Circulating tumor DNA: current challenges for clinical utility

Multidimensional differences of right- and left-sided colorectal cancer and their impact on targeted therapies

Despite advances in metastatic colorectal cancer (mCRC) treatment, long-term survival remains poor, particularly in right-sided colorectal cancer (RCRC), which has a worse prognosis compared to left-sided CRC (LCRC). This disparity is driven by the complex biological diversity of these malignancies. RCRC and LCRC differ not only in clinical presentation and outcomes but also in their underlying molecular and genetic profiles. This article offers a detailed literature review focusing on the distinctions between RCRC and LCRC. We explore key differences across embryology, anatomy, pathology, omics, and the tumor microenvironment (TME), providing insights into how these factors contribute to prognosis and therapeutic responses. Furthermore, we examine the therapeutic implications of these differences, considering whether the conventional classification of CRC into right- and left-sided forms should be refined. Recent molecular findings suggest that this binary classification may overlook critical biological complexities. Therefore, we propose that future approaches should integrate molecular insights to better guide personalized treatments, especially anti-EGFR therapies, and improve patient outcomes.

Prognostic significance of circulating tumor DNA detection and quantification in cervical cancer: a systematic review and meta-analysis

Background

Circulating tumor DNA (ctDNA) is an emerging biomarker in cervical cancer, with elevated levels typically indicating a higher tumor burden. However, its prognostic value in cervical cancer patients remains debated. This meta-analysis aims to clarify the prognostic significance of ctDNA in this patient population.

Methods

We searched the PubMed, Cochrane Library, CNKI, and EMBASE databases for studies published up to September 30, 2024, to investigate the prognostic significance of ctDNA in cervical cancer patients. The outcome measures included overall survival (OS) and progression-free survival (PFS)/disease-free survival (DFS).

Results

This analysis included 10 studies encompassing a total of 706 cervical cancer patients. Findings revealed that patients with detectable baseline ctDNA had significantly poorer OS(HR = 1.64, 95% CI = 1.45-1.86, P < 0.001) as well as worse PFS or DFS (HR = 1.42, 95% CI = 1.07-1.89, P = 0.015). Additionally, ctDNA detectability during treatment was strongly associated with poorer OS (HR = 17.22, 95% CI = 4.43-66.89, P < 0.001) and PFS/DFS (HR = 4.16, 95% CI = 2.57-6.73, P < 0.001).

Conclusions

This meta-analysis demonstrates that elevated ctDNA levels are significantly associated with poorer PFS, DFS, and OS in patients with cervical cancer. However, data regarding the association between ctDNA levels and OS are relatively limited, and the number of included studies remains small, with a potential risk of publication bias. Based on the current evidence, ctDNA shows promise as a valuable tool for pre-treatment assessment and an effective biomarker for monitoring therapeutic response and disease progression. Further large-scale, prospective studies are warranted to validate these findings and establish their reliability and clinical applicability.

Systematic Review Registration

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Novel Methods to Assess Tumor Burden and Minimal Residual Disease in Genitourinary Cancers

BACKGROUND AND OBJECTIVE

Advances in molecular diagnostics have ushered in a new era for patients with prostate, renal, and urothelial cancers, with novel radiographic and molecular modalities for the assessment of disease burden and minimal residual disease (MRD). Conventional imaging has a limited threshold for disease detection and is often unable to discern clinically occult disease with varying risks of false-negative or false-positive findings depending on the disease state and type of imaging.

METHODS

We provide an overview of emerging radiographic and molecular tools in development within the genitourinary (GU) disease space. A literature review of contemporary basic, translational, and clinical research studies was performed, covering the timeframe of 1980-2024 through the MEDLINE (via PubMed) and Scopus databases. We highlight select examples of emerging technologies and biomarker-informed clinical trials, which aim to quantify disease at lower thresholds and have the potential for integrating MRD in clinical practice for GU patients.

KEY FINDINGS AND LIMITATIONS

The development of novel radiotracers, such as prostate-specific membrane antigen or carbonic anhydrase IX, is being evaluated in both clinical practice and trial setting, aiming to change the management of these tumors. Molecular tools including circulating tumor cells and byproducts such as plasma and urine cell-free circulating tumor DNA provide the opportunity for MRD detection. MRD capture on single-cell or cellular byproducts can serve as a conduit for genomic and transcriptomic analyses, providing insight into the molecular underpinnings and clonal evolution of disease.

CONCLUSIONS AND CLINICAL IMPLICATIONS

While the full potential for MRD applications has yet to be realized, we are witnessing the emergence of novel techniques aimed at MRD detection and the rapid development of elegantly designed studies implementing iterative detection of MRD as means to provide biological rationale and tailor therapeutic options in GU tumors.

Utility of genomic testing in children, adolescents, and young adults with cancer

Genomic testing can inform the diagnosis and personalize management of cancers in children, adolescents, and young adults (CAYA). This scoping review explored the clinical utility and impact of genomic testing in general CAYA cancer cohorts. Relevant records published in English between 2017 and 2024 were identified by searching PubMed. 36 studies (32 original articles; 4 reviews) were identified on genomic testing in CAYA cancers, most of which were advanced cancers. Studies internationally reported that approximately 16%-18% of CAYAs with cancer carry an associated pathogenic germline variant where 40% are de novo, and can guide treatment (eg, DNA repair gene variants). Somatic variants, predominantly copy number or structural rearrangements, inform diagnosis in up to 95% of primary cancers. Between 18% and 69% of patients have a somatic variant with a matched therapy, but only one third receive the genomic-guided recommendation, predominantly due to declining patient condition. Few studies evaluated the impact of matched therapies on response and survival. Combining comprehensive DNA and RNA sequencing maximises sensitivity. Circulating tumour DNA was detected in most primary cancers and shows high concordance with tumour tissue. In conclusion, genomic testing of CAYA cancers is feasible, informs diagnoses and guides personalised care. Further research is needed on response to genomic-guided treatments.

