Circulating tumor DNA analysis for tumor diagnosis

DNA/RNA-based electrochemical nanobiosensors for early detection of cancers

Nucleic acids, like DNA and RNA, serve as versatile recognition elements in electrochemical biosensors, demonstrating notable efficacy in detecting various cancer biomarkers with high sensitivity and selectivity. These biosensors offer advantages such as cost-effectiveness, rapid response, ease of operation, and minimal sample preparation. This review provides a comprehensive overview of recent developments in nucleic acid-based electrochemical biosensors for cancer diagnosis, comparing them with antibody-based counterparts. Specific examples targeting key cancer biomarkers, including prostate-specific antigen, microRNA-21, and carcinoembryonic antigen, are highlighted. The discussion delves into challenges and limitations, encompassing stability, reproducibility, interference, and standardization issues. The review suggests future research directions, exploring new nucleic acid recognition elements, innovative transducer materials and designs, novel signal amplification strategies, and integration with microfluidic devices or portable instruments. Evaluating these biosensors in clinical settings using actual samples from cancer patients or healthy donors is emphasized. These sensors are sensitive and specific at detecting non-communicable and communicable disease biomarkers. DNA and RNA's self-assembly, programmability, catalytic activity, and dynamic behavior enable adaptable sensing platforms. They can increase biosensor biocompatibility, stability, signal transduction, and amplification with nanomaterials. In conclusion, nucleic acids-based electrochemical biosensors hold significant potential to enhance cancer detection and treatment through early and accurate diagnosis.

Impact of Molecular Profiling on Therapy Management in Breast Cancer

Breast cancer (BC) remains the most prevalent cancer among women and the leading cause of cancer-related mortality worldwide. The heterogeneity of BC in terms of histopathological features, genetic polymorphisms, and response to therapies necessitates a personalized approach to treatment. This review focuses on the impact of molecular profiling on therapy management in breast cancer, emphasizing recent advancements in next-generation sequencing (NGS) and liquid biopsies. These technologies enable the identification of specific molecular subtypes and the detection of blood-based biomarkers such as circulating tumor cells (CTCs), circulating tumor DNA (ctDNA), and tumor-educated platelets (TEPs). The integration of molecular profiling with traditional clinical and pathological data allows for more tailored and effective treatment strategies, improving patient outcomes. This review also discusses the current challenges and prospects of implementing personalized cancer therapy, highlighting the potential of molecular profiling to revolutionize BC management through more precise prognostic and therapeutic interventions.

Latest Research Progress of Liquid Biopsy in Tumor-A Narrative Review

Human life expectancy is significantly impacted by cancer, with liquid biopsy emerging as an advantageous method for cancer detection because of its noninvasive nature, high accuracy, ease of sampling, and cost-effectiveness compared with conventional tissue biopsy techniques. Liquid biopsy shows promise in early cancer detection, real-time monitoring, and personalized treatment for various cancers, including lung, cervical, and prostate cancers, and offers innovative approaches for cancer diagnosis and management. By utilizing circulating tumor DNA, circulating tumor cells, and exosomes as biomarkers, liquid biopsy enables the tracking of cancer progression. Various techniques commonly used in life sciences research, such as polymerase chain reaction (PCR), next-generation sequencing (NGS), and droplet digital PCR, are employed to assess cancer progression on the basis of different indicators. This review examines the latest advancements in liquid biopsy markers-circulating tumor DNA (ctDNA), circulating tumor cells (CTCs), and exosomes-for cancer diagnosis over the past three years, with a focus on their detection methodologies and clinical applications. It encapsulates the pivotal aims of liquid biopsy, including early detection, therapy response prediction, treatment monitoring, prognostication, and its relevance in minimal residual disease, while also addressing the challenges facing routine clinical adoption. By combining the latest research advancements and practical clinical experiences, this work focuses on discussing the clinical significance of DNA methylation biomarkers and their applications in tumor screening, auxiliary diagnosis, companion diagnosis, and recurrence monitoring. These discussions may help enhance the application of liquid biopsy throughout the entire process of tumor diagnosis and treatment, thereby providing patients with more precise and effective treatment plans.

