent. This comprehensive review seeks to provide a broad yet in-depth narrative of the present status of epigenetics in cfDNA liquid biopsy and its associated challenges. It highlights the potential of epigenetics in cfDNA liquid biopsy technologies with the hopes of enhancing its clinical translation. The momentum of cfDNA liquid biopsy technologies in recent years has propelled epigenetics to the forefront of molecular biology. We have only begun to reveal the true potential of epigenetics in both our understanding of disease and leveraging epigenetics in the diagnostic and therapeutic domains. Recent clinical applications of epigenetics-based cfDNA liquid biopsy revolve around DNA methylation in screening and early cancer detection, leading to the development of multi-cancer early detection tests and the capability to pinpoint tissues of origin. The clinical application of epigenetics in cfDNA liquid biopsy in minimal residual disease, monitoring, and surveillance are at their initial stages. A notable advancement in fragmentation patterns analysis has created a new avenue for epigenetic biomarkers. However, the widespread application of cfDNA liquid biopsy has many challenges, including biomarker sensitivity, specificity, logistics including infrastructure and personnel, data processing, handling, results interpretation, accessibility, and cost effectiveness. Exploring and translating epigenetics in cfDNA liquid biopsy technology can transform our understanding and perception of cancer prevention and management. cfDNA liquid biopsy has great potential in precision oncology to revolutionize conventional ways of early cancer detection, monitoring residual disease, treatment response, surveillance, and drug development. Adapting the implementation of liquid biopsy workflow to the local policy worldwide and developing point-of-care testing holds great potential to overcome global cancer disparity and improve cancer outcomes.

Serum Extracellular Vesicles Cargo Approach in Bitches with Mammary Tumors.

This study investigated serum extracellular vesicles (EVs) in bitches with mammary neoplasms, in order to understand their size, shape, and concentration, as well as their association with tumor malignancy. Thirty bitches were categorized into control (n = 10), mammary tumor grades I and II (GI, n = 13), and grade III (GII, n = 7). Serum was separated from blood collected during mastectomy, and EVs were isolated using size exclusion chromatography. The analysis revealed no significant differences in EV concentrations among groups, with similar concentrations for control, GI, and GII. Ninety-one proteins were identified in EV-enriched samples, with six showing varied abundance across groups. Notably, keratin 18 was highly abundant in GI, while sushi domain-containing protein, EvC ciliary subunit 2, and the joining chain of multimeric IgM and IgA were increased in GII. Additionally, protocadherin 17 and albumin were upregulated in both GI and GII. ROC curves identified potential biomarkers for differentiating tumor grades. Enrichment pathway analysis revealed AFP gene upregulation in the GI. Mass spectrometry proteomics data were deposited in Mendeley Data. The study provides valuable insights into serum EV characterization in bitches, suggesting keratin 18 and protocadherin 17 as potential biomarkers for canine mammary neoplasia, with implications for future diagnostic and therapeutic strategies.

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.

Revisiting the standards of cancer detection and therapy alongside their comparison to modern methods.

In accordance with the World Health Organization data, cancer remains at the forefront of fatal diseases. An upward trend in cancer incidence and mortality has been observed globally, emphasizing that efforts in developing detection and treatment methods should continue. The diagnostic path typically begins with learning the medical history of a patient; this is followed by basic blood tests and imaging tests to indicate where cancer may be located to schedule a needle biopsy. Prompt initiation of diagnosis is crucial since delayed cancer detection entails higher costs of treatment and hospitalization. Thus, there is a need for novel cancer detection methods such as liquid biopsy, elastography, synthetic biosensors, fluorescence imaging, and reflectance confocal microscopy. Conventional therapeutic methods, although still common in clinical practice, pose many limitations and are unsatisfactory. Nowadays, there is a dynamic advancement of clinical research and the development of more precise and effective methods such as oncolytic virotherapy, exosome-based therapy, nanotechnology, dendritic cells, chimeric antigen receptors, immune checkpoint inhibitors, natural product-based therapy, tumor-treating fields, and photodynamic therapy. The present paper compares available data on conventional and modern methods of cancer detection and therapy to facilitate an understanding of this rapidly advancing field and its future directions. As evidenced, modern methods are not without drawbacks; there is still a need to develop new detection strategies and therapeutic approaches to improve sensitivity, specificity, safety, and efficacy. Nevertheless, an appropriate route has been taken, as confirmed by the approval of some modern methods by the Food and Drug Administration.

Colorectal cancer screening: Modalities and adherence.

