Liquid biopsy: current technology and clinical applications

Single circulating tumor cell sequencing based on improved high-porosity membranes and nanoporous microchambers

Circulating tumor cells (CTCs) are crucial for understanding tumor heterogeneity and progression. Despite extensive research over the years, most studies have focused on CTCs counting, with fewer efforts directed toward single-cell sequencing (SCS) of CTCs. In this study, we developed two novel nanodevices---a high-porosity ultrathin filter membrane and a nanowell chip--- to isolate single CTCs. Automated scanning and single-cell picking systems were employed to locate and isolate individual CTCs, enabling the establishment of an efficient and automated workflow for single CTC sequencing using filter-based systems. We conducted an in-depth comparison to evaluate the effects of different filter membranes and cell adhesion types on genomic integrity, cell viability, sequencing coverage, and depth. The results showed that the high-porosity filter membrane outperformed other photolithographic filters for SCS of CTCs. Validation using NCI-H358 cell lines and patient-derived CTCs demonstrated that this workflow could accurately and comprehensively detect gene mutations, amplifications, and copy number variations (CNVs). CNV profiles of CTCs from patients with the same tumor type were highly consistent, while intra-patient CTCs revealed significant heterogeneity. Furthermore, we identified and overcame challenges related to cell adhesion to the filter membrane and the impact of cell viability on sequencing outcomes during CTC enrichment. This workflow offers new insights into the development of CTC-based approaches for exploring tumor progression, heterogeneity, and mechanisms of drug resistance.

The biological and technical challenges facing utilizing circulating tumor DNA in non-metastatic breast cancer patients

Breast cancer is one of the most prevalent cancers and has emerged as a major global challenge. Circulating tumor DNA (ctDNA), a liquid biopsy method, overcomes the accessibility limitations of tissue-based testing and is widely used for monitoring minimal residual disease and molecular relapse, predicting prognosis, evaluating the response of neoadjuvant therapy, and optimizing treatment decisions in non-metastatic breast cancer. However, the application of ctDNA still faces many challenges. Here, we survey the clinical applications of ctDNA in non-metastatic breast cancer and discuss the significant biological and technical challenges of utilizing ctDNA. Importantly, we investigate potential avenues for addressing the challenges. In addition, emerging technologies, including fragmentomics detection, methylation sequencing, and long-read sequencing, have clinical potential and could be a future direction. Proper utilization of machine learning facilitates the identification of meaningful patterns from complex fragment and methylation profiles of ctDNA. There is still a lack of clinical trials focused on the subsets of ctDNA (e.g., circulating mitochondrial DNA), ctDNA-inferred drug-resistant clonal evolution, tumor heterogeneity, and ctDNA-guided clinical decision-making in non-metastatic breast cancer. Due to regional differences in the number of registered clinical trials, it is essential to enhance communication and foster global collaboration to advance the field.

Nanosized Membrane Fusion-Triggered Three-Dimensional DNA Walker for Subtype-Specific Analysis of Breast Cancer Extracellular Vesicles

Extracellular vesicles (EVs) are highly attractive in cancer diagnosis, owing to their ability to reflect the molecular characteristics of the source cells. Herein, we engineer a DNA-equipped liposome nanoprobe for developing a nanosized membrane fusion-triggered three-dimensional (3D) DNA walker for the analysis of breast cancer EVs. Specifically, liposome nanoprobes efficiently fuse with target EVs by recognizing surface-expressed epidermal growth factor receptors, thereby creating 3D tracks for the DNA walker. Subsequently, walking probes targeting human epidermal growth factor receptor-2 (HER-2) were recruited onto the fused vesicles to manipulate the walker, eventually generating considerable electrochemical signals. Results reveal a good linearity between the electrochemical output and the target EV concentration and also prove the ability of the membrane fusion-triggered DNA walker to differentiate HER-2-positive breast cancer patients and monitor the disease progression. Taken together, this work presents an effective approach for the early and subtype-specific diagnosis of breast cancer.

Longitudinal Tracking of ALK-Rearranged NSCLC From Plasma Using Circulating Tumor RNA and Circulating Tumor DNA

Background

Although the administration of tyrosine-kinase inhibitors in ALK-rearranged NSCLC has revolutionized precision medicine, the detection of gene rearrangements from liquid biopsies remains challenging. RNA-based detection has revealed promising sensitivity for rearrangement detection and thus we hypothesize that a liquid biopsy assay analyzing circulating tumor RNA (ctRNA) in addition to circulating tumor DNA (ctDNA) will improve detection. Furthermore, we hypothesize that the detection of gene fusions at baseline will correlate with clinical outcomes.

Methods

We retrospectively analyzed 86 plasma samples from 33 patients enrolled in the BRIGHTSTAR clinical trial assessing local consolidative therapy (LCT) and brigatinib in patients with stage IV or recurrent NSCLC and confirmed ALK rearrangement (NCT03707938) using a targeted next-generation sequencing assay that analyzes ctDNA to detect gene rearrangements and mutations in 80 genes and ctRNA to detect gene arrangements in 36 genes.

Results

ALK rearrangements were detected in 15 of 28 patients (54%) at baseline, of which eight were detected in both ctDNA and ctRNA. ALK rearrangements were detected in two patients pre-LCT, exclusively in ctRNA, but cleared completely post-LCT. The detection of ALK fusion at baseline was associated with significantly worse progression-free survival (p = 0.033). Plasma cell-free DNA concentrations for patients with detectable ALK rearrangements at baseline were significantly higher than for those without detectable gene fusions (12.3 ng/mL versus 20.2 ng/mL, p = 0.0046).

Conclusions

The inclusion of ctRNA in liquid biopsies increased detection of ALK rearrangements and detection at baseline was associated with significantly worse progression-free survival highlighting the added benefit of ctRNA.

Comprehensive proteomic analysis and multidimensional model construction of peritoneal metastasis in gastric cancer

Peritoneal metastasis following gastric cancer surgery is often associated with a poor prognosis. This study aimed to investigate the mechanisms underlying peritoneal metastasis and to develop a predictive model for the risk of postoperative peritoneal metastases in gastric cancer. We performed a comprehensive analysis of the protein mass spectra and tumor microenvironment in paraffin-embedded primary tumor sections from gastric cancer patients, both with and without postoperative peritoneal metastases. Using proteomic profiling, we identified 9595 proteins and stratified patients into three distinct proteomic subgroups (Pro1, Pro2, Pro3) based on differential protein expression. Simultaneously, immune cell profiling allowed us to classify patients into four immune subgroups (IG-I, IG-II, IG-III, IG-IV). The relationships between these proteomic, immune, and metastasis classifications were further explored to uncover potential associations and mechanisms driving metastasis. Building on these insights, we developed an integrative model combining proteomics, immunological, and radiomics data for predicting postoperative peritoneal metastases. This model demonstrated high predictive efficacy, offering a robust tool for identifying high-risk patients. Our findings provide a deeper understanding of the biological processes underlying peritoneal metastasis in gastric cancer, highlighting the interplay between proteomic and immune factors. By establishing novel patient subgroups and an effective prediction model, this study lays the groundwork for early diagnosis and tailored therapeutic strategies to improve outcomes for gastric cancer patients.

Extracellular vesicles: a new frontier in diagnosing and treating graft-versus-host disease after allogeneic hematopoietic cell transplantation

Graft-versus-host disease (GvHD) is a prevalent complication following allogeneic hematopoietic stem cell transplantation (HSCT) and is characterized by relatively high morbidity and mortality rates. GvHD can result in extensive systemic damage in patients following allogeneic HSCT (allo-HSCT), with the skin, gastrointestinal tract, and liver frequently being the primary target organs affected. The severe manifestations of acute intestinal GvHD often indicate a poor prognosis for patients after allo-HSCT. Endoscopy and histopathological evaluation remain employed to diagnose GvHD, and auxiliary examinations exclude differential diagnoses. Currently, reliable serum biomarkers for the diagnosis and differential diagnosis of GvHD are scarce. As an essential part of standard transplant protocols, early application of immunosuppressive drugs effectively prevents GvHD. Among them, steroids represent first-line therapeutic agents, and the JAK2 inhibitor ruxolitinib represents the second-line therapeutic agent. Currently, no efficacious treatment modality exists for steroid-resistant aGvHD. Therefore, the diagnosis and treatment of GvHD still face significant medical demands. Extracellular vesicles (EVs) are nanometer to micrometer-scale biomembrane vesicles containing various bioactive components, such as proteins, nucleotides, and metabolites. Distinctive changes in serum-derived EV components occur in patients after allo-HSCT; Hence, EVs are expected to be potential biomarkers for diagnosing and treating GvHD. Furthermore, cell-free therapeutics characterized by EVs derived from mesenchymal stem cells (MSCs) have manifested remarkable therapeutic efficacy in preclinical models and preclinical trials of GvHD. Customized engineered EVs with fewer toxic and side effects for the combined treatment of GvHD hold broad prospects for clinical translation. This review article examines the potential value of translating EVs into clinical applications for the diagnosis and treatment of GvHD. It summarizes the latest advancements and prospects of engineered EVs applying GvHD.