Phenotyping Tumor Heterogeneity through Proteogenomics: Study Models and Challenges

Tumor heterogeneity refers to the diversity observed among tumor cells: both between different tumors (inter-tumor heterogeneity) and within a single tumor (intra-tumor heterogeneity). These cells can display distinct morphological and phenotypic characteristics, including variations in cellular morphology, metastatic potential and variability treatment responses among patients. Therefore, a comprehensive understanding of such heterogeneity is necessary for deciphering tumor-specific mechanisms that may be diagnostically and therapeutically valuable. Innovative and multidisciplinary approaches are needed to understand this complex feature. In this context, proteogenomics has been emerging as a significant resource for integrating omics fields such as genomics and proteomics. By combining data obtained from both Next-Generation Sequencing (NGS) technologies and mass spectrometry (MS) analyses, proteogenomics aims to provide a comprehensive view of tumor heterogeneity. This approach reveals molecular alterations and phenotypic features related to tumor subtypes, potentially identifying therapeutic biomarkers. Many achievements have been made; however, despite continuous advances in proteogenomics-based methodologies, several challenges remain: in particular the limitations in sensitivity and specificity and the lack of optimal study models. This review highlights the impact of proteogenomics on characterizing tumor phenotypes, focusing on the critical challenges and current limitations of its use in different clinical and preclinical models for tumor phenotypic characterization.

Imaging and Liquid Biopsy for Distinguishing True Progression From Pseudoprogression in Gliomas, Current Advances and Challenges

RATIONALE AND OBJECTIVES

Gliomas are aggressive brain tumors with a poor prognosis. Assessing treatment response is challenging because magnetic resonance imaging (MRI) may not distinguish true progression (TP) from pseudoprogression (PsP). This review aims to discuss imaging techniques and liquid biopsies used to distinguish TP from PsP.

MATERIALS AND METHODS

This review synthesizes existing literature to examine advances in imaging techniques, such as magnetic resonance diffusion imaging (MRDI), perfusion-weighted imaging (PWI) MRI, and liquid biopsies, for identifying TP or PsP through tumor markers and tissue characteristics.

RESULTS

Advanced imaging techniques, including MRDI and PWI MRI, have proven effective in delineating tumor tissue properties, offering valuable insights into glioma behavior. Similarly, liquid biopsy has emerged as a potent tool for identifying tumor-derived markers in biofluids, offering a non-invasive glimpse into tumor evolution. Despite their promise, these methodologies grapple with significant challenges. Their sensitivity remains inconsistent, complicating the accurate differentiation between TP and PSP. Furthermore, the absence of standardized protocols across platforms impedes the reliability of comparisons, while inherent biological variability adds complexity to data interpretation.

CONCLUSION

Their potential applications have been highlighted, but gaps remain before routine clinical use. Further research is needed to develop and validate these promising methods for distinguishing TP from PsP in gliomas.

It was not possible to detect BRAF V600E mutation in circulating cell-free DNA from patients with ameloblastoma: A diagnostic accuracy study

BACKGROUND

The objective of this study is to evaluate the diagnostic accuracy of plasma-based liquid biopsy for the detection of the BRAF V600E mutation in circulating cell-free DNA from patients with ameloblastoma.

METHODS

This is a prospective diagnostic accuracy study conducted based on the Standards for Reporting Diagnostic Accuracy recommendations. The index test was the plasma-based liquid biopsy, whereas the reference standard was the conventional tissue biopsy. The target condition was the detection of BRAF V600E mutation. The study population consisted of individuals with ameloblastoma recruited from three tertiary hospitals from Brazil. A negative control group composed of three individuals with confirmed wild-type BRAF lesions were included. The participants underwent plasma circulating cell-free DNA and tumor tissue DNA isolation, and both were submitted to using competitive allele-specific TaqMan™ real-time polymerase chain reaction technology mutation detection assays. Sensitivity and specificity measures and positive and negative predictive values were calculated.