Tetrahedral DNA nanostructures-assisted electrochemical assay for detecting circulating tumor DNA by combining a masking tactic with 3D-hybridization chain reactions

Circulating tumor DNA (ctDNA) is a remarkable noninvasive tumor marker that plays a crucial role in tumor diagnosis, prognosis and treatment. However, detecting low-abundance ctDNA from a substantial amount of nucleic acids originating from healthy cells is challenging. Herein, we proposed a tetrahedral DNA nanostructures (TDNs)-assisted electrochemical biosensor for ctDNA detection. This biosensor combines a masking tactic with 3D-hybridization chain reactions. Masking hairpins (MHs) were initially introduced to prevent interference from wild-type (WT) DNA. Then, the initiator sequence was transferred to the electrode surface modified with TDNs by the target ctDNA. The initiator sequence triggers the 3D self-assembly of hairpin strands, leading to the formation of DNA networks or even DNA hydrogels (long reaction time). This process generates numerous evenly distributed biotin molecules that can bind to streptavidin peroxidase to considerably amplify the signal. This method exhibits high sensitivity (the minimum concentration for detecting ctDNA is 1 aM, which corresponds to 60 ctDNA molecules in 100 μl sample) and excellent specificity (single mismatch). More importantly, this high-performance sensor can detect ctDNA with other mutation sites and their mixtures by modifying the corresponding capture probes on the TDNs. Furthermore, this ultrasensitive sensor effectively detects target ctDNA (0.001 %) at high levels of WT DNA and in complex matrices such as serum. These findings suggest that the sensor has promising potential as a noninvasive tool for early tumor diagnosis.

The Role of ctDNA for Diagnosis and Histological Prediction in Early Stage Non-Small-Cell Lung Cancer: A Narrative Review

Background: Circulating tumor DNA (ctDNA) may be released from neoplastic cells into biological fluids through apoptosis, necrosis, or active release. In patients with non-small-cell lung cancer (NSCLC), ctDNA analysis is being introduced in clinical practice only for advanced disease management. Nevertheless, an interesting and promising field of application is the analysis of ctDNA in the management of early stage non-small-cell lung cancer, both for evaluation before treatment, such as diagnosis and screening, and for prediction of histology or pathological features. Methods: A thorough review of the literature published between 2000 and 2024 was performed on PubMed, utilizing the advanced search feature to narrow down titles and abstracts containing the following keywords: ctDNA, early stage, and NSCLC. A total of 20 studies that met all inclusion criteria were chosen for this review. Results: In this review, we summarize the increasing evidence suggesting that ctDNA has potential clinical applications in the management of patients with early stage NSCLC. ctDNA levels in early stage cancers are very low, posing many technical challenges in improving the detection rate and sensitivity, especially in clinical practice, if it is to be implemented for early detection. Presently, the main limitation of ctDNA experimental and clinical studies, especially in early stage settings, is the lack of definitive standardization and consensus regarding methodology, the absence of systematically validated analyses, and the lack of adoption of sensitive approaches. Conclusions: Possible applications of this analyte open up new fields of diagnosis, treatment, and follow up, which are less invasive and more precise than other approaches currently in use, especially in early stage NSCLC patients.

Integrating Clinical Variables, Radiomics, and Tumor-derived Cell-Free DNA for Enhanced Prediction of Resectable Esophageal Adenocarcinoma Outcomes

PURPOSE

The value of integrating clinical variables, radiomics, and tumor-derived cell-free DNA (cfDNA) for the prediction of survival and response to chemoradiation of patients with resectable esophageal adenocarcinoma is not yet known. Our aim was to investigate if radiomics and cfDNA metrics combined with clinical variables can improve personalized predictions.

METHODS AND MATERIALS

A cohort of 111 patients with resectable esophageal adenocarcinoma from 2 centers treated with neoadjuvant chemoradiation therapy was used for exploratory retrospective analyses. Models combining the clinical variables of the SOURCE survival model with radiomic features and cfDNA were built using elastic net regression and internally validated using 5-fold cross-validation. Model performance for overall survival (OS) and time to progression (TTP) were evaluated with the C-index and the area under the curve for pathologic complete response.

RESULTS

The best-performing baseline models for OS and TTP were based on the combination of SOURCE-cfDNA that reached a C-index of 0.55 and 0.59 compared with 0.44 to 0.45 with SOURCE alone. The addition of restaging positron emission tomography radiomics to SOURCE was the most promising addition for predicting OS (C-index: 0.65) and TTP (C-index: 0.60). Baseline risk stratification was achieved for OS and TTP by combining SOURCE with radiomics or cfDNA, log-rank P < .01. The best-performing combination model for the prediction of pathologic complete response reached an area under the curve of 0.61 compared with 0.47 with SOURCE variables alone.

CONCLUSIONS

The addition of radiomics and cfDNA can improve the performance of an established survival model. External validity needs to be further assessed in future studies together with the optimization of radiomic pipelines.

Evaluation of an innovative multi-cancer early detection test: high sensitivity and specificity in differentiating cancer, inflammatory conditions, and healthy individuals

Background

Cancer is a leading cause of death worldwide, with early detection crucial for effective treatment. Traditional diagnostic methods, such as imaging and biopsies, are often limited by invasiveness, cost, and sensitivity. Blood-based multi-cancer early detection (MCED) tests offer a less invasive and potentially more comprehensive approach. Recently, a novel screening tool, the Carcimun® test was reported, detecting conformational changes in plasma proteins through optical extinction measurements. This study evaluates the Carcimun® test's performance, including participants with inflammatory conditions.

Methods

This prospective, single-blinded study included 172 participants: 80 healthy volunteers, 64 cancer patients (various types), and 28 individuals with inflammatory conditions (fibrosis, sarcoidosis, pneumonia) or benign tumors. Plasma samples were analyzed using the Carcimun® test. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated.

Results

Mean extinction values were significantly higher in cancer patients (315.1) compared to healthy individuals (23.9) and those with inflammatory conditions (62.7) (p<0.001). The Carcimun® test distinguished these groups with high accuracy (95.4%), sensitivity (90.6%), and specificity (98.2%). Significant differences were found between healthy participants and cancer patients (p<0.001), and between cancer patients and those with inflammation (p<0.001).

Conclusion

The Carcimun® test achieved high accuracy, sensitivity, and specificity, effectively identifying cancer patients while minimizing false positives and negatives. By including participants with inflammatory conditions, we addressed a significant limitation of previous studies, demonstrating the test's robustness in real-world clinical scenarios. These findings underscore the potential of the Carcimun® test as a valuable tool for early cancer detection and screening.

Serum Tumor Markers for Muscle-Invasive Bladder Cancer in Clinical Practice: A Narrative Review

In recent decades, serum tumor markers (STMs) have emerged as valuable adjuncts in early cancer detection and post-treatment surveillance. STMs are inexpensive, minimally invasive, and readily accessible tools that can be used to diagnose cancers, monitor patients' responses to treatment, and even detect recurrence without imposing additional burdens on patients. Emerging evidence has demonstrated the reliability of STMs in the prognostication of bladder cancer (BC). However, their potential role extends beyond prognostication. This review intends to provide a multidimensional picture of STM applications in muscle-invasive bladder cancer (MIBC). In addition, we supplement this review with real-life clinical experiences from our institution to further illustrate the clinical feasibility of STMs in MIBC.