Liquid biopsies in cancer

Cancer ranks among the most lethal diseases worldwide. Tissue biopsy is currently the primary method for the diagnosis and biological analysis of various solid tumors. However, this method has some disadvantages related to insufficient tissue specimen collection and intratumoral heterogeneity. Liquid biopsy is a noninvasive approach for identifying cancer-related biomarkers in peripheral blood, which allows for repetitive sampling across multiple time points. In the field of liquid biopsy, representative biomarkers include circulating tumor cells (CTCs), circulating tumor DNA (ctDNA), and exosomes. Many studies have evaluated the prognostic and predictive roles of CTCs and ctDNA in various solid tumors. Although these studies have limitations, the results of most studies appear to consistently demonstrate the correlations of high CTC counts and ctDNA mutations with lower survival rates in cancer patients. Similarly, a reduction in CTC counts throughout therapy may be a potential prognostic indicator related to treatment response in advanced cancer patients. Moreover, the biochemical characteristics of CTCs and ctDNA can provide information about tumor biology as well as resistance mechanisms against targeted therapy. This review discusses the current clinical applications of liquid biopsy in cancer patients, emphasizing its possible utility in outcome prediction and treatment decision-making.

Portable and rapid solid sample preparation system utilizing twin-screw mechanism for diagnostic applications

Solid specimens play a crucial role in diagnostic and analytical testing, yet their integration into in vitro diagnostics (IVD) is often limited by lengthy processing times and bulky sample preparation equipment. In this study, we introduce a novel twin-screw mechanical maceration system that enables rapid, continuous, and efficient solid sample preparation within a compact portable platform. By utilizing counter-rotating twin screws, the system generates high shear forces, significantly reducing processing time while maintaining high sample recovery efficiency. We validated its versatility across diverse solid sample types, demonstrating efficient bacterial elution from plant tissues and single-cell dissociation of animal tissues. Our device achieved bacterial elution from plant samples in under 1 min, which is 30 times faster than conventional stomaching, while maintaining a significantly smaller footprint. For animal tissue samples, it dissociated tissue samples of varying sizes (5 g to 100 mg) into single-cell suspensions within 1 min. Furthermore, we explored scalability with a miniaturized device fabricated using 3D printing, which retained comparable performance while reducing volume requirements, expediting processing time, and enabling manual operation without an external power source. This rapid, compact, adaptable, and highly efficient twin-screw system outperforms conventional solid sample processing techniques, making it a promising innovation for a wide range of biomedical applications, from point-of-care diagnostics to tissue biopsies, food hygiene, and agricultural monitoring.

Sequential Changes in Circulating Tumor Cells in the Peripheral Blood of Pancreatic Cancer Patients with Preoperative Chemotherapy Using a New Immunocytology-Based, Light Microscopic CTC Detection Platform

Background: Circulating tumor cells (CTCs) have recently been developed as biomarkers. Several studies have reported on the clinical use of CTCs to assess drug resistance in various cancers. However, sequential and multiple CTC measurements during chemotherapy are relatively rare. We recently reported a transient increase in CTCs early after chemotherapy by sequentially detecting CTCs in a human pancreatic cancer xenograft model in nude mice. Method: In the present study, using a newly developed immunocytology and glass slide-based convenient CTC detection platform, we examined CTC numbers sequentially before, during, and after chemotherapy in the peripheral blood of 14 pancreatic cancer patients, pathological stage (pStage) I-IV, who underwent surgery with preoperative chemotherapy and GS (Gem/S-1) and GnP (Gem/nab-PTX). Results: Among patients with strongly or weakly elevated CTC counts (3-44/5 mL of blood) following GS treatment, four out of six pancreatic cancer patients were judged to have a partial response (PR), and two out of six were deemed to have stable disease (SD) as a clinical response based on the CT image. In contrast, in patients with GnP therapy, three out of four patients showed no CTC response, and these three patients were judged to have progressive disease (PD), while the remaining one patient was judged to have SD in terms of their clinical response. Conclusion: These results suggest that sequential CTC monitoring during preoperative chemotherapy in pancreatic cancer patients can be a helpful liquid biopsy diagnostic tool as a therapeutic marker to predict tumor chemosensitivity and chemoresistance in clinical settings. Further large-scale clinical studies are required to confirm and clarify this hypothesis.

Translational Advances in Oncogene and Tumor-Suppressor Gene Research

Cancer, characterized by the uncontrolled proliferation of cells, is one of the leading causes of death globally, with approximately one in five people developing the disease in their lifetime. While many driver genes were identified decades ago, and most cancers can be classified based on morphology and progression, there is still a significant gap in knowledge about genetic aberrations and nuclear DNA damage. The study of two critical groups of genes-tumor suppressors, which inhibit proliferation and promote apoptosis, and oncogenes, which regulate proliferation and survival-can help to understand the genomic causes behind tumorigenesis, leading to more personalized approaches to diagnosis and treatment. Aberration of tumor suppressors, which undergo two-hit and loss-of-function mutations, and oncogenes, activated forms of proto-oncogenes that experience one-hit and gain-of-function mutations, are responsible for the dysregulation of key signaling pathways that regulate cell division, such as p53, Rb, Ras/Raf/ERK/MAPK, PI3K/AKT, and Wnt/β-catenin. Modern breakthroughs in genomics research, like next-generation sequencing, have provided efficient strategies for mapping unique genomic changes that contribute to tumor heterogeneity. Novel therapeutic approaches have enabled personalized medicine, helping address genetic variability in tumor suppressors and oncogenes. This comprehensive review examines the molecular mechanisms behind tumor-suppressor genes and oncogenes, the key signaling pathways they regulate, epigenetic modifications, tumor heterogeneity, and the drug resistance mechanisms that drive carcinogenesis. Moreover, the review explores the clinical application of sequencing techniques, multiomics, diagnostic procedures, pharmacogenomics, and personalized treatment and prevention options, discussing future directions for emerging technologies.

Helicobacter pylori-related serum indicators: Cutting-edge advances to enhance the efficacy of gastric cancer screening

Helicobacter pylori (H. pylori) infection induces pathological changes via chronic inflammation and virulence factors, thereby increasing the risk of gastric cancer development. Compared with invasive examination methods, H. pylori-related serum indicators are cost-effective and valuable for the early detection of gastric cancer (GC); however, large-scale clinical validation and sufficient understanding of the specific molecular mechanisms involved are lacking. Therefore, a comprehensive review and analysis of recent advances in this field is necessary. In this review, we systematically analyze the relationship between H. pylori and GC and discuss the application of new molecular biomarkers in GC screening. We also summarize the screening potential and application of anti-H. pylori immunoglobulin G and virulence factor-related serum antibodies for identifying GC risk. These indicators provide early warning of infection and enhance screening accuracy. Additionally, we discuss the potential combination of multiple screening indicators for the comprehensive analysis and development of emerging testing methods to improve the accuracy and efficiency of GC screening. Although this review may lack sufficient evidence due to limitations in existing studies, including small sample sizes, regional variations, and inconsistent testing methods, it contributes to advancing personalized precision medicine in high-risk populations and developing GC screening strategies.

Liquid biopsy for guiding breast cancer immunotherapy

Liquid biopsy is a laboratory test used to detect and analyze circulating tumor cells (CTCs), circulating tumor DNA (ctDNA), and other tumor-derived components, in a blood sample. In the context of breast cancer (BC), liquid biopsies hold significant promise for guiding the use of immune checkpoint inhibitors and immune-based combinations, offering real-time insights into tumor dynamics, treatment response, and resistance mechanisms. This review explores the role of liquid biopsy in BC immunotherapy, focusing on its applications, benefits, issues, and current and future research directions.