RESULTS

Twelve patients with conventional ameloblastoma were included. BRAF V600E mutation was detected in 11/12 (91.66%) ameloblastoma tissue samples. However, the mutation was not detected in any of the plasma-based liquid biopsy circulating cell-free DNA samples in both ameloblastomas and negative control group. The sensitivity and specificity of plasma-based liquid biopsy for the detection of the BRAF V600E mutation in circulating cell-free DNA was 0.0 and 1.0, respectively. The agreement between index test and reference standard results was 26.66%.

CONCLUSION

Plasma-based liquid biopsy does not seem to be an accurate method for the detection of the BRAF V600E mutation in circulating circulating cell-free DNA from patients with ameloblastoma, regardless of tumor size, anatomic location, recurrence status, and other clinicopathological features.

Advances in Cancer Research: Current and Future Diagnostic and Therapeutic Strategies

Cancers of unknown primary (CUP) exhibit significant cellular heterogeneity and malignancy, which poses significant challenges for diagnosis and treatment. Recent years have seen deeper insights into the imaging, pathology, and genetic characteristics of CUP, driven by interdisciplinary collaboration and the evolution of diagnostic and therapeutic strategies. However, due to their insidious onset, lack of evidence-based medicine, and limited clinical understanding, diagnosing and treating CUP remain a significant challenge. To inspire more creative and fantastic research, herein, we report and highlight recent advances in the diagnosis and therapeutic strategies of CUP. Specifically, we discuss advanced diagnostic technologies, including 12-deoxy-2-[fluorine-18]fluoro-D-glucose integrated with computed tomography (18F-FDG PET/CT) or 68Ga-FAPI (fibroblast activation protein inhibitor) PET/CT, liquid biopsy, molecular diagnostics, self-assembling nanotechnology, and artificial intelligence (AI). In particular, the discussion will extend to the effective treatment techniques currently available, such as targeted therapies, immunotherapies, and bio-nanotechnology-based therapeutics. Finally, a novel perspective on the challenges and directions for future CUP diagnostic and therapeutic strategies is discussed.

RLP system: A single-tube two-step approach with dual amplification cascades for rapid identification of EGFR T790M

BACKGROUND

The detection of cancer gene mutations in biofluids plays a pivotal role in revolutionizing disease diagnosis. The presence of a large background of wild-type sequences poses a challenge to liquid biopsy of tumor mutation genes. Suppressing the detection of wild-type sequences can reduce their interference, however, due to the minimal difference between mutant and wild-type sequences (such as single nucleotide variants differing by only one nucleotide), how to suppress the detection of wild-type sequences to the greatest extent without compromising the sensitivity of mutant sequence detection remains to be explored.

SIGNIFICANCE

The RLP system addresses the incompatibility between RPA and RT-PCR reactions through a physical separation strategy. Besides, due to the remarkable flexibility of locked nucleic acid probes, the RLP system emerges as a potent tool for detecting mutations across diverse genes. It excels in sensitivity and speed, tolerates plasma matrix, and is cost-effective. This bodes well for advancing the field of precision medicine.

RESULTS

The recombinase-assisted locked nucleic acid (LNA) probe-mediated dual amplification biosensing platform (namely RLP), which combines recombinase polymerase amplification (RPA) and LNA clamp PCR method in one tube, enabling highly sensitive and selective detection of EGFR T790M mutation under the help of well-designed LNA probes. This technique can quantify DNA targets with a limit of detection (LoD) at the single copy level and identify point mutation with mutant allelic fractions as low as 0.007 % in 45 min. Moreover, RLP has the potential for the direct detection of plasma samples without the need for nucleic acid extraction and the cost of a single test is less than 1USD. Furthermore, the RLP system is a cascading dual amplification reaction conducted in a single tube, which eliminates the risk of cross-contamination associated with opening multiple tubes and ensures the reliability of the results.