Dual Biomarker Strategies for Liquid Biopsy: Integrating Circulating Tumor Cells and Circulating Tumor DNA for Enhanced Tumor Monitoring

The liquid biopsy has gained significant attention in cancer diagnostics, with circulating tumor cells (CTCs) and circulating tumor DNA (ctDNA) being recognized as key biomarkers for tumor detection and monitoring. However, each biomarker possesses inherent limitations that restrict its standalone clinical utility, such as the rarity and heterogeneity of CTCs and the variable sensitivity and specificity of ctDNA assays. This highlights the necessity of integrating both biomarkers to maximize diagnostic and prognostic potential, offering a more comprehensive understanding of the tumor biology and therapeutic response. In this review, we summarize clinical studies that have explored the combined analysis of CTCs and ctDNA as biomarkers, providing insights into their synergistic value in diverse tumor types. Specifically, this paper examines the individual advantages and limitations of CTCs and ctDNA, details the findings of combined biomarker studies across various cancers, highlights the benefits of dual biomarker approaches over single-biomarker strategies, and discusses future prospects for advancing personalized oncology through liquid biopsies. By offering a comprehensive overview of clinical studies combining CTCs and ctDNA, this review serves as a guideline for researchers and clinicians aiming to enhance biomarker-based strategies in oncology and informs biosensor design for improved biomarker detection.

The prognostic value of circulating tumor DNA in malignant melanoma patients treated with immune checkpoint inhibitors: a systematic review and meta-analysis

Background

Circulating tumor DNA (ctDNA) is an emerging biomarker in malignant melanoma(MM), and high levels of ctDNA may reflect a higher tumor load. However, its prognostic value for MM receiving immune checkpoint inhibitors(ICI) remains controversial. This meta-analysis aimed to elucidate the prognostic significance of ctDNA in this patient population.

Methods

We conducted a comprehensive search of the PubMed, Cochrane Library, CNKI, and EMBASE databases, including studies published up to August 15, 2024, to investigate the prognostic impact of ctDNA in MM patients treated with ICI. Using a fixed-effects model, we systematically evaluated the association between ctDNA levels and key survival outcomes, including overall survival (OS) and progression-free survival (PFS). Additionally, funnel plots, Begg's test, and Egger's test were employed to assess potential publication bias.

Results

Twelve studies from eleven articles, involving a total of 1063 eligible MM patients receiving ICI therapy, were included. The results indicated that patients with detectable ctDNA before initiating ICI therapy had significantly poorer OS (HR = 3.19, 95% CI = 2.22-4.58, P < 0.001) and PFS (HR = 2.08, 95% CI = 1.61-2.69, P < 0.001). Furthermore, the detectability of ctDNA during treatment was also significantly associated with worse OS (HR = 4.57, 95% CI = 3.03-6.91, P < 0.001) and PFS (HR = 3.79, 95% CI = 2.13-6.75, P < 0.001).

Conclusions

This meta-analysis indicates that in MM patients receiving ICI therapy, detectable and high levels of ctDNA are significantly associated with poorer OS and PFS. Therefore, ctDNA can serve as a diagnostic and stratification tool prior to treatment, as well as an effective indicator for monitoring treatment response and disease progression.

Systematic Review Registration

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Circulating Extracellular Vesicles as Promising Biomarkers for Precession Diagnostics: A Perspective on Lung Cancer

Extracellular vesicles (EVs) have emerged as promising biomarkers in liquid biopsy, owing to their ubiquitous presence in bodily fluids and their ability to carry disease-related cargo. Recognizing their significance in disease diagnosis and treatment, substantial efforts have been dedicated to developing efficient methods for EV isolation, detection, and analysis. EVs, heterogeneous membrane-encapsulated vesicles secreted by all cells, contain bioactive substances capable of modulating recipient cell biology upon internalization, including proteins, lipids, DNA, and various RNAs. Their prevalence across bodily fluids has positioned them as pivotal mediators in physiological and pathological processes, notably in cancer, where they hold potential as straightforward tumor biomarkers. This review offers a comprehensive examination of advanced nanotechnology-based techniques for detecting lung cancer through EV analysis. It begins by providing a brief overview of exosomes and their role in lung cancer progression. Furthermore, this review explores the evolving landscape of EV isolation and cargo analysis, highlighting the importance of characterizing specific biomolecular signatures within EVs for improved diagnostic accuracy in lung cancer patients. Innovative strategies for enhancing the sensitivity and specificity of EV isolation and detection, including the integration of microfluidic platforms and multiplexed biosensing technologies are summarized. The discussion then extends to key challenges associated with EV-based liquid biopsies, such as the standardization of isolation and detection protocols and the establishment of robust analytical platforms for clinical translation. This review highlights the transformative impact of EV-based liquid biopsy in lung cancer diagnosis, heralding a new era of personalized medicine and improved patient care.

Advancements in pathology: Digital transformation, precision medicine, and beyond

Pathology, a cornerstone of medical diagnostics and research, is undergoing a revolutionary transformation fueled by digital technology, molecular biology advancements, and big data analytics. Digital pathology converts conventional glass slides into high-resolution digital images, enhancing collaboration and efficiency among pathologists worldwide. Integrating artificial intelligence (AI) and machine learning (ML) algorithms with digital pathology improves diagnostic accuracy, particularly in complex diseases like cancer. Molecular pathology, facilitated by next-generation sequencing (NGS), provides comprehensive genomic, transcriptomic, and proteomic insights into disease mechanisms, guiding personalized therapies. Immunohistochemistry (IHC) plays a pivotal role in biomarker discovery, refining disease classification and prognostication. Precision medicine integrates pathology's molecular findings with individual genetic, environmental, and lifestyle factors to customize treatment strategies, optimizing patient outcomes. Telepathology extends diagnostic services to underserved areas through remote digital pathology. Pathomics leverages big data analytics to extract meaningful insights from pathology images, advancing our understanding of disease pathology and therapeutic targets. Virtual autopsies employ non-invasive imaging technologies to revolutionize forensic pathology. These innovations promise earlier diagnoses, tailored treatments, and enhanced patient care. Collaboration across disciplines is essential to fully realize the transformative potential of these advancements in medical practice and research.