Catching cancer signals in the blood: Innovative pathways for early esophageal cancer diagnosis

In recent years, significant progress has been made in the application of DNA methylation for the early detection of esophageal cancer (EC). As an epigenetic modification, DNA methylation allows for noninvasive screening by detecting the methylation status of circulating tumor DNA. Studies have shown that the methylation of genes such as SHOX2, SEPTIN9, EPO, and RNF180 significantly improves diagnostic sensitivity and specificity. Currently, SEPTIN9 has been approved by the Food and Drug Administration for colorectal cancer screening, while SHOX2 and EPO show promising results in EC, and RNF180 has potential in gastrointestinal tumors. This editorial reviews the study by Liu et al, which demonstrated the potential of combining the methylation of these four genes for early EC screening. In addition to their roles in early diagnosis, DNA methylation markers are gaining attention because of their roles in predicting recurrence and in postoperative follow-up. By monitoring changes in methylation levels, these markers can provide valuable insights into treatment efficacy and long-term management. As research progresses, liquid biopsy technology is expected to become an essential tool in the precision diagnosis and treatment of EC, benefiting patients significantly.

Biological roles and clinical applications of EpCAM in HCC

Epithelial cell adhesion molecule (EpCAM) is an important biomarker in tumors. In hepatocellular carcinoma (HCC), EpCAM + cells exhibit high invasiveness, tumorigenic ability, therapeutic resistance, and self-renewal ability, often identified as liver cancer stem cells (CSCs). Detecting EpCAM + cells in tumor lesions and circulation is valuable for predicting patient prognosis and monitoring therapeutic outcomes, emphasizing its clinical significance. Given its broad expression in HCC, especially in CSCs and circulating tumor cells (CTCs), EpCAM-targeting agents have garnered substantial research interest. However, the role of EpCAM in HCC progression and its regulatory mechanisms remains poorly understood. Furthermore, clinical applications of EpCAM, such as liquid biopsy and targeted therapies, are still controversial. This review summarizes the biological properties of EpCAM + HCC cells, explores the regulatory mechanisms governing EpCAM expression, and discusses its clinical significance of using EpCAM as a prognostic marker and therapeutic target.

In Silico Validation of OncoOrigin: An Integrative AI Tool for Primary Cancer Site Prediction with Graphical User Interface to Facilitate Clinical Application

Cancers of unknown primary (CUPs) represent a significant diagnostic and therapeutic challenge in the field of oncology. Due to the limitations of current diagnostic tools in these cases, novel approaches must be brought forward to improve treatment outcomes for these patients. The objective of this study was to develop a machine-learning-based software for primary cancer site prediction (OncoOrigin), based on genetic data acquired from tumor DNA sequencing. By design, this was an in silico diagnostic study, conducted using data from the cBioPortal database (accessed on 21 September 2024) and several data processing and machine learning Python libraries. The study involved over 20,000 tumor samples with information on patient age, sex, and the presence of genetic variants in over 600 genes. The main outcome of interest was machine-learning-based discrimination between cancer site classes. Model quality was assessed by training set cross-validation and evaluation on a segregated test set. Finally, the optimal model was incorporated with a graphical user interface into the OncoOrigin software. Feature importance for class discrimination was also determined on the optimal model. Out of the four tested machine learning estimators, the XGBoostClassifier-based model proved superior in test set evaluation, with a top-2 accuracy of 0.91 and ROC-AUC of 0.97. Unlike other machine learning models published in the literature, OncoOrigin stands out as the only one integrated with a graphical user interface, which is crucial for facilitating its use by oncology specialists in everyday clinical practice, where its application and implementation will have the greatest value in the future.

Utilizing Nanomaterials in Microfluidic Devices for Disease Detection and Treatment

Microfluidic technology has gained widespread application in the field of biomedical research due to its exceptional sensitivity and high specificity. Particularly when combined with nanomaterials, the synergy between the two has significantly advanced fields such as precision medicine, drug delivery, disease detection, and treatment. This article aims to provide an overview of the latest research achievements of microfluidic nanomaterials in disease detection and treatment. It delves into the applications of microfluidic nanomaterials in detecting blood parameters, cardiovascular disease markers, neurological disease markers, and tumor markers. Special emphasis is placed on their roles in disease treatment, including models such as blood vessels, the blood-brain barrier, lung chips, and tumors. The development of microfluidic nanomaterials in emerging medical technologies, particularly in skin interactive devices and medical imaging, is also introduced. Additionally, the challenges and future prospects of microfluidic nanomaterials in current clinical applications are discussed. In summary, microfluidic nanomaterials play an indispensable role in disease detection and treatment. With the continuous advancement of technology, their applications in the medical field will become even more profound and extensive.

The correlation between epithelial-mesenchymal transition classification and MMP2 expression of circulating tumor cells and prognosis of advanced or metastatic nasopharyngeal carcinoma

Background

Epithelial-mesenchymal transition (EMT) and circulating tumor cells (CTCs) are key prognostic factors in nasopharyngeal carcinoma (NPC). However, the role of EMT status in CTCs for predicting outcomes in advanced NPC treated with radiotherapy after induction chemotherapy remains unclear.

Methods

A total of 143 CTC tests from 95 advanced/metastatic NPC patients were analyzed before, during, and after radiotherapy, with a 60-month follow-up. CTC count, matrix metalloproteinase 2 (MMP2)) protein expression, and EMT subtypes were examined.

Results

During radiotherapy, CTC counts increase but decrease afterward. Patients with higher pre-radiotherapy tumor-node-metastasis (TNM) stages have lower total and M-subtype CTC counts. Higher T and TNM stages during radiotherapy correlate with increased EMT-state CTCs, especially hybrid CTCs. EA/IgG-positive patients have a higher number of hybrid CTCs and E-type (epithelial + hybrid) CTCs, while EBV-EA-negative patients have more mesenchymal CTCs. A higher post-radiotherapy CTC count predicts relapse, and the positive rate of MMP2 expression on hybrid and epithelial CTCs is higher than that on mesenchymal CTCs.

Conclusion

EMT status, particularly in hybrid CTCs, is a potential prognostic marker for relapse in advanced NPC after radiotherapy.

Society for Immunotherapy of Cancer (SITC) consensus statement on essential biomarkers for immunotherapy clinical protocols

Immunotherapy of cancer is now an essential pillar of treatment for patients with many individual tumor types. Novel immune targets and technical advances are driving a rapid exploration of new treatment strategies incorporating immune agents in cancer clinical practice. Immunotherapies perturb a complex system of interactions among genomically unstable tumor cells, diverse cells within the tumor microenvironment including the systemic adaptive and innate immune cells. The drive to develop increasingly effective immunotherapy regimens is tempered by the risk of immune-related adverse events. Evidence-based biomarkers that measure the potential for therapeutic response and/or toxicity are critical to guide optimal patient care and contextualize the results of immunotherapy clinical trials. Responding to the lack of guidance on biomarker testing in early-phase immunotherapy clinical trials, we propose a definition and listing of essential biomarkers recommended for inclusion in all such protocols. These recommendations are based on consensus provided by the Society for Immunotherapy of Cancer (SITC) Clinical Immuno-Oncology Network (SCION) faculty with input from the SITC Pathology and Biomarker Committees and the Journal for ImmunoTherapy of Cancer readership. A consensus-based selection of essential biomarkers was conducted using a Delphi survey of SCION faculty. Regular updates to these recommendations are planned. The inaugural list of essential biomarkers includes complete blood count with differential to generate a neutrophil-to-lymphocyte ratio or systemic immune-inflammation index, serum lactate dehydrogenase and albumin, programmed death-ligand 1 immunohistochemistry, microsatellite stability assessment, and tumor mutational burden. Inclusion of these biomarkers across early-phase immunotherapy clinical trials will capture variation among trials, provide deeper insight into the novel and established therapies, and support improved patient selection and stratification for later-phase clinical trials.

Epigenetic modifications in early stage lung cancer: pathogenesis, biomarkers, and early diagnosis

The integration of liquid biopsy with epigenetic markers offers significant potential for early lung cancer detection and personalized treatment. Epigenetic alterations, including DNA methylation, histone modifications, and noncoding RNA changes, often precede genetic mutations and are critical in cancer progression. In this study, we explore how liquid biopsy, combined with epigenetic markers, can provide early detection of lung cancer, potentially predicting onset up to 4 years before clinical diagnosis. We discuss the challenges of targeting epigenetic regulators, which could disrupt cellular balance if overexploited, and the need for maintaining key gene expressions in therapeutic applications. This review highlights the promise and challenges of using liquid biopsy and epigenetic markers for early-stage lung cancer diagnosis, with a focus on optimizing treatment strategies for personalized and precision medicine.