In the last decade, several studies have explored various modalities and strategies for colorectal cancer (CRC) screening, taking into account epidemiological data, individual characteristics, and socioeconomic factors. In this editorial, we comment further on a retrospective study by Agatsuma et al published in the recent issue of the World Journal of Gastroenterology. Our focus is on screening trends, particularly in relation to efforts to improve the currently suboptimal uptake among the general population worldwide, aiming to enhance early diagnosis rates of CRC. There is a need to raise awareness through health edu-cation programs and to consider the use of readily available, non-invasive screening methods. These strategies are crucial for attracting screen-eligible populations to participate in first-line screening, especially those in high- or average-risk groups and in regions with limited resources. Liquid biopsies and biomarkers represent rapidly evolving trends in screening and diagnosis; however, their clinical relevance has yet to be standardized.

Liquid Biopsy in Whole Blood for Identification of Gene Expression Patterns (mRNA and miRNA) Associated with Recurrence of Glioblastoma WHO CNS Grade 4.

GBM WHO CNS Grade 4 represents a major challenge for oncology due to its aggressive behavior. Conventional imaging has restrictions in detecting tumor recurrence. This prospective study aims to identify gene-based biomarkers in whole blood instead of isolating exosomes for the early detection of tumor recurrence. Blood samples (n = 33) were collected from seven GBM patients at time points before and after surgery as well as upon tumor recurrence. Four tumor tissue samples were assessed in parallel. Next-generation sequencing (NGS), including mRNA-seq and small RNA-seq, was used to analyze gene expression profiles in blood samples and tumor tissues. A novel filtering pipeline was invented to narrow down potential candidate genes. In total, between 6-93 mRNA and 1-19 small RNA candidates could be identified among the seven patients. The overlap of genes between the patients was minimal, indicating significant inter-individual variance among GBM patients. In summary, this prospective study supports the applicability of gene expression measurements in whole blood for the detection of tumor recurrence. It might provide an alternative to the challenging workflow of liquid biopsy after laborious exosome isolation from whole blood.

Haemostatic Gene Expression in Cancer-Related Immunothrombosis: Contribution for Venous Thromboembolism and Ovarian Tumour Behaviour.

Ovarian cancer (OC) is the deadliest gynaecological malignancy. Identifying new prognostic biomarkers is an important research field. Haemostatic components together with leukocytes can drive cancer progression while increasing the susceptibility to venous thromboembolism (VTE) through immunothrombosis. Unravelling the underlying complex interactions offers the prospect of uncovering relevant OC prognostic biomarkers, predictors of cancer-associated thrombosis (CAT), and even potential targets for cancer therapy. Thus, this study evaluated the expression of F3, F5, F8, F13A1, TFPI1, and THBD in peripheral blood cells (PBCs) of 52 OC patients. Those with VTE after tumour diagnosis had a worse overall survival (OS) compared to their counterparts (mean OS of 13.8 ± 4.1 months and 47.9 ± 5.7 months, respectively; log-rank test, p = 0.001). Low pre-chemotherapy F3 and F8 expression levels were associated with a higher susceptibility for OC-related VTE after tumour diagnosis (χ2, p < 0.05). Regardless of thrombogenesis, patients with low baseline F8 expression had a shorter progression-free survival (PFS) than their counterparts (adjusted hazard ratio (aHR) = 2.54; p = 0.021). Among those who were not under platelet anti-aggregation therapy, low F8 levels were also associated with a shorter OS (aHR = 6.16; p = 0.006). Moving forward, efforts should focus on external validation in larger cohorts.

Serial Changes of Circulating Tumor Cells in Patients with Hepatocellular Carcinoma Treated with Atezolizumab Plus Bevacizumab.

Immune checkpoint inhibitors have promising outcomes in patients with hepatocellular carcinoma (HCC); however, there is no reliable biomarker for predicting disease progression. Circulating tumor cells (CTCs) derived from peripheral blood have attracted attention in monitoring therapeutic efficacy. In this study, CTCs were serially collected from HCC patients undergoing atezolizumab plus bevacizumab (Atezo+Bev), and changes in molecular expression and CTC numbers were analyzed to identify effective biomarkers. Changes in CTC numbers during Atezo+Bev reflected the tumor volume. Targeted RNA sequencing with next-generation sequencing (NGS) revealed that patients with elevated transforming growth factor (TGF)-ß signaling molecules had a poorer response, whereas those with elevated apoptosis signaling molecules had a favorable response. In addition, compared with changes in CTC counts, changes in TGF-ß signaling molecule expression in CTCs accurately and promptly predicted treatment response. Overall, NGS analysis of CTC-derived RNA showed that changes in TGF-ß signaling molecules predict treatment response earlier than changes in CTC counts. These findings suggest that changes in the expression of TGF-ß molecules in CTCs could serve as novel biomarkers for the early prediction of therapeutic response in patients with unresectable HCC undergoing Atezo+Bev.

Transcript Markers from Urinary Extracellular Vesicles for Predicting Risk Reclassification of Prostate Cancer Patients on Active Surveillance.