Integration of circulating tumor DNA in biliary tract cancer: the emerging landscape

Precision medicine has emerged as a cornerstone in cancer treatment revolutionizing our approach across malignancies. Molecular profiling of biliary tract cancers (BTCs) has changed the treatment landscape positively by prolonging survival in an aggressively fatal malignancy in its advanced stages. The acquisition of tissue tumor DNA for genomic analysis in BTC is often anatomically challenging, limited by quantity and quality. In response, ctDNA has emerged as a noninvasive means of molecular profiling. The utility of both plasma and bile ctDNA has been explored in several studies demonstrating the high mutation detection rates and the ability to isolate targetable mutations when present. In addition, the concordance between plasma and tissue DNA provides validity in utilizing ctDNA results to infer treatment decisions. Analysis of ctDNA in BTC has also provided prognostic information and facilitated evaluation of clonal evolution with ease of serial measurements. Insight into novel mechanisms of resistance to targeted therapies are being uncovered in ctDNA. As research endeavors continue to deepen our understanding in the field particularly in the space of ctDNA surveillance after curative intent, the tremendous progress made so far has enabled integration of ctDNA into the clinical practice of BTCs.

Potential role of circulating tumor cells and cell-free DNA as biomarkers in oral squamous cell carcinoma: A prospective single-center study

Metastasis in patients with oral squamous cell carcinoma has been associated with a poor prognosis. However, sensitive and reliable tests for monitoring their occurrence are unavailable, with the exception of PET-CT. Circulating tumor cells and cell-free DNA have emerged as promising biomarkers for determining treatment efficacy and as prognostic predictors in solid tumors such as breast cancer and colorectal cancer. Hence, this study aimed to determine the potential role of liquid biopsy, circulating tumor cells, and cell-free DNA as biomarkers of oral squamous cell carcinoma. Thirteen patients with primary oral squamous cell carcinoma who visited our hospital between 2022 and 2023 were recruited, and plasma samples were collected from each patient preoperatively and postoperatively. We examined the relationship between the prognosis, the number of circulating tumor cells per four milliliters of peripheral blood, and the amount of cell-free DNA per milliliter of serum or the gene mutation in cell-free DNA. We observed no correlation between the number of preoperative circulating tumor cells and metastatic events. However, the number of circulating tumor cell clusters or the amount of preoperative cell-free DNA in metastatic cases was higher than that in non-metastatic cases. In oral squamous cell carcinoma, circulating tumor cell clusters or cell-free DNA levels may help inform management decisions regarding metastasis. However, further studies are required to provide a possible window for therapeutic interventions.

Cell-Free Carbonic Anhydrase IX mRNA in Urine as Biomarker for Urogenital Cancers: The Relationship Between Urinary Extracellular RNA and Tumor-Cell-Associated RNA

Circulating tumor cells and cell-free nucleic acids are novel diagnostic, prognostic and predictive tools for non-invasive and cost-effective cancer detection in liquid biopsy. Carbonic anhydrase IX (CAIX) has been proposed as a biomarker in urogenital tumors and urine sediment. Our aim was to evaluate CAIX full-length percentage (CAIX FL%) in urine-cell-free RNA (cfRNA) and its relationship with tumor-cell-associated RNA (TC-RNA). CAIX FL% was quantified by reverse transcription quantitative polymerase chain reaction (RT-qPCR) in patients with prostate, kidney or bladder carcinoma. When cfRNA and TC-RNA were analyzed, CAIX FL% was significantly higher in urine samples from cancer patients than from controls. Using a 10% cutoff for CAIX FL%, specificity, sensitivity, positive and negative predictive values, as well as accuracy for TC-RNA were higher than for cfRNA in all urogenital cancers, but varied according to tumor type. CAIX FL% distribution in TC-RNA differed significantly (p < 0.001) between control and tumor samples (37.5% and 96.2%, respectively); similar results were obtained for each tumor type. Additionally, the 10% cutoff showed a 77.9% concordance between TC-RNA and cfRNA. In conclusion, urine is proposed as an alternative biofluid for investigating CAIX FL% in urogenital cancers, and this parameter can be reliably measured as cfRNA and TC-RNA with different predictive capabilities depending on tumor type.

Colocalization of Cancer-Associated Biomarkers on Single Extracellular Vesicles for Early Detection of Cancer

Detection of cancer early, when it is most treatable, remains a significant challenge because of the lack of diagnostic methods sufficiently sensitive to detect nascent tumors. Early-stage tumors are small relative to their tissue of origin, heterogeneous, and infrequently manifest in clinical symptoms. The detection of early-stage tumors is challenging given the lack of tumor-specific indicators (ie, protein biomarkers, circulating tumor DNA) to enable detection using a noninvasive diagnostic assay. To overcome these obstacles, we have developed a liquid biopsy assay that interrogates circulating extracellular vesicles (EVs) to detect tumor-specific biomarkers colocalized on the surface of individual EVs. We demonstrate the technical feasibility of this approach in human cancer cell line-derived EVs, where we show strong correlations between assay signal and cell line gene/protein expression for the ovarian cancer-associated biomarkers bone marrow stromal antigen-2, folate receptor-α, and mucin-1. Furthermore, we demonstrate that detecting distinct colocalized biomarkers on the surface of EVs significantly improves discrimination performance relative to single biomarker measurements. Using this approach, we observe promising discrimination of high-grade serous ovarian cancer versus benign ovarian masses and healthy women in a proof-of-concept clinical study.

ctDNA in the reading room: A guide for radiologists

Liquid biopsy with sequencing of circulating tumor DNA (ctDNA) is a minimally invasive method for sampling body fluids and offers a promising alternative to tissue biopsies that involve greater risks, costs, and time. ctDNA not only identifies actionable targets by revealing unique molecular signatures in cancer, but also may assess treatment response, treatment resistance and progression, and recurrence. Imaging correlates of these applications are already being identified and utilized for various solid tumors. Radiologists have new challenges in interpreting oncologic imaging. Given their integral role in cancer surveillance, they must become familiar with the importance of ctDNA in detecting recurrence and minimal residual disease, measuring treatment response, predicting survival and metastatic patterns, and identifying new molecular therapeutic targets. In this review, we provide an overview of ctDNA testing, and a snapshot of current clinical guidelines from the National Comprehensive Cancer Network and the European Society of Molecular Oncology on the use of ctDNA in lung, breast, colorectal, pancreatic, and hepatobiliary cancers. For each cancer type, we also highlight current research applications of ctDNA that are relevant to the field of diagnostic radiology.