Changes in L-phenylalanine concentration reflect and predict response to anti-PD-1 treatment combined with chemotherapy in patients with non-small cell lung cancer

Chemotherapy combined with checkpoint blockade antibodies targeting programmed cell death protein (PD-1) has achieved remarkable success in non-small cell lung cancer. However, few patients benefit from long-term treatment. Therefore, biomarkers capable of guiding the optimal therapeutic selection and reducing unnecessary toxicity are of pressing importance. In our research, we gathered serial blood samples from two groups of non-small cell lung cancer patients: 49 patients received a combination of therapies, and 34 patients went under chemotherapy alone. Utilizing non-targeted metabolomic analysis, we examined different metabolites' disparity. Among the lot, L-phenylalanine emerged as a significant prognostic marker in the combination treatment of non-small cell lung cancer patients, interestingly absent in patients under sole chemotherapy. The reduced ratio of L-phenylalanine concentration (two-cycle treatment vs. pre-treatment) was associated with improved progression-free survival (hazard ratio = 1.8000, 95% confidence interval: 0.8566‒3.7820, p < 0.0001) and overall survival (hazard ratio = 1.583, 95% confidence interval: 0.7416‒3.3800, p < 0.005). We further recruited two validation cohorts (cohort 1: 40 patients and cohort 2: 30 patients) to validate the sensitivity and specificity of L-phenylalanine prediction. Our results demonstrate that a model based on L-phenylalanine variations could serve as an early risk-assessment tool for non-small cell lung cancer patients undergoing treatment, potentially facilitating strategic clinical decision-making.

Design Principles of an Engineered Metastatic Niche for Monitoring of Cancer Progression

Across many types of cancer, metastatic disease is associated with a substantial decrease in 5-year survival rates relative to only a localized primary tumor. Many patients self-report metastatic disease due to disruption of normal organ or tissue function, and earlier detection could enable treatment with a lower burden of disease. We have previously reported a subcutaneous biomaterial implant for early detection by serving as an engineered metastatic niche, which has been reported to recruit tumor cells before colonization of solid organs. In this report, we investigated the design principles of the scaffold and defined the conditions for use in disease detection. Using the metastatic 4T1 triple-negative breast cancer model, we identified that a porous structure was essential to capture tumor and immune cells. Scaffolds of multiple diameters were investigated for their ability to serve as a metastatic niche, with a porous scaffold with a diameter as small as 2 mm identifying disease accurately. Additionally, scaffolds that had been in vivo for 1-5 weeks were able to identify disease accurately. Finally, the sensitivity of the scaffold relative to liquid biopsies was analyzed, with scaffolds accurately detecting disease at earlier time points than liquid biopsy. Collectively, these studies inform the design principles and use conditions for porous scaffolds to detect metastatic disease.

Sample-to-answer detection of miRNA from whole blood using thermally responsive alkane partitions

Circulating miRNA offers a tremendous opportunity as a biomarker paradigm for many applications in disease diagnostics, including point-of-care diagnostics for global health needs. However, despite the numerous miRNA detection schemes reported, there still does not exist a solution for highly sensitive sample-to-answer detection of miRNA directly from complex samples, such as whole blood. We recently developed thermally responsive alkane partitions (TRAPs), which - when combined with magnetic microbeads - enable the complete assay automation from whole blood. Here we apply TRAPs with ligation-LAMP to automate the detection of miRNA in whole blood samples. MBs and a TRAP enable the automated purification of miRNA from blood, while a novel displacement-ligation method is utilized to trigger the ligation-LAMP reaction, which is streamlined into one step by a second TRAP. Using easily manufacturable TRAP-enabled assay cassettes and a custom low-cost handheld instrument, we report the specific detection of miR-155 at concentrations as low as 15 fM in whole blood with no intermediate steps by the user. This new approach creates the opportunity for point-of-care miRNA-based diagnostics with global health applications.

Diagnosis of primary meningeal natural killer/T‑cell lymphoma of the central nervous system using cerebrospinal fluid cytology: A case report

Primary central nervous system (CNS) lymphoma of the meninges is a rare tumor that originates in the meninges and does not show parenchymal or systemic spread. CNS involvement by natural killer (NK)/T-cell lymphoma accounts for only 2% of all extranodal NK/T-cell lymphomas, and primary NK/T-cell lymphoma of the meninges is even rarer. The present study reports a case of a 55-year-old male patient with primary NK/T-cell lymphoma. The patient presented with intermittent dizziness and headaches for the past 1 month prior to presentation. Magnetic resonance imaging of the head identified no overt abnormalities. However, cytological analysis of a Wright-Giemsa-stained cerebrospinal fluid (CSF) sample, demonstrated numerous atypical lymphocytes and lymphoma cells. Flow cytometry of the CSF was performed as an auxiliary method, and it showed that a large proportion of the cells in the CSF were of the NK/T-cell lineage, to indicating a diagnosis of NK/T-cell lymphoma. Mutations of 14 genes were detected, including JAK3 mutations, upon screening of the CSF for blood system diseases using next-generation sequencing. Therefore, the present study demonstrated that a CSF cytological examination may be an important component of the diagnostic workup for patients suspected to have a primary meningeal CNS lymphoma.

Application and development of CRISPR-Cas12a methods for the molecular diagnosis of cancer: A review

Rapid, sensitive, and specific molecular detection methods are crucial for diagnosing, treating and prognosing cancer patients. With advancements in biotechnology, molecular diagnostic technology has garnered significant attention as a fast and accurate method for cancer diagnosis. CRISPR-Cas12a (Cpf1), an important CRISPR-Cas family member, has revolutionized the field of molecular diagnosis since its introduction. CRISPR-Cas technologies are a new generation of molecular tools that are widely used in the detection of pathogens, cancers, and other diseases. Liquid biopsy methods based on CRISPR-Cas12a have demonstrated remarkable success in cancer diagnosis, encompassing the detection of DNA mutations, DNA methylation, tumor-related viruses, and non-nucleic acid molecule identification. This review systematically discusses the developmental history, key technologies, and principles of CRISPR-Cas12a-based molecular diagnostic techniques and their applications in cancer diagnosis. This review has also discussed the future development directions of CRISPR-Cas12a, aiming for it to become a reliable new technology that can be used in clinical application.

Current advances and future prospects of blood-based techniques for identifying benign and malignant pulmonary nodules

Lung cancer is the leading cause of cancer-related mortality worldwide, highlighting the urgent need for more accurate and minimally invasive diagnostic tools to improve early detection and patient outcomes. While low-dose computed tomography (LDCT) is effective for screening in high-risk individuals, its high false-positive rate necessitates more precise diagnostic strategies. Liquid biopsy, particularly ctDNA methylation analysis, represents a promising alternative for non-invasive classification of indeterminate pulmonary nodules (IPNs). This review highlights the progress and clinical potential of liquid biopsy technologies, including traditional proteins markers, cfDNA, exosomes, metabolomics, circulating tumor cells (CTCs) and platelets, in lung cancer diagnosis. We discuss the integration of ctDNA methylation analysis with traditional imaging and clinical data to enhance the early detection of IPNs, as well as potential solutions to address the challenges of low biomarker concentration and background noise. By advancing precision diagnostics, liquid biopsy technologies could transform lung cancer management, improve survival rates, and reduce the disease burden.

Cell-free Tumor DNA: a Promising Technology for Diagnosis, Surveillance and Therapeutic Decision in Urothelial Carcinoma of the Bladder

PURPOSE OF REVIEW

This narrative review aims to discuss the latest evidence for cell-free tumor DNA (ctDNA) use in bladder cancer, future perspectives and challenges in implementing this technology in clinical practice.

RECENT FINDINGS

Recent papers describe promising findings regarding ctDNA analysis in blood samples and in urine of bladder cancer patients. This biomarker can be used as a diagnostic tool, in prognostic evaluation and as additional data for treatment indication and surveillance.

Descriptive report of complex cystic renal mass fluid cytology: a cross-sectional analysis

Background

During surgical extirpation of cystic renal masses, surgeons attempt to avoid cyst rupture due to the theoretical risk of tumor seeding. Whether the concern regarding tumor seeding is warranted is debatable. Our objective was to evaluate the presence of malignant cells in the fluid of complex renal cysts.

Methods

This was a cross-sectional analysis of adult patients undergoing radical or partial nephrectomy to address a cystic renal mass. Patients undergoing a partial or radical nephrectomy by open or robotic approach for a clinically localized (< cT2N0M0) cystic renal mass were included. Following excision, fluid from the mass was aspirated and sent for cytologic analysis. Cyst fluid was prepared by processing up to 50 mL into a PreservCyt® vial on a ThinPrep® 2000 or ThinPrep® 5000 processor using standard protocols, resulting in a pap-stained ThinPrep glass slide. The second half of the fluid was processed into a cellblock using a plasma/thrombin process resulting in a Formalin-Fixed Paraffin-Embedded (FFPE) block cut to produce a hematoxylin and eosin (H&E)-stained slide. Both the pap-stained and H&E slides were evaluated for malignant cells by a cytotechnologist and pathologist.