Serum prostate-specific antigen (PSA), its derivatives, and magnetic resonance tomography (MRI) lack sufficient specificity and sensitivity for the prediction of risk reclassification of prostate cancer (PCa) patients on active surveillance (AS). We investigated selected transcripts in urinary extracellular vesicles (uEV) from PCa patients on AS to predict PCa risk reclassification (defined by ISUP 1 with PSA > 10 ng/mL or ISUP 2-5 with any PSA level) in control biopsy. Before the control biopsy, urine samples were prospectively collected from 72 patients, of whom 43% were reclassified during AS. Following RNA isolation from uEV, multiplexed reverse transcription, and pre-amplification, 29 PCa-associated transcripts were quantified by quantitative PCR. The predictive ability of the transcripts to indicate PCa risk reclassification was assessed by receiver operating characteristic (ROC) curve analyses via calculation of the area under the curve (AUC) and was then compared to clinical parameters followed by multivariate regression analysis. ROC curve analyses revealed a predictive potential for AMACR, HPN, MALAT1, PCA3, and PCAT29 (AUC = 0.614-0.655, p < 0.1). PSA, PSA density, PSA velocity, and MRI maxPI-RADS showed AUC values of 0.681-0.747 (p < 0.05), with accuracies for indicating a PCa risk reclassification of 64-68%. A model including AMACR, MALAT1, PCAT29, PSA density, and MRI maxPI-RADS resulted in an AUC of 0.867 (p < 0.001) with a sensitivity, specificity, and accuracy of 87%, 83%, and 85%, respectively, thus surpassing the predictive power of the individual markers. These findings highlight the potential of uEV transcripts in combination with clinical parameters as monitoring markers during the AS of PCa.

Tumor-Derived Extracellular Vesicles as Liquid Biopsy for Diagnosis and Prognosis of Solid Tumors: Their Clinical Utility and Reliability as Tumor Biomarkers.

Early cancer detection and accurate monitoring are crucial to ensure increased patient survival. Recent research has focused on developing non-invasive biomarkers to diagnose cancer early and monitor disease progression at low cost and risk. Extracellular vesicles (EVs), nanosized particles secreted into extracellular spaces by most cell types, are gaining immense popularity as novel biomarker candidates for liquid cancer biopsy, as they can transport bioactive cargo to distant sites and facilitate intercellular communications. A literature search was conducted to discuss the current approaches for EV isolation and the advances in using EV-associated proteins, miRNA, mRNA, DNA, and lipids as liquid biopsies. We discussed the advantages and challenges of using these vesicles in clinical applications. Moreover, recent advancements in machine learning as a novel tool for tumor marker discovery are also highlighted.

Artificial intelligence-based plasma exosome label-free SERS profiling strategy for early lung cancer detection.

As a lung cancer biomarker, exosomes were utilized for in vitro diagnosis to overcome the lack of sensitivity of conventional imaging and the potential harm caused by tissue biopsy. However, given the inherent heterogeneity of exosomes, the challenge of accurately and reliably recognizing subtle differences in the composition of exosomes from clinical samples remains significant. Herein, we report an artificial intelligence-assisted surface-enhanced Raman spectroscopy (SERS) strategy for label-free profiling of plasma exosomes for accurate diagnosis of early-stage lung cancer. Specifically, we build a deep learning model using exosome spectral data from lung cancer cell lines and normal cell lines. Then, we extracted the features of cellular exosomes by training a convolutional neural network (CNN) model on the spectral data of cellular exosomes and used them as inputs to a support vector machine (SVM) model. Eventually, the spectral features of plasma exosomes were combined to effectively distinguish adenocarcinoma in situ (AIS) from healthy controls (HC). Notably, the approach demonstrated significant performance in distinguishing AIS from HC samples, with an area under the curve (AUC) of 0.84, sensitivity of 83.3%, and specificity of 83.3%. Together, the results demonstrate the utility of exosomes as a biomarker for the early diagnosis of lung cancer and provide a new approach to prescreening techniques for lung cancer.

Optimized AF4 combined with density cushion ultracentrifugation enables profiling of high-purity human blood extracellular vesicles.

Extracellular vesicles (EVs) have emerged as a promising tool for clinical liquid biopsy. However, the identification of EVs derived from blood samples is hindered by the presence of abundant plasma proteins, which impairs the downstream biochemical analysis of EV-associated proteins and nucleic acids. Here, we employed optimized asymmetric flow field-flow fractionation (AF4) combined with density cushion ultracentrifugation (UC) to obtain high-purity and intact EVs with very low lipoprotein contamination from human plasma and serum. Further proteomic analysis revealed more than 1000 EV-associated proteins, a large proportion of which has not been previously reported. Specifically, we found that cell-line-derived EV markers are incompatible with the identification of plasma-EVs and proposed that the proteins MYCT1, TSPAN14, MPIG6B and MYADM, as well as the traditional EV markers CD63 and CD147, are plasma-EV markers. Benefiting from the high-purity of EVs, we conducted comprehensive miRNA profiling of plasma EVs and nanosized particles (NPs), as well as compared plasma- and serum-derived EVs, which provides a valuable resource for the EV research community. Overall, our findings provide a comprehensive assessment of human blood EVs as a basis for clinical biopsy applications.