Performance evaluation of a CRISPR Cas9-based selective exponential amplification assay for the detection of KRAS mutations in plasma of patients with advanced pancreatic cancer

AIMS

Pancreatic ductal adenocarcinoma (PDAC) is highly malignant, with shockingly mortality rates. KRAS oncoprotein is the main molecular target for PDAC. Liquid biopsies, such as the detection of circulating tumour DNA (ctDNA), offer a promising approach for less invasive diagnosis. In this study, we aim to evaluate the precision and utility of programmable enzyme-based selective exponential amplification (PASEA) assay for rare mutant alleles identification.

METHODS

PASEA uses CRISPR-Cas9 to continuously shear wild-type alleles during recombinase polymerase amplification, while mutant alleles are exponentially amplified, ultimately reaching a level detectable by Sanger sequencing. We applied PASEA to detect KRAS mutations in plasma ctDNA. A total of 153 patients with stage IV PDAC were enrolled. We investigated the relationship between ctDNA detection rates with various clinical factors.

RESULTS

Our results showed 91.43% vs 44.83% detection rate in patients of prechemotherapy and undergoing chemotherapy. KRAS ctDNA was more prevalent in patients with liver metastases and patients did not undergo surgical resection. Patients with liver metastases prior to chemotherapy showed a sensitivity of 95.24% (20/21) with PASEA. Through longitudinal monitoring, we found ctDNA may be a more accurate biomarker for monitoring chemotherapy efficacy in PDAC than CA19-9.

CONCLUSIONS

Our study sheds light on the potential of ctDNA as a valuable complementary biomarker for precision targeted therapy, emphasising the importance of considering chemotherapy status, metastatic sites and surgical history when evaluating its diagnostic potential in PDAC. PASEA technology provides a reliable, cost-effective and minimally invasive method for detecting ctDNA of PDAC.

Clinical applications of circulating tumor DNA in hematological malignancies: From past to the future

Liquid biopsy, particularly circulating tumor DNA (ctDNA), has drawn a lot of attention as a non- or minimal-invasive detection approach for clinical applications in patients with cancer. Many hematological malignancies are well suited for serial and repeated ctDNA surveillance due to relatively high ctDNA concentrations and high loads of tumor-specific genetic and epigenetic abnormalities. Progress of detecting technology in recent years has improved sensitivity and specificity significantly, thus broadening and strengthening the potential utilities of ctDNA including early diagnosis, prognosis estimation, treatment response evaluation, minimal residual disease monitoring, targeted therapy selection, and immunotherapy surveillance. This manuscript reviews the detection methodologies, clinical application and future challenges of ctDNA in hematological malignancies, especially for lymphomas, myeloma and leukemias.

Addressing heterogeneous sensitivity in biomarker screening with application in NanoString nCounter data

Biomarkers are measurable indicators of biological processes and have wide biomedical applications including disease screening and prognosis prediction. Candidate biomarkers can be screened in high-throughput settings, which allow simultaneous measurements of a large number of molecules. For binary biomarkers, the ability to detect a molecule may be hindered by the presence of background noise and the variable signal strength, which lower the sensitivity to a different extent for different target molecules in a sample-specific manner. This heterogeneity in detection sensitivity is often overlooked and leads to an inflated false positive rate. We propose a novel sensitivity adjusted likelihood-ratio test (SALT), which properly controls the false positives and is more powerful than the unadjusted approach. We show that sample-and-feature-specific detection sensitivity can be well estimated from NanoString nCounter data, and using the estimated sensitivity in SALT results in improved biomarker screening.

The ctDNA revolution: Insights on cancer care: A narrative review

Circulating tumor DNA (ctDNA) is a revolutionary tool in the detection and monitoring of cancer: a minimally invasive, highly sensitive approach to analysing tumor-specific DNA in the bloodstream. Therefore, it is of interest to explore the current and evolving landscape of cancer genomics as precision tools in quantifying tumor dynamics. Thus, the role of ctDNA in tracking minimum residual disease, relapse, recurrence and the tailoring of therapeutic strategies for effective management of tumours is reviewed.

Circulating tumor DNA: current implementation issues and future challenges for clinical utility

Over the past decades, liquid biopsy, especially circulating tumor DNA (ctDNA), has received tremendous attention as a noninvasive detection approach for clinical applications, including early diagnosis of cancer and relapse, real-time therapeutic efficacy monitoring, potential target selection and investigation of drug resistance mechanisms. In recent years, the application of next-generation sequencing technology combined with AI technology has significantly improved the accuracy and sensitivity of liquid biopsy, enhancing its potential in solid tumors. However, the increasing integration of such promising tests to improve therapy decision making by oncologists still has complexities and challenges. Here, we propose a conceptual framework of ctDNA technologies and clinical utilities based on bibliometrics and highlight current challenges and future directions, especially in clinical applications such as early detection, minimal residual disease detection, targeted therapy, and immunotherapy. We also discuss the necessities of developing a dynamic field of translational cancer research and rigorous clinical studies that may support therapeutic strategy decision making in the near future.

Plasma cell-free DNA as predictor of disease status in patients with differentiated thyroid cancer - a prospective study from a tertiary care institution

Introduction

Plasma cell-free DNA (cfDNA) estimation offers a non-invasive method to potentially diagnose, monitor, and prognosticate patients with malignancy. This prospective study aimed to assess plasma cfDNA levels in patients with differentiated thyroid cancer (DTC) to determine its role in predicting disease status in the post-operative setting.

Materials and methods

This was a single-center prospective observational study conducted at a public medical research university and hospital in New Delhi, India. 254 patients with DTC in the post-operative setting were included: 95 in Group 1 (active structural disease) and 159 in Group 2 (disease-free). Blood samples were collected for plasma separation and cfDNA extraction. The cfDNA concentrations were quantified and compared across various disease states.

Results

Median values of plasma cfDNA (ng/µL) in groups 1 and 2 were found to be 0.272 (IQR: 0.137-0.442) and 0.222 (IQR: 0.123-0.398), respectively with no significant difference (p=0.122). cfDNA levels were significantly higher in patients in the age group ≥55 years (p=0.016). However, the cfDNA levels were not significantly associated with any of the other known prognostic markers of DTC.

Discussion

Based on the results of this study, plasma cfDNA levels did not significantly predict disease status in patients with DTC in the post-operative setting.