Results

Twenty-three patients underwent resection of 24 cystic tumors including 17 (73.9%) males and 6 (26.1%) females. The median patient age was 58 years [interquartile range (IQR), 43-68 years]. The median tumor diameter was 3.7 cm (IQR, 3.2-6.1 cm). Most patients underwent robotic partial nephrectomy (n=19, 83%). Renal cyst cytology was benign in 46% (n=11), atypical in 29% (n=7), suspicious in 8% (n=2), positive for neoplasm in 4% (n=1), and positive for malignancy in 4% (n=1). Clear cell renal cell carcinoma was the most common histologic subtype (n=17, 71%).

Conclusions

Based on routine cytologic analysis, there is no clear pattern with the presence or absence of malignant cells in the fluid of complex renal cysts. More sophisticated testing may provide insight into the malignant potential of renal cyst fluid.

Neutrophil- and Endothelial Cell-Derived Extracellular Microvesicles Are Promising Putative Biomarkers for Breast Cancer Diagnosis

Introduction: Breast cancer (BC) is a disease that affects about 2.2 million people worldwide. The prognosis and treatment of these patients depend on clinical and histopathologic staging, in which more aggressive cancers need a less conservative therapeutic approach. Previous studies showed that patients with BC have an increased frequency of systemic microvesicles (MVs) that are associated with invasion, progression, and metastasis, which can be used in liquid biopsy to predict the therapeutic response in individualized treatment. Objective: This study proposes the development of a minimally invasive BC diagnostic panel and follow-up biomarkers as a complementary method to screen patients. Methods: The quantification of circulating MVs in 48 healthy women and 100 BC patients who attended the Mário Penna Institute between 2019 and 2022 was performed by flow cytometry. In addition, the MVs of BC patients were analyzed before treatment and 6, 12, and 24 months post-treatment. Machine learning approaches were employed to determine the performance of MVs to identify BC and to propose BC classifier algorithms. Results: Patients with BC had more neutrophil- and endothelial cell-derived MVs than controls before treatment. After treatment, all MV populations were decreased compared to pre-treatment, but leukocyte- and erythrocyte-derived MVs were increased at 12 months after treatment, before decreasing again at 24 months. Conclusions: Performance analyses and machine learning approaches pointed out that MVs from neutrophils and endothelial cells are the best candidates for BC diagnostic biomarkers. Neutrophil- and endothelial cell-derived MVs are putative candidates for BC biomarkers to be employed as screening tests for BC diagnosis.

Environmental Sustainability and Cancer Imaging

The rising global burden of cancer drives increased demands for medical imaging, which is essential throughout cancer care. However, delivering medical imaging presents significant environmental challenges including high energy use, reliance on single-use supplies, and the production of environmental pollutants. Environmental factors, such as ultraviolet radiation, wildfire smoke, and carcinogenic pollutants contribute to rising cancer rates, while extreme weather events driven by climate change disrupt cancer care delivery-highlighting the close connection between patient and planetary health. This review explores opportunities to improve the environmental sustainability of oncologic imaging, emphasizing the importance of patient-relevant outcomes-such as quality of life and overall survival-as a guiding principle in cancer care. Key strategies include optimizing imaging schedules to reduce low-value imaging, selecting modalities with lower environmental impact where clinically appropriate, minimizing waste streams, and adopting energy-efficient practices. Artificial intelligence offers the potential to personalize imaging schedules and improve efficiency, though its benefits must be weighed against energy use. Mobile imaging programs and integrated scheduling reduce patient travel-related emissions while promoting health equity, particularly in underserved communities. Future research should focus on optimizing imaging intervals to address patient-relevant outcomes better, expanding the use of abbreviated imaging protocols, and the judicious deployment of artificial intelligence, ensuring its benefits justify energy use.

Clinicopathological Predictors of the Presence of Blood Circulating Tumor DNA in Early-Stage Non-Small Cell Lung Cancers

The implementation of lung cancer screening programs across the world has drawn considerable attention to improving early-stage lung cancer detection and prognostication. Several blood-based assays detecting circulating tumor DNA (ctDNA) recently emerged as noninvasive methods to detect malignancies. However, their limited sensitivity and predictive value remain a hurdle to their clinical use. We aimed to evaluate the association between clinicopathological parameters and presurgical ctDNA detection in clinical stage I non-small cell lung cancer patients to further understand ctDNA shedding biology. The cohort included 180 adenocarcinomas (LUAD) and 80 squamous cell carcinomas (LUSC) stage I patients who underwent lung cancer resection. Patients' clinical and pathological features were collected. A multicancer early-detection test (GRAIL LLC) was used to detect ctDNA using targeted methylation patterns. The association between the cell-free DNA tumor methylated fraction (TMeF) and the clinicopathological predictors was evaluated using univariate and multivariate modeling. LUSC was associated with a higher TMeF than LUAD. Pathological stage, tumor grade, and tumor volume were key determinants of ctDNA detection in both LUSC and LUAD. In LUAD, ctDNA detection also correlated with histologic pattern composition, necrosis, acute inflammation, and, to a lesser degree, spread through alveolar spaces and lymphovascular invasion. Based on our results, we propose classification methods for both LUAD (using histologic pattern composition) and LUSC (using tumor grade and pathological stage) to identify patients likely to have high ctDNA levels. These results confirm previous findings and suggest that previously unidentified factors, including histologic pattern composition and acute inflammation, influence ctDNA levels. These results will help in understanding the ctDNA shedding process and may allow identification of patients eligible for ctDNA detection-based follow-up.

Application of plasma cell-free DNA in screening of advanced colorectal adenoma

BACKGROUND

Currently, due to the invasive nature of colonoscopy and the associated pain, people avoid undergoing the procedure, making it difficult to detect the majority of potential early stage colorectal carcinoma/precancerous lesions or advanced adenoma. Advanced colorectal adenoma is the main precursor to the development of colorectal carcinoma. Therefore, improving advanced colorectal adenoma detection rate can significantly decrease the development and morbidity of colorectal carcinoma. Accordingly, a non-invasive method to screen high-risk people for colonoscopy in clinical practice is urgently needed.

MAIN TEXT

With the development of medical technology, screening methods for colorectal carcinoma are emerging rapidly, and diverse non-invasive methods are being developed. Cell-free DNA (cfDNA), commonly referred to as liquid biopsy, has promising application prospects as a minimally invasive strategy for early screening of colorectal cancer. CfDNA has already been applied in the field of prenatal diagnosis, advanced carcinoma, and organ transplantation, and the application cfDNA in advanced colorectal adenoma is at the cutting-edge of current research. Thus, this review summarizes the progress in research on different biological characteristics of cfDNA and its utility in the screening of advanced colorectal adenoma, including sizes of cfDNA molecules, end signature of cfDNA (preferred ends, end motifs, jagged ends), nucleosomal footprints, cfDNA topology, cfDNA methylation, and cfDNA integrity.

CONCLUSIONS

We hope that this review will advance this promising research field.

Harnessing ferroptosis for precision oncology: challenges and prospects

The discovery of diverse molecular mechanisms of regulated cell death has opened new avenues for cancer therapy. Ferroptosis, a unique form of cell death driven by iron-catalyzed peroxidation of membrane phospholipids, holds particular promise for targeting resistant cancer types. This review critically examines current literature on ferroptosis, focusing on its defining features and therapeutic potential. We discuss how molecular profiling of tumors and liquid biopsies can generate extensive multi-omics datasets, which can be leveraged through machine learning-based analytical approaches for patient stratification. Addressing these challenges is essential for advancing the clinical integration of ferroptosis-driven treatments in cancer care.

A predictive model for neoadjuvant therapy response in breast cancer

Neoadjuvant therapy is a standard treatment for breast cancer, but its effectiveness varies among patients. This highlights the importance of developing accurate predictive models. Our study uses metabolomics and machine learning to predict the response to neoadjuvant therapy in breast cancer patients.

OBJECTIVE

To develop and validate predictive models using machine learning and circulating metabolites for forecasting responses to neoadjuvant therapy among breast cancer patients, enhancing personalized treatment strategies.