Novel liquid biopsy CNV biomarkers in malignant melanoma.

Malignant melanoma (MM) is known for its abundance of genetic alterations and a tendency for rapid metastasizing. Identification of novel plasma biomarkers may enhance non-invasive diagnostics and disease monitoring. Initially, we examined copy number variations (CNV) in CDK genes (CDKN2A, CDKN2B, CDK4) using MLPA (gDNA) and ddPCR (ctDNA) analysis. Subsequently, low-coverage whole genome sequencing (lcWGS) was used to identify the most common CNV in plasma samples, followed by ddPCR verification of chosen biomarkers. CNV alterations in CDK genes were identified in 33.3% of FFPE samples (Clark IV, V only). Detection of the same genes in MM plasma showed no significance, neither compared to healthy plasmas nor between pre- versus post-surgery plasma. Sequencing data showed the most common CNV occurring in 6q27, 4p16.1, 10p15.3, 10q22.3, 13q34, 18q23, 20q11.21-q13.12 and 22q13.33. CNV in four chosen genes (KIF25, E2F1, DIP2C and TFG) were verified by ddPCR using 2 models of interpretation. Model 1 was concordant with lcWGS results in 54% of samples, for model 2 it was 46%. Although CDK genes have not been proven to be suitable CNV liquid biopsy biomarkers, lcWGS defined the most frequently affected chromosomal regions by CNV. Among chosen genes, DIP2C demonstrated a potential for further analysis.

Detection and Characterization of Methylated Circulating Tumor DNA in Gastric Cancer.

Gastric cancer is the fifth most common disease in the world and the fourth most common cause of death. It is diagnosed through esophagogastroduodenoscopy with biopsy; however, there are limitations in finding lesions in the early stages. Recently, research has been actively conducted to use liquid biopsy to diagnose various cancers, including gastric cancer. Various substances derived from cancer are reflected in the blood. By analyzing these substances, it was expected that not only the presence or absence of cancer but also the type of cancer can be diagnosed. However, the amount of these substances is extremely small, and even these have various variables depending on the characteristics of the individual or the characteristics of the cancer. To overcome these, we collected methylated DNA fragments using MeDIP and compared them with normal plasma to characterize gastric cancer tissue or patients' plasma. We attempted to diagnose gastric cancer using the characteristics of cancer reflected in the blood through the cancer tissue and patients' plasma. As a result, we confirmed that the consistency of common methylated fragments between tissue and plasma was approximately 41.2% and we found the possibility of diagnosing and characterizing cancer using the characteristics of the fragments through SFR and 5'end-motif analysis.

Diagnosis of pediatric central nervous system tumors using methylation profiling of cfDNA from cerebrospinal fluid.

Pediatric central nervous system tumors remain challenging to diagnose. Imaging approaches do not provide sufficient detail to discriminate between different tumor types, while the histopathological examination of tumor tissue shows high inter-observer variability. Recent studies have demonstrated the accurate classification of central nervous system tumors based on the DNA methylation profile of a tumor biopsy. However, a brain biopsy holds significant risk of bleeding and damaging the surrounding tissues. Liquid biopsy approaches analyzing circulating tumor DNA show high potential as an alternative and less invasive tool to study the DNA methylation pattern of tumors. Here, we explore the potential of classifying pediatric brain tumors based on methylation profiling of the circulating cell-free DNA (cfDNA) in cerebrospinal fluid (CSF). For this proof-of-concept study, we collected cerebrospinal fluid samples from 19 pediatric brain cancer patients via a ventricular drain placed for reasons of increased intracranial pressure. Analyses on the cfDNA showed high variability of cfDNA quantities across patients ranging from levels below the limit of quantification to 40 ng cfDNA per milliliter of CSF. Classification based on methylation profiling of cfDNA from CSF was correct for 7 out of 20 samples in our cohort. Accurate results were mostly observed in samples of high quality, more specifically those with limited high molecular weight DNA contamination. Interestingly, we show that centrifugation of the CSF prior to processing increases the fraction of fragmented cfDNA to high molecular weight DNA. In addition, classification was mostly correct for samples with high tumoral cfDNA fraction as estimated by computational deconvolution (> 40%). In summary, analysis of cfDNA in the CSF shows potential as a tool for diagnosing pediatric nervous system tumors especially in patients with high levels of tumoral cfDNA in the CSF. Further optimization of the collection procedure, experimental workflow and bioinformatic approach is required to also allow classification for patients with low tumoral fractions in the CSF.