Integrating machine learning and bioinformatics approaches for identifying novel diagnostic gene biomarkers in colorectal cancer

This study aimed to identify diagnostic gene biomarkers for colorectal cancer (CRC) by analyzing differentially expressed genes (DEGs) in tumor and adjacent normal samples across five colon cancer gene-expression profiles (GSE10950, GSE25070, GSE41328, GSE74602, GSE142279) from the Gene Expression Omnibus (GEO) database. Intersecting identified DEGs with the module with the highest correlation to gene expression patterns of tumor samples in the gene co-expression network analysis revealed 283 overlapped genes. Centrality measures were calculated for these genes in the reconstructed STRING protein-protein interaction network. Applying LASSO logistic regression, eleven genes were ultimately recognized as candidate diagnostic genes. Among these genes, the area under the receiver operating characteristic curve (AUROC) values for nine genes (CDC25B, CDK4, IQGAP3, MMP1, MMP7, SLC7A5, TEAD4, TRIB3, and UHRF1) surpassed the threshold of 0.92 in both the training and validation sets. We evaluated the diagnostic performance of these genes with four machine learning algorithms: random forest (RF), support vector machines (SVM), artificial neural network (ANN), and gradient boosting machine (GBM). In the testing dataset (GSE21815 and GSE106582), the AUROC scores were greater than 0.95 for all of the machine learning algorithms, indicating the high diagnostic performance of the nine genes. Besides, these nine genes are also significantly correlated to twelve immune cells, namely Mast cells activated, Macrophages M0, M1, and M2, Neutrophils, T cells CD4 memory activated, T cells follicular helper, T cells CD8, T cells CD4 memory resting, B cells memory, Plasma cells, and Mast cells resting (P < 0.05). These results strongly suggest that all of the nine genes have the potential to serve as reliable diagnostic biomarkers for CRC.

Extracellular vesicle-derived biomarkers in prostate cancer care: Opportunities and challenges

Prostate cancer (PCa) is the second most prevalent cancer in men worldwide, presenting a significant global public health challenge that necessitates early detection and personalized treatment. Recently, non-invasive liquid biopsy methods have emerged as promising tools to provide insights into the genetic landscape of PCa and monitor disease progression, aiding decision-making at all stages. Research efforts have concentrated on identifying liquid biopsy biomarkers to improve PCa diagnosis, prognosis, and treatment prediction. This article reviews recent research advances over the last five years utilizing extracellular vesicles (EVs) as a natural biomarker library for PCa, and discusses the clinical translation of EV biomarkers, including ongoing trials and key implementation challenges. The findings underscore the transformative role of liquid biopsy, particularly EV-based biomarkers, in revolutionizing PCa diagnosis, prediction, and treatment.

Genomic Landscape of Advanced Solid Tumors in Middle East and North Africa Using Circulating Tumor DNA in Routine Clinical Practice

INTRODUCTION

Next-generation sequencing (NGS) of tumor DNA can detect actionable drivers and help guide therapy for patients with advanced-stage cancers. While tissue-based genotyping is considered a standard of care, blood-based genotyping is emerging as a valid alternative. Tumor genomic profiles may vary by region, and data from the Middle East and North Africa (MENA) are not widely available. This study elucidates the genomic landscape of advanced solid cancers in patients from the MENA region by retrospectively analyzing results from NGS circulating tumor DNA (ctDNA) testing.

METHODS

In routine clinical practice, 926 plasma samples from 767 patients with advanced cancers from the MENA region were profiled using a comprehensive NGS assay (Guardant360®). We conducted a pan-cancer analysis and sub-analyses focusing on lung, breast, and colorectal cancers.

RESULTS

In the pan-cancer group, TP53 (58.5%), EGFR (20.4%), and KRAS (18.9%) were the most frequently mutated genes. EGFR (10.2%), FGFR1 (4.9%), and PIK3CA (4.9%) showed the most amplifications, while fusions were observed in 2.7% of patients, including ALK, FGFR2, and RET. For lung adenocarcinoma, EGFR (30.5%), KRAS (19.3%), and ERBB2 (4.6%) were the most frequently identified alterations among the genes recommended for evaluation by the National Comprehensive Cancer Network (NCCN). In patients with breast cancer, PIK3CA (35.3%), ESR1 (21.7%), and BRCA1/2 (13.3%) had the most prevalent alterations among NCCN-recommended genes. In colorectal cancer, KRAS (39.0%), NRAS (8.0%), and BRAF (V600E, 4.0%) were the most observed mutations among genes recommended by the NCCN. Comparing this cohort to publicly available Western and Eastern datasets also indicated similarities (including PIK3CA in breast cancer) and variances (including EGFR in lung adenocarcinoma) in key genes of interest in the analyzed cancer types.

CONCLUSION

Overall, our findings provide insight into the genomic landscape of individuals with advanced solid organ malignancies from the MENA region and support the role of ctDNA in guiding therapeutic decisions.

Pre-metastatic niche: formation, characteristics and therapeutic implication

Distant metastasis is a primary cause of mortality and contributes to poor surgical outcomes in cancer patients. Before the development of organ-specific metastasis, the formation of a pre-metastatic niche is pivotal in promoting the spread of cancer cells. This review delves into the intricate landscape of the pre-metastatic niche, focusing on the roles of tumor-derived secreted factors, extracellular vesicles, and circulating tumor cells in shaping the metastatic niche. The discussion encompasses cellular elements such as macrophages, neutrophils, bone marrow-derived suppressive cells, and T/B cells, in addition to molecular factors like secreted substances from tumors and extracellular vesicles, within the framework of pre-metastatic niche formation. Insights into the temporal mechanisms of pre-metastatic niche formation such as epithelial-mesenchymal transition, immunosuppression, extracellular matrix remodeling, metabolic reprogramming, vascular permeability and angiogenesis are provided. Furthermore, the landscape of pre-metastatic niche in different metastatic organs like lymph nodes, lungs, liver, brain, and bones is elucidated. Therapeutic approaches targeting the cellular and molecular components of pre-metastatic niche, as well as interventions targeting signaling pathways such as the TGF-β, VEGF, and MET pathways, are highlighted. This review aims to enhance our understanding of pre-metastatic niche dynamics and provide insights for developing effective therapeutic strategies to combat tumor metastasis.

Clinical Validity and Utility of Circulating Tumor DNA (ctDNA) Testing in Advanced Non-small Cell Lung Cancer (aNSCLC): A Systematic Literature Review and Meta-analysis

PURPOSE

Circulating tumor DNA (ctDNA) testing has become a promising tool to guide first-line (1L) targeted treatment for advanced non-small cell lung cancer (aNSCLC). This study aims to estimate the clinical validity (CV) and clinical utility (CU) of ctDNA-based next-generation sequencing (NGS) for oncogenic driver mutations to inform 1L treatment decisions in aNSCLC through a systematic literature review and meta-analysis.