METHODS

Based on pathological analysis after neoadjuvant chemotherapy and surgery, this retrospective study analyzed 30 young women breast cancer patients from a single institution, categorized as responders or non-responders. Utilizing liquid chromatography-tandem mass spectrometry, we investigated the plasma metabolome, explicitly targeting 40 metabolites, to identify relevant biomarkers linked to therapy response, using machine learning to generate a predictive model and validate the results.

RESULTS

Eighteen significant biomarkers were identified, including specific acylcarnitines and amino acids. The most effective predictive model demonstrated a remarkable accuracy of 90.7% and an Area Under the Curve (AUC) of 0.999 at 95% confidence, illustrating its potential utility as a web-based application for future patient management. This model's reliability underscores the significant role of circulating metabolites in predicting therapy outcomes.

CONCLUSION

Our study's findings highlight the crucial role of metabolomics in advancing personalized medicine for breast cancer treatment by effectively identifying metabolite biomarkers correlated with neoadjuvant therapy response. This approach signifies a critical step towards tailoring treatment plans based on individual metabolic profiles, ultimately improving patient outcomes in breast cancer care.

A Highly Sensitive Methylation Assay for Prostate Cancer Diagnosis

PURPOSE

Prostate cancer is a prevalent malignancy among males, necessitating precise diagnosis for effective treatment and prognosis. However, there is a lack of accurate, reliable, and cost-effective methods for precise diagnosis of prostate cancer.

MATERIALS AND METHODS

The bisulfite-treated DNA was amplified by a blocker strand-assisted methylation-specific PCR method, and the signal was amplified by a guiding strand-assisted enzyme/probe detection system. On this basis, an Optimized DNA Methylation Detection Assay was developed. Fifty-five prostate cancer patients and 24 healthy patients were selected for blood/urine sample testing to evaluate the clinical value of the assay.

RESULTS

The experimental results showed that the detection limit of the Tri-Component Liquid Biopsy Assay reached 0.002%. Assays for six prostate cancer methylation variants were constructed and finally three sites, GSTP1, ADCY4, and HOXA7, were selected for the design of prostate cancer diagnostic panel. The differences in methylation were statistically significant. Additionally, evaluating this approach on liquid biopsies from prostate cancer patients, we obtained a sensitivity and specificity of 89% and 76% respectively. Meanwhile, the cost of a single test on this platform is about $7.5, and the testing time is only about 5 hours.

CONCLUSIONS

Here we have successfully developed a highly sensitive methylation assay for prostate cancer diagnosis that features both accuracy, efficiency, and low cost. Combined with the established detection panel, this method can realize accurate and non-invasive early diagnosis of prostate cancer, which substantially augments the pragmatic utility of liquid biopsy.

A scoping review of factors influencing the implementation of liquid biopsy for cancer care

BACKGROUND

Liquid biopsy (LB) offers a promising, minimally invasive alternative to traditional tissue biopsies in cancer care, enabling real-time monitoring and personalized treatment. Despite its potential, the routine implementation of LB in clinical practice faces significant challenges. This scoping review examines the barriers and facilitators influencing the implementation of liquid biopsies into standard cancer care.

METHODS

Four academic databases (PubMed, Scopus, Embase, and Web of Science) were systematically searched without language restrictions. We included peer-reviewed articles that were published between January 2019 and March 2024 that focused on the implementation of LB in cancer care or described barriers and facilitators to its implementation. Data relevant to the review objective, including key article characteristics; barriers and facilitators of implementation; and recommendations for advancement or optimisation; were extracted and analysed using thematic and visual network analyses.

RESULTS

The majority of the included articles were narrative review articles (84%), with most from China (24.2%) and the United States (20%). Thematic analysis identified four main categories and their associated barriers and facilitators to the implementation of LB in cancer care: (1) Laboratory and personnel requirements; (2) Disease specificity; (3) Biomarker-based liquid biopsy; and (4) Policy and regulation. The majority of barriers identified were concentrated in the pre-analytical phase, highlighting the lack of standardization in LB technologies and outcomes.

CONCLUSIONS

Through a thematic analysis of the barriers and facilitators to LB implementation, we present an integrated tool designed to encourage the standardization of testing methods for clinical practice guidelines in the field.

Preoperative circulating tumor cells level is associated with lymph node metastasis in patients with unifocal papillary thyroid carcinoma

OBJECTIVE

Unifocal papillary thyroid carcinoma (PTC) refers to thyroid cancer that has only one isolated lesion, it has also the possibility of lymph node metastasis (LNM). Circulating tumor cell (CTC) has been used to assist in the assessment of tumor progression, but the relationship between CTCs levels and LNM in unifocal PTC patients is unclear.

METHODS

The clinical records (age, gender, Hashimoto's thyroiditis, thyroid function, tumor size, invaded capsule (thyroid cancer penetrating the capsule), clinical stage, and LNM) of unifocal PTC patients in Meizhou People's Hospital were analyzed retrospectively. Receiver operating characteristic (ROC) curve analysis was used to determine the cutoff value of CTCs levels to distinguish LNM. The relationship between CTCs level and clinical features was analyzed. Logistic regression analysis was used to evaluate the relationship between CTCs and LNM.

RESULTS

A total of 507 unifocal PTC patients were included, and 198(39.1%) patients with LNM. The critical value of CTCs was 9.25 FU/3mL by ROC analysis, and 288(56.8%) unifocal PTC patients with preoperative CTC-positive(≥ 9.25 FU/3mL). The patients with positive CTCs had higher proportions of normal thyroid function (91.3% vs. 84.5%, p = 0.018), and LNM (44.1% vs. 32.4%, p = 0.008) than patients with negative. High preoperative CTCs level (≥ 9.25/<9.25 FU/3mL, odds ratio(OR): 1.653, 95% confidence interval(CI): 1.115-2.451, p = 0.012), tumor size > 1 cm (OR: 3.189, 95% CI: 2.069-4.913, p < 0.001), and invaded capsule (OR: 1.521, 95% CI: 1.005-2.302, p = 0.047) were associated with LNM among unifocal PTC in multivariate logistic regression analysis.

CONCLUSIONS

High preoperative CTCs level (≥ 9.25 FU/3mL), tumor size > 1 cm, and invaded capsule were associated with LNM among unifocal PTC.

The role of platelets in cancer: from their influence on tumor progression to their potential use in liquid biopsy

Platelets, anucleate blood cells essential for hemostasis, are increasingly recognized for their role in cancer, challenging the traditional notion of their sole involvement in blood coagulation. It has been demonstrated that platelets establish bidirectional communication with tumor cells, contributing to tumor progression and metastasis through diverse molecular mechanisms such as modulation of proliferation, angiogenesis, epithelial-mesenchymal transition, resistance to anoikis, immune evasion, extravasation, chemoresistance, among other processes. Reciprocally, cancer significantly alters platelets in their count and composition, including mRNA, non-coding RNA, proteins, and lipids, product of both internal synthesis and the uptake of tumor-derived molecules. This phenomenon gives rise to tumor-educated platelets (TEPs), which are emerging as promising tools for the development of liquid biopsies. In this review, we provide a detailed overview of the dynamic roles of platelets in tumor development and progression as well as their use in diagnosis and prognosis. We also provide our view on current limitations, challenges and future research areas, including the need to design more efficient strategies for their isolation and analysis, as well as the validation of their sensitivity and specificity through large-scale and rigorous clinical trials. This research will not only enable the evaluation of their clinical viability but could also open new opportunities to enhance diagnostic accuracy and develop personalized treatments in oncology.

Innovative laboratory techniques shaping cancer diagnosis and treatment in developing countries

Cancer is a major global health challenge, with approximately 19.3 million new cases and 10 million deaths estimated by 2020. Laboratory advancements in cancer detection have transformed diagnostic capabilities, particularly through the use of biomarkers that play crucial roles in risk assessment, therapy selection, and disease monitoring. Tumor histology, single-cell technology, flow cytometry, molecular imaging, liquid biopsy, immunoassays, and molecular diagnostics have emerged as pivotal tools for cancer detection. The integration of artificial intelligence, particularly deep learning and convolutional neural networks, has enhanced the diagnostic accuracy and data analysis capabilities. However, developing countries face significant challenges including financial constraints, inadequate healthcare infrastructure, and limited access to advanced diagnostic technologies. The impact of COVID-19 has further complicated cancer management in resource-limited settings. Future research should focus on precision medicine and early cancer diagnosis through sophisticated laboratory techniques to improve prognosis and health outcomes. This review examines the evolving landscape of cancer detection, focusing on laboratory research breakthroughs and limitations in developing countries, while providing recommendations for advancing tumor diagnostics in resource-constrained environments.