An approach for integrating droplet generation and detection in digital polymerase chain reaction applications based on a bifunctional microfluidic cross-structure

Digital polymerase chain reaction (dPCR) is an approach for absolute nucleic acid quantification with high sensitivity. Although several successful commercial dPCR devices have been developed to date, further miniaturizing device dimensions, decreasing cross-contamination, and improving automation level are still research highlights. In this study, we developed a fully contamination-free dPCR detection chip with fluorescence flow cytometry and micro droplet approach. A bifunctional cross-structure (BFCS) was designed to realize monodisperse sample droplet generation in forward flow and droplet detection in backward flow with simple pneumatic control and fixed chip position. In order to improve droplet detection efficiency and accuracy, droplets morphology and sequence pattern during microfluidic droplet generation and backward flow droplet detection at the same cross-structure were observed and analyzed under different pneumatic pressures. In addition, during backward flow droplet detection, an optimized declination angle of the chip was applied to increase droplet reflux rates. For the validation of PCR performance, temperature changing processes during PCR cycles were achieved by heating the monodispersed droplet array with a customized PCR amplification device. The fluorescence signal of each droplet right after passing the cross-structure was excitated and detected. The absolute quantification ability of our integrated dPCR microfluidic chip utilizing flow fluorescence cytometry was tested and verified with Influenza A virus gene (from 7.5 copies/μL to 30000 copies/μL). Thus, our platform provides a novel and integrated approach for ddPCR analysis.

Microfluidics-based patient-derived disease detection tool for deep learning-assisted precision medicine

Cancer spatial and temporal heterogeneity fuels resistance to therapies. To realize the routine assessment of cancer prognosis and treatment, we demonstrate the development of an Intelligent Disease Detection Tool (IDDT), a microfluidic-based tumor model integrated with deep learning-assisted algorithmic analysis. IDDT was clinically validated with liquid blood biopsy samples (n = 71) from patients with various types of cancers (e.g., breast, gastric, and lung cancer) and healthy donors, requiring low sample volume (∼200 μl) and a high-throughput 3D tumor culturing system (∼300 tumor clusters). To support automated algorithmic analysis, intelligent decision-making, and precise segmentation, we designed and developed an integrative deep neural network, which includes Mask Region-Based Convolutional Neural Network (Mask R-CNN), vision transformer, and Segment Anything Model (SAM). Our approach significantly reduces the manual labeling time by up to 90% with a high mean Intersection Over Union (mIoU) of 0.902 and immediate results (<2 s per image) for clinical cohort classification. The IDDT can accurately stratify healthy donors (n = 12) and cancer patients (n = 55) within their respective treatment cycle and cancer stage, resulting in high precision (∼99.3%) and high sensitivity (∼98%). We envision that our patient-centric IDDT provides an intelligent, label-free, and cost-effective approach to help clinicians make precise medical decisions and tailor treatment strategies for each patient.

Identification of monotonically expressed long non-coding RNA signatures for breast cancer using variational autoencoders

As breast cancer is a multistage progression disease resulting from a genetic sequence of mutations, understanding the genes whose expression values increase or decrease monotonically across pathologic stages can provide insightful clues about how breast cancer initiates and advances. Utilizing variational autoencoder (VAE) networks in conjunction with traditional statistical testing, we successfully ascertain long non-coding RNAs (lncRNAs) that exhibit monotonically differential expression values in breast cancer. Subsequently, we validate that the identified lncRNAs really present monotonically changed patterns. The proposed procedure identified 248 monotonically decreasing expressed and 115 increasing expressed lncRNAs. They correspond to a total of 65 and 33 genes respectively, which possess unique known gene symbols. Some of them are associated with breast cancer, as suggested by previous studies. Furthermore, enriched pathways by the target mRNAs of these identified lncRNAs include the Wnt signaling pathway, human papillomavirus (HPV) infection, and Rap 1 signaling pathway, which have been shown to play crucial roles in the initiation and development of breast cancer. Additionally, we trained a VAE model using the entire dataset. To assess the effectiveness of the identified lncRNAs, a microarray dataset was employed as the test set. The results obtained from this evaluation were deemed satisfactory. In conclusion, further experimental validation of these lncRNAs with a large-sized study is warranted, and the proposed procedure is highly recommended.