METHODS

A systematic literature search was conducted in PubMed/MEDLINE and Embase to identify randomized control trials or observational studies reporting CV/CU on ctDNA testing in patients with aNSCLC. Meta-analyses were performed using bivariate random-effects models to estimate pooled sensitivity and specificity. Progression-free/overall survival (PFS/OS) was summarized for CU studies.

RESULTS

A total of 20 studies were identified: 17 CV only, 2 CU only, and 1 both, and 13 studies were included for the meta-analysis on multi-gene detection. The overall sensitivity and specificity for ctDNA detection of any mutation were 0.69 (95% CI 0.63-0.74) and 0.99 (95% CI 0.97-1.00), respectively. However, sensitivity varied greatly by driver gene, ranging from 0.29 (95% CI 0.13-0.53) for ROS1 to 0.77 (95% CI 0.63-0.86) for KRAS. Two studies that compared PFS with ctDNA versus tissue-based testing followed by 1L targeted therapy found no significant differences. One study reported OS curves on ctDNA-matched and tissue-matched therapies but no hazard ratios were provided.

CONCLUSIONS

ctDNA testing demonstrated an overall acceptable diagnostic accuracy in patients with aNSCLC, however, sensitivity varied greatly by driver mutation. Further research is needed, especially for uncommon driver mutations, to better understand the CU of ctDNA testing in guiding targeted treatments for aNSCLC.

Predictive value of primary tumor volume change during concurrent chemoradiotherapy in patients with unresectable stage III non-small cell lung cancer

BACKGROUND AND PURPOSE

No established early biomarkers currently exist to predict responses during concurrent chemoradiotherapy (CCRT) in patients with unresectable non-small cell lung cancer (NSCLC). This study investigated the potential of gross tumor volume (GTV) and its changes during CCRT as predictors of survival outcomes.

MATERIALS AND METHODS

We identified 227 patients with unresectable stage III NSCLC who underwent definitive CCRT followed by durvalumab between November 2018 and December 2022. GTV was defined as the volume of the primary tumor, assessed at two time points: before starting CCRT for initial planning (GTV1), and at the fourth week of CCRT for adaptive planning (GTV2). Both relative and absolute regressions between GTV1 and GTV2 were calculated.

RESULTS

The median GTV1 volume was 90 mL (range, 5-840 mL), and the median GTV2 volume was 64 mL (range, 1-520 mL), resulting in median absolute and relative regressions of 18.6 mL and 25.0 %, respectively. Among the GTV parameters, relative GTV regression exhibited the strongest predictive value, with an area under the curve (AUC) of 0.804 for in-field progression and 0.711 for overall progression. The 1-year progression-free survival rates for the high (>30 %), intermediate (0-30 %), and low (≤0%) relative regression groups were 88.0 %, 62.6 %, and 14.3 %, respectively (p = 0.006 for high vs. intermediate; p < 0.001 for intermediate vs. low). Additionally, GTV2 volume demonstrated stronger associations with survival outcomes than GTV1 volume.

CONCLUSION

Relative GTV regression was identified as a promising early predictor for patients with unresectable stage III NSCLC. Further development of a multi-parametric predictive model is warranted to guide patient-tailored therapeutic approaches.

Circulating tumor cells in pancreatic cancer: The prognostic impact in surgical patients

Pancreatic cancer is associated with a poor prognosis, even in the early stages, mainly due to metastatic progression. New diagnostic techniques that predict unfavorable outcomes are needed in order to improve treatment strategies. Circulating tumor cells (CTCs) are showing promising results as a predictive biomarker for various tumors. In this editorial we comment on the article by Zhang et al, who published the first systematic review and meta-analysis evaluating the prognostic value of CTCs as biomarkers in early-stage pancreatic cancer patients undergoing surgery. CTCs were detected in peripheral or central venous system blood, before or during surgery. Positive CTCs showed a correlation with decreased overall survival and decreased relapse-free, disease-free and progression-free survival in this meta-analysis. However, the heterogeneity was significant. The authors suggest that this result was related to the separation methods used between studies, but other differences such as the margin status or the neoadjuvant and adjuvant treatments used are also important to consider. CTCs may be a potential prognostic biomarker in pancreatic cancer patients, but it is necessary to compare and standardize the platforms used to isolate CTCs, to compare different biomarkers from liquid biopsy and to determine the impact on prognosis when therapeutic changes are made based on CTCs levels.

Exploratory Analyses of Circulating Neoplastic-Immune Hybrid Cells as Prognostic Biomarkers in Advanced Intrahepatic Cholangiocarcinoma

Existing clinical biomarkers do not reliably predict treatment response or disease progression in patients with advanced intrahepatic cholangiocarcinoma (ICC). Circulating neoplastic-immune hybrid cells (CHCs) have great promise as a blood-based biomarker for patients with advanced ICC. Peripheral blood specimens were longitudinally collected from patients with advanced ICC enrolled in the HELIX-1 phase II clinical trial (NCT04251715). CHCs were identified by co-expression of pan-cytokeratin (CK) and CD45, and levels were correlated to patient clinical disease course. Unsupervised machine learning was then performed to extract their morphological features to compare them across disease courses. Five patients were included in this study, with a median of nine specimens collected per patient. A median of 13.5 CHCs per 50,000 peripheral blood mononuclear cells were identified at baseline, and levels decreased to zero following the initiation of treatment in all patients. Counts remained undetectable in three patients who demonstrated end-of-trial clinical treatment response and conversely increased in two patients with evidence of therapeutic resistance. In the post-trial surveillance period, interval counts increased prior to or at the time of clinical progression in three patients and remain undetectable in one patient with continued long-term disease stability. Using our machine learning platform, treatment-resistant CHCs exhibited upregulation of CK and downregulation of CD45 relative to treatment-responsive CHCs. CHCs represent a promising blood-based biomarker to supplement traditional radiographic and biochemical measures.

From haystack to high precision: advanced sequencing methods to unraveling circulating tumor DNA mutations

Identifying mutations in cancer-associated genes to guide patient treatments is essential for precision medicine. Circulating tumor DNA (ctDNA) offers valuable insights for early cancer detection, treatment assessment, and surveillance. However, a key issue in ctDNA analysis from the bloodstream is the choice of a technique with adequate sensitivity to identify low frequent molecular changes. Next-generation sequencing (NGS) technology, evolving from parallel to long-read capabilities, enhances ctDNA mutation analysis. In the present review, we describe different NGS approaches for identifying ctDNA mutation, discussing challenges to standardized methodologies, cost, specificity, clinical context, and bioinformatics expertise for optimal NGS application.