Detection of plasma circulating GD2 ganglioside in patients with neuroblastoma and age-matched healthy children. Diagnostic and prognostic evaluation

BACKGROUND

GD2 ganglioside, a known specific marker for neuroblastoma (NB), exists in different lipoforms, including C18 and C20, which are distinguished by the length of their fatty acid chains. C18 and C20 GD2 lipoforms can be simultaneously measured by liquid chromatography-tandem mass spectrometry (LC-MS/MS). We evaluated the diagnostic and prognostic performance of circulating GD2 levels in children with NB.

METHODS

Thirty microliters of peripheral blood (PB) plasma samples from 83 children with NB at diagnosis and 83 age-matched healthy controls were analyzed by LC-MS/MS. From stage M patients, 29 additional PB plasma samples were collected after induction therapy, 7 before and after immunotherapy, and 6 at relapse. For 22 stage M patients, bone marrow (BM) plasma samples were also collected at diagnosis.

RESULTS

C18 and C20 GD2 concentrations were significantly higher in children with NB than in controls. Receiver operating characteristic (ROC) analysis showed a cut-point of 44.1 and 0.47 nM for C18 and C20, respectively, able to discriminate with high specificity and sensitivity in patients with NB from controls. Circulating C18 and C20 levels in PB strongly correlated with those in BM. At diagnosis, C18 and C20 GD2 concentrations were significantly higher in stage M, deceased patients, and in those bearing tumors with MYCN amplification. ROC analysis identified prognostic cut points for the whole population, whereas only C20 concentrations above the cut points were significantly associated with a worse event-free survival of patients with stage M disease or with MYCN-amplified tumors. C18 and C20 plasma concentrations strongly decreased during treatment but increased at relapse.

CONCLUSIONS

Measurement of circulating GD2 seems to have prognostic power in the subsets of patients with stage M disease and with MYCN-amplified tumors, and be able to early detect relapse, thus its ability to monitor disease should be prospectively evaluated in future studies.

One-step diagnosis of infection and lung cancer using metagenomic sequencing

BACKGROUND

Traditional detection methods face challenges in meeting the diverse clinical needs for diagnosing both lung cancer and infections within a single test. Onco-mNGS has emerged as a promising solution capable of accurately identifying infectious pathogens and tumors simultaneously. However, critical evidence is still lacking regarding its diagnostic performance in distinguishing between pulmonary infections, tumors, and non-infectious, non-tumor conditions in real clinical settings.

METHODS

In this study, data were gathered from 223 participants presenting symptoms of lung infection or tumor who underwent Onco-mNGS testing. Patients were categorized into four groups based on clinical diagnoses: infection, tumor, tumor with infection, and non-infection-non-tumor. Comparisons were made across different groups, subtypes, and stages of lung cancer regarding copy number variation (CNV) patterns, microbiome compositions, and clinical detection indices.

RESULTS

Compared to conventional infection testing methods, Onco-mNGS demonstrates superior infection detection performance, boasting a sensitivity of 81.82%, specificity of 72.55%, and an overall accuracy of 77.58%. In lung cancer diagnosis, Onco-mNGS showcases excellent diagnostic capabilities with sensitivity, specificity, accuracy, positive predictive value, and negative predictive value reaching 88.46%, 100%, 91.41%, 100%, and 90.98%, respectively. In bronchoalveolar lavage fluid (BALF) samples, these values stand at 87.5%, 100%, 94.74%, 100%, and 91.67%, respectively. Notably, more abundant CNV mutation types and higher mutation rates were observed in adenocarcinoma (ADC) compared to squamous cell carcinoma (SCC). Concurrently, onco-mNGS data revealed specific enrichment of Capnocytophaga sputigeria in the ADC group and Candida parapsilosis in the SCC group. These species exhibited significant correlations with C reaction protein (CRP) and CA153 values. Furthermore, Haemophilus influenzae was enriched in the early-stage SCC group and significantly associated with CRP values.

CONCLUSIONS

Onco-mNGS has exhibited exceptional efficiencies in the detection and differentiation of infection and lung cancer. This study provides a novel technological option for achieving single-step precise and swift detection of lung cancer.

Decoding Benign Prostatic Hyperplasia: Insights from Multi-Fluid Metabolomic Analysis

With the rising incidence of benign prostatic hyperplasia (BPH) due to societal aging, accurate and early diagnosis has become increasingly critical. The clinical challenges associated with BPH diagnosis, particularly the lack of specific biomarkers that can differentiate BPH from other causes of lower urinary tract symptoms (LUTS). Here, matrix-assisted laser desorption/ionization mass spectrometry (MALDI MS) metabolomic detection platform utilizing urine and serum samples is applied to explore metabolic information and identify potential biomarkers in designed cohort. The nanoparticle-assisted platform demonstrated rapid analysis, minimal sample consumption, and high reproducibility. Employing a two-step grouping screening approach, the identification of urinary metabolic patterns (UMPs) is automated to distinguish healthy individuals from LUTS group, followed by the use of serum metabolic patterns (SMPs) to accurately identify BPH cases within the LUTS cohort, achieving an area under the curve (AUC) of 0.830 (95% CI: 0.802-0.851). Furthermore, eight BPH-sensitive metabolic markers are identified, confirming their uniform distribution across age groups (p > 0.05). This research contributes valuable insights for the early diagnosis and personalized treatment of BPH, enhancing clinical practice and patient care.

Clinical characteristics of EGFR-ctDNA shedders in EGFR-mutant NSCLC patients

BACKGROUND

Circulating tumor DNA (ctDNA) revolutionized the molecular diagnostics of lung cancer by enabling non-invasive, sensitive identification of actionable mutations. However, ctDNA analysis may be challenging due to tumor shedding variability, leading to false negative results. This study aims to understand the determinants for ctDNA shedding based on clinical characteristics of lung cancer patients, for a better interpretation of false negative results to be considered when ordering ctDNA analysis for clinical practice.

METHODS

Blood samples were collected from patients with stage IV EGFR-mutated (mEGFR) NSCLC before treatment and monitored until disease progression. EGFR was assessed on tissue by standard procedures, while EGFR status on ctDNA was tested using dPCR at baseline and at the first reassessment. NGS was used to evaluate patients mutational status at the progression of the disease.

RESULTS

A total of 40 mEGFR tissue samples were collected. Plasma samples were analyzed for mEGFR before starting the first line, 65 % of patients had detectable mEGFR in ctDNA ("shedders"). Higher ECOG PS (p = 0.04), bilateral localization of primary tumor (p = 0.04), and the presence of intrathoracic/extrathoracic disease (p = 0.05), were associated to mEGFR shedding. Shedders had shorter PFS compared to non-shedders (p = 0.03). Patients with detectable mEGFR in ctDNA at the first radiological assessment exhibited worse PFS compared to patients with ctDNA clearance (p = 0.05).

CONCLUSION

Our preliminary data demonstrate that specific clinical characteristics predict mEGFR shedding in ctDNA of NSCLC, suggesting a potential clinical applicability for understanding potential false negative results and appropriate reporting in clinical practice.

Inherently imperfect, inherently evolving - The pursuit of precision through biomarkers

Featuring a special section on cancer biomarkers, this issue of the Biomedical Journal highlights research on cfDNA, fecal miRNA, mitochondrial pathways, Epstein-Barr virus DNA, multi-biomarker panels combined with LC-MS-based methods, and circulating tumor cell (CTC) growth status as potential tools for cancer detection and management, including colorectal cancer, ovarian cancer, nasopharyngeal carcinoma, and hepatocellular carcinoma. Additionally, it explores the social stigma surrounding mpox, and discusses the achievements in miRNA research that earned the 2024 Nobel Prize in Physiology or Medicine. Advances in deep learning for trauma imaging are examined, alongside a review of decades of enterovirus research and current vaccination strategies. Other studies investigate the combined use of anthelmintic and antibiotic therapy for roundworm infection, and the application of a well-established Traditional Chinese Medicine herbal formula, commonly prescribed for gynecological conditions, against autoimmune hepatitis. Further articles elucidate the role of the nuclear receptor HNF4 in Schistosoma, mitochondrial dysfunction in acute kidney injury, the effects of astragalus polysaccharides on prostate cancer, and the use of deep learning to predict mortality from electrocardiograms.