Blood-based liquid biopsy: insights into early detection, prediction, and treatment monitoring of bladder cancer

Bladder cancer (BC) is a clinical challenge worldwide with late clinical presentation, poor prognosis, and low survival rates. Traditional cystoscopy and tissue biopsy are routine methods for the diagnosis, prognosis, and monitoring of BC. However, due to the heterogeneity and limitations of tumors, such as aggressiveness, high cost, and limited applicability of longitudinal surveillance, the identification of tumor markers has attracted significant attention in BC. Over the past decade, liquid biopsies (e.g., blood) have proven to be highly efficient methods for the discovery of BC biomarkers. This noninvasive sampling method is used to analyze unique tumor components released into the peripheral circulation and allows serial sampling and longitudinal monitoring of tumor progression. Several liquid biopsy biomarkers are being extensively studied and have shown promising results in clinical applications of BC, including early detection, detection of microscopic residual disease, prediction of recurrence, and response to therapy. Therefore, in this review, we aim to provide an update on various novel blood-based liquid biopsy markers and review the advantages and current limitations of liquid biopsy in BC therapy. The role of blood-based circulating tumor cells, circulating tumor DNA, cell-free RNA, exosomes, metabolomics, and proteomics in diagnosis, prognosis, and treatment monitoring, and their applicability to the personalized management of BC, are highlighted.

Development of a hybridization chain reaction-powered lab-on-fiber device for ultrafast point-of-care testing of circulating tuor DNA in whole blood

Circulating tumor DNA (ctDNA) demonstrates great promise in the guidance of prognostication, diagnosis, and surveillance of cancers, which highlights the need for rapid and sensitive point-of-care testing (POCT) technologies. Hybridization chain reaction (HCR)-based optical biosensors provide excellent solutions due to their prominent features. However, the requirement of a sophisticated and expensive optical readout device, relatively long detection time, and heating hold back their scalability and clinical applications. Here, an innovative HCR-powered lab-on-fiber device (HCR-LOFD) was developed for rapid on-site detection of ctDNA with high sensitivity, specificity, and reproducibility. A LOFD with a compact all-fiber optical structure was constructed for the fluorescence detection of the HCR system. Combining HCR, fluorescence energy resonant transfer, and the evanescent wave fluorescence principle, HCR-LOFD achieved the quantitative detection of KRAS G12D, the 12th amino acid from glycine (Gly) mutated aspartate (Asp) and the most common mutation of KARS, in 5 min at room temperature based on end-point detection mode or real-time fluorescence detection mode. This new assay platform was also successfully applied for the direct detection of KRAS G12D in whole blood with simple dilution. The application of HCR-LOFD not only greatly simplifies the complexity of optical readout devices and improves their scalability but also potentially serves as a sample-to-answer solution for the detection of biomarkers in limited medical resource regions.

Circulating Histones to Detect and Monitor the Progression of Cancer

Liquid biopsies have emerged as a minimally invasive cancer detection and monitoring method, which could identify cancer-related alterations in nucleosome or histone levels and modifications in blood, saliva, and urine. Histones, the core component of the nucleosome, are essential for chromatin compaction and gene expression modulation. Increasing evidence suggests that circulating histones and histone complexes, originating from cell death or immune cell activation, could act as promising biomarkers for cancer detection and management. In this review, we provide an overview of circulating histones as a powerful liquid biopsy approach and methods for their detection. We highlight current knowledge on circulating histones in hematologic malignancies and solid cancer, with a focus on their role in cancer dissemination, monitoring, and tumorigenesis. Last, we describe recently developed strategies to identify cancer tissue-of-origin in blood plasma based on nucleosome positioning, inferred from nucleosomal DNA fragmentation footprint, which is independent of the genetic landscape.