Circulating tumor DNA mutation analysis: advances in its application for early diagnosis of hepatocellular carcinoma and therapeutic efficacy monitoring

In recent years, the detection and analysis of circulating tumor DNA (ctDNA) have emerged as a new focus in the field of cancer research, particularly in the early diagnosis of hepatocellular carcinoma (HCC) and monitoring of therapeutic efficacy. ctDNA, which refers to cell-free DNA fragments released into the bloodstream from tumor cells upon cell death or shedding, carries tumor-specific genetic and epigenetic alterations, thereby providing a non-invasive approach for cancer diagnosis and prognosis. The concentration of ctDNA in the blood is higher compared to that in healthy individuals or other liquid biopsies from early-stage cancers, which is closely associated with the early diagnosis and comprehensive sequencing studies of HCC. Recent studies have indicated that sequential ctDNA analysis in patients receiving primary or adjuvant therapy for HCC can detect treatment resistance and recurrence before visible morphological changes in the tumor, making it a valuable basis for rapid adjustment of treatment strategies. However, this technology is continuously being optimized and improved. Challenges such as enhancing the accuracy of ctDNA sequencing tests, reducing the burden of high-throughput sequencing on a large number of samples, and controlling variables in the assessment of the relationship between ctDNA concentration and tumor burden, need to be addressed. Overall, despite the existing challenges, the examination and analysis of ctDNA have opened up new avenues for early diagnosis and therapeutic efficacy monitoring in hepatocellular carcinoma, expanding the horizons of this field.

Detection of the JAK2 V617F Mutation in Urinary Cell-free DNA in Patients with Myeloproliferative Neoplasms

Objective Testing for the Janus activating kinase 2 (JAK2) V617F mutation is important for diagnosing and treating myeloproliferative neoplasms (MPNs). Recently, urine cell-free DNA (ucfDNA) was reported to be useful for detecting tumor-specific gene mutations in several solid tumors. However, its utility in detecting such mutations in hematological malignancies has not yet been assessed. In this study, we assessed whether or not the JAK2 V617F mutation could be detected in ucfDNA and whether or not its positivity rate in ucfDNA was associated with the JAK2 V617F allele ratio of peripheral blood cells in patients with MPN. Methods The JAK2 V617F allele ratio of genomic DNA from peripheral blood cells was determined using quantitative polymerase chain reaction (qPCR) or droplet digital PCR (ddPCR). ucfDNA was subjected to ddPCR. The correlation between the JAK2 V617F mutation positivity rates of blood-derived DNA and those of ucfDNA was assessed. Materials Twelve patients with polycythemia vera and 12 patients with essential thrombocythemia were enrolled. Ethylenediaminetetraacetic acid-treated peripheral blood (100 mL) and 15-30 mL of fresh urine were used. Results The JAK2 V617F mutation was detected in the ucfDNA from all 20 JAK2 V617F mutation-positive patients. In addition, the JAK2 V617F mutation positivity rate of ucfDNA was correlated with the JAK2 V617F allele ratio of blood-derived DNA, including in both estimated glomerular filtration rate (eGFR) groups (patients with an eGFR ≥50 or <50 mL/min/1.73 m2). Conclusion Our results indicate that ucfDNA is a valuable tool for diagnosing and monitoring MPN. Given these findings, other disease-specific gene mutations in hematological malignancies may also be detectable in ucfDNA.

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

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

Methylated circulating tumor DNA in hepatocellular carcinoma: A comprehensive analysis of biomarker potential and clinical implications

The intricate epigenetic landscape of hepatocellular carcinoma (HCC) is profoundly influenced by alterations in DNA methylation patterns. Understanding these alterations is crucial for unraveling the molecular mechanisms underlying HCC pathogenesis. Methylated circulating tumor DNA (ctDNA) presents itself as an encouraging avenue for biomarker discovery and holds substantial clinical implications in HCC management. This review comprehensively outlines the studies concerning DNA methylation in HCC and underscores the significance of methylated ctDNA within this context. Moreover, a variety of cfDNA methylation-based methodologies, such as 5hmC profiling, bisulfite-based, restriction enzyme-dependent, and enrichment-based methods, provide in-depth insights into the molecular pathology of HCC. Additionally, the integration of methylated ctDNA analysis into clinical practice represents a significant advancement in personalized HCC management. By facilitating cancer screening, prognosis assessment, and treatment response prediction, the utilization of methylated ctDNA signifies a pivotal stride toward enhancing patient care and outcomes in HCC.

Application of machine learning for high-throughput tumor marker screening

High-throughput sequencing and multiomics technologies have allowed increasing numbers of biomarkers to be mined and used for disease diagnosis, risk stratification, efficacy assessment, and prognosis prediction. However, the large number and complexity of tumor markers make screening them a substantial challenge. Machine learning (ML) offers new and effective ways to solve the screening problem. ML goes beyond mere data processing and is instrumental in recognizing intricate patterns within data. ML also has a crucial role in modeling dynamic changes associated with diseases. Used together, ML techniques have been included in automatic pipelines for tumor marker screening, thereby enhancing the efficiency and accuracy of the screening process. In this review, we discuss the general processes and common ML algorithms, and highlight recent applications of ML in tumor marker screening of genomic, transcriptomic, proteomic, and metabolomic data of patients with various types of cancers. Finally, the challenges and future prospects of the application of ML in tumor therapy are discussed.

Monitoring advanced gastrointestinal stromal tumor with circulating tumor DNA

PURPOSE OF REVIEW

This review explores the role of circulating tumor (ct)DNA as a biomarker for clinical decision-making and monitoring purposes in metastatic gastrointestinal stromal tumor (GIST) patients. We discuss key insights from recent clinical trials and anticipate the future perspectives of ctDNA profiling within the clinical landscape of GIST.

RECENT FINDINGS

The identification and molecular characterization of KIT/platelet-derived growth factor receptor alpha (PDGFRA) mutations from ctDNA in metastatic GIST is feasible and reliable. Such identification through ctDNA serves as a predictor of clinical outcomes to tyrosine-kinase inhibitors (TKIs) in metastatic patients. Additionally, conjoined ctDNA analysis from clinical trials reveal the evolving mutational landscapes and increase in intratumoral heterogeneity across treatment lines. Together, this data positions ctDNA determination as a valuable tool for monitoring disease progression and guiding therapy in metastatic patients. These collective efforts culminated in the initiation of a ctDNA-based randomized clinical trial in GIST, marking a significant milestone in integrating ctDNA testing into the clinical care of GIST patients.

SUMMARY