Liquid biopsies and exosomal ncRNA: Transforming pancreatic cancer diagnostics and therapeutics

Pancreatic cancer is a highly fatal malignancy due to poor early detection rate and resistance to conventional therapies. This review examines the potential for liquid biopsy as a transformative technology to identify diagnostic and therapeutic targets in pancreatic cancer. Specifically, we explore emerging biomarkers such as exosomal non-coding RNAs (ncRNAs), circulating tumor DNA (ctDNA), and circulating tumor cells (CTCs). Tumor-derived exosomes contain nucleic acid and protein that reflect the unique molecular landscape of the malignancy and can serve as an alternative diagnostic approach vs traditional biomarkers like CA19-9. Herein we highlight exosomal miRNAs, lncRNAs, and other ncRNAs alongside ctDNA and CTC-based strategies, evaluating their combined ability to improve early detection, disease monitoring and treatment response. Furthermore, the therapeutic implications of ncRNAs such as lncRNA UCA1 and miR-3960 in chemoresistance and progression are also discussed via suppression of EZH2 and PTEN/AKT pathways. Emerging therapeutic strategies that target the immune response, epithelial-mesenchymal transition (EMT) and drug resistance are explored. This review demonstrates a paradigm shift in pancreatic cancer management toward personalized, less invasive and more effective approaches.

Enhancing Cancer Screening and Early Diagnosis in India: Overcoming Challenges and Leveraging Emerging Technologies

This review addresses the significant challenges and technological developments in cancer screening and early diagnosis in the context of India's diverse and resource-constrained healthcare landscape. Selected cancers like breast, cervical, oral, lung, and colorectal cancers are focused on, and established screening methods such as clinical breast examination (CBE), mammography, visual inspection with acetic acid (VIA), HPV DNA testing, and oral visual inspection (OVI) are reviewed. These are cost-effective strategies that are proven to reduce mortality. However, they face systemic barriers, including low awareness, socio-cultural stigma, and discontinuous healthcare access. Emerging technologies in cancer screening like liquid biopsy (detecting circulating tumor DNA), artificial intelligence (AI)-driven imaging (enhancing radiological accuracy), next-generation sequencing (identifying genetic mutations), and methylation-based ctDNA analysis (epigenetic profiling) are considered to be transformative in cancer management. Digital pathology and telemedicine are also found to improve diagnostic precision and rural/remote outreach. However, high costs, technical complexity, and limited validation in Indian settings are the major challenges that hinder their widespread adoption. The review emphasizes the need for culturally tailored awareness campaigns, integration of screening with the already existing public health programs, and increased investments in indigenous research to address genetic and environmental risk factors. It specifically advocates for strengthening the primary healthcare infrastructure, training community health workers, and leveraging mobile screening units to bridge urban-rural disparities. A combination of scalable low-resource methods and strategic adoption of emerging technologies can help in mitigating India's growing cancer burden. This aligns with global targets to reduce premature non-communicable disease (NCD) mortality by 2030. This synthesis of evidence-based practices and innovative strategies offers a roadmap for policymakers and stakeholders to enhance equitable cancer care delivery nationwide.

Epigenetic regulation in coronary artery disease: from mechanisms to emerging therapies

Atherosclerosis, the primary cause of coronary artery disease (CAD), remains a leading global cause of mortality. It is characterized by the accumulation of cholesterol-rich plaques and inflammation, which narrow the coronary arteries and increase the risk of rupture. To elucidate this complex biological process and improve therapeutic strategies, CAD has been extensively explored from an epigenetic perspective over the past two decades. Epigenetics is a field investigating heritable alterations in gene expression without DNA sequence changes, such as DNA methylation, histone modifications, and non-coding RNAs. Increasing evidence has indicated that the development of CAD is significantly influenced by epigenetic changes. Meanwhile, the impact of epigenetics in CAD is now transitioning from pathophysiology to therapeutics. Focusing on the key epigenetic enzymes and their target genes will help to facilitate the diagnosis and treatment of CAD. This review synthesizes novel epigenetic insights into CAD, addressing the pathological processes, key molecular mechanisms, and potential biomarkers. Furthermore, we discuss emerging therapeutic strategies targeting epigenetic pathways. By focusing on pivotal enzymes and their associated genes, this work aims to advance CAD diagnostics and interventions.

Minimally invasive biomarkers for triaging lung nodules-challenges and future perspectives

CT chest scans are commonly performed worldwide, either in routine clinical practice for a wide range of indications or as part of lung cancer screening programs. Many of these scans detect lung nodules, which are small, rounded opacities measuring 8-30 mm. While the concern about nodules is that they may represent early lung cancer, in screening programs, only 1% of such nodules turn out to be cancer. This leads to a series of complex decisions and, at times, unnecessary biopsies for nodules that are ultimately determined to be benign. Additionally, patients may be anxious about the status of detected lung nodules. The high rate of false positive lung nodule detections has driven advancements in biomarker-based research aimed at triaging lung nodules (benign versus malignant) to identify truly malignant nodules better. Biomarkers found in biofluids and breath hold promise owing to their minimally invasive sampling methods, ease of use, and cost-effectiveness. Although several biomarkers have demonstrated clinical utility, their sensitivity and specificity are still relatively low. Combining multiple biomarkers could enhance the characterisation of small pulmonary nodules by addressing the limitations of individual biomarkers. This approach may help reduce unnecessary invasive procedures and accelerate diagnosis in the future. This review offers a thorough overview of emerging minimally invasive biomarkers for triaging lung nodules, emphasising key challenges and proposing potential solutions for biomarker-based nodule differentiation. It focuses on diagnosis rather than screening, analysing research published primarily in the past five years with some exceptions. The incorporation of biomarkers into clinical practice will facilitate the early detection of malignant nodules, leading to timely interventions and improved outcomes. Further efforts are needed to increase the cost-effectiveness and practicality of many of these applications in clinical settings. However, the range of technologies is advancing rapidly, and they may soon be implemented in clinics in the near future.

CTCs Detection Methods In Vivo and In Vitro and Their Application in Tumor Immunotherapy

Circulating tumor cells (CTCs) are tumor cells that detach from the primary tumor site and enter the bloodstream. They hold significant value for the early detection, diagnosis, and treatment of tumors. CTC detection methods can be classified into in vivo and in vitro techniques. Compared to traditional tumor detection methods, CTC detection causes less harm to the body and allows for earlier identification of malignant tumors, thereby enabling timely treatment and improving patient survival rates. In recent years, CTC detection has been widely used to assess the effectiveness of tumor immunotherapy. Dynamic monitoring of CTCs can help optimize clinical treatment strategies. This review summarizes the latest in vivo and in vitro detection methods for CTCs and discusses their applications in immunotherapy for various common tumors, aiming to provide better guidance and support for clinical practice.

Immunolipid magnetic bead-based circulating tumor cell sorting: a novel approach for pathological staging of colorectal cancer

Objective

This study aimed to assess whether circulating tumor cells (CTCs) from colorectal cancer (CRC) could be used as an alternative to tissue samples for genetic mutation testing, overcoming the challenge of difficult tumor tissue acquisition.

Methods

We developed an immunolipid magnetic bead (IMB) system modified with antibodies against epithelial cell adhesion molecule (EpCAM) and vimentin to efficiently separate CTCs. We prepared EpCAM-modified IMBs (Ep-IMBs) and vimentin-modified IMBs (Vi-IMBs). The separation efficiency of the system was evaluated via in vitro experiments and by capturing and counting CTCs in blood samples from 23 CRC patients and 20 healthy controls. Hotspot mutations in patient tissue samples were identified via next-generation sequencing (NGS), whereas mutations in blood CTCs were detected via Sanger sequencing. The concordance between hotspot mutations in tumor tissue and blood CTCs was analyzed.

Results

The CTC sorting system exhibited good dispersion, stability, and low cytotoxicity, with a specificity of 90.54% and a sensitivity of 89.07%. CRC patients had an average of 8.39 CTCs per 7.5 mL of blood, whereas healthy controls had 0.09 per 7.5 mL of blood. The consistency of gene mutations was as follows: TP53 (91.31%), PIK3CA (76.00%), KRAS (85.36%), BRAF (51.00%), APC (65.67%), and EGFR (74.00%), with an overall gene mutation consistency of 85.06%.

Conclusion

Our CTC sorting system, which is based on Ep-IMBs and Vi-IMBs, effectively captures CTCs in the peripheral blood of CRC patients and enables clinical hotspot gene mutation testing via these enriched CTCs. This system partially solves the problem of difficult tumor tissue sample collection and provides a reference for gene mutation testing in early diagnosis, therapeutic efficacy evaluation, prognosis assessment, and minimal metastasis detection in CRC patients, showing significant potential for clinical application, especially in targeted therapy gene testing for CRC.