Folic acid-modified disulfiram/Zn-IRMOF3 nanoparticles for oral cancer therapy by inhibiting ALDH1A1+ cancer stem cells

The repurposing of old drugs can reduce the cost of drug development and speed up the availability of drugs for clinical use. Disulfiram (DSF) is an approved drug for alcohol abuse. In recent years, it has been established that DSF exerts an antitumor effect via targeted inhibition of ALDH1+ cancer stem cells (CSCs). However, due to its metal ion dependence, easy hydrolysis and low availability, the clinical application of DSF is limited. Previous studies have also shown that Zn²⁺ can inhibit CSCs. Accordingly, we developed a novel metal organic framework (IRMOF3)-Zn²⁺, and DSF was incorporated in the IRMOF3. Folic acid (FA) was subsequently loaded on the surface yielding IRMOF3 (IRMOF3-DSF-FA) for targeted therapy of tumors. The nanoscale IRMOF3-DSF-FA exhibited a high loading capacity, good biocompatibility and strong cell uptake capacity, which could provide metal ions, target tumor tissues and inhibit ALDH1+ CSCs. In vivo experiments showed that IRMOF3-DSF-FA could significantly inhibit the growth of CSCs and tumors, with no significant vital organ damage during treatment. Accordingly, IRMOF3-DSF-FA has great prospects for application as a DSF carrier, opening new horizons for targeted therapy of oral cancer.

Highly accurate diagnosis of lung adenocarcinoma and squamous cell carcinoma tissues by deep learning

Intraoperative detection of the marginal tissues is the last and most important step to complete the resection of adenocarcinoma and squamous cell carcinoma. However, the current intraoperative diagnosis is time-consuming and requires numerous steps including staining. In this paper, we present the use of Raman spectroscopy with deep learning to achieve accurate diagnosis with stain-free process. To make the spectrum more suitable for deep learning, we utilize an unusual way of thinking which regards Raman spectral signal as a sequence and then converts it into two-dimensional Raman spectrogram by short-time Fourier transform as input. The normal-adenocarcinoma deep learning model and normal-squamous carcinoma deep learning model both achieve more than 96% accuracy, 95% sensitivity and 98% specificity when test, which higher than the conventional principal components analysis-linear discriminant analysis method with normal-adenocarcinoma model (0.896 accuracy, 0.867 sensitivity, 0.926 specificity) and normal-squamous carcinoma model (0.821 accuracy, 0.776 sensitivity, 1.000 specificity). The high performance of deep learning models provides a reliable way for intraoperative detection of marginal tissue, and is expected to reduce the detection time and save human lives.

Exosomes-mediated tumor treatment: One body plays multiple roles

Exosomes are vesicles secreted by a variety of living cells, containing proteins, RNA and other components, which are nanoscale capsules commonly existed in the body. Exosomes play important roles in a variety of physiological and pathological processes by participating in material and information exchange between cells, which can play multiple roles in tumor treatment. On the one hand, exosomes can be used as carriers and biomarkers, participate in the apoptosis signaling pathway and improve chemotherapy resistance, thus playing beneficial roles in tumor treatment. On the other hand, exosomes play unfavorable roles in tumor treatment. Tumor cell exosomes contain PD-L1, which is a nuclear weapon for tumor growth, metastasis, and immunosuppression. In addition, exosomes can not only promote the epithelial-mesenchymal transition process, tumor angiogenesis and chemoresistance, but also participate in the autocrine pathway. In this review, the multiple roles of exosomes and their prospects in the treatment of tumor were reviewed in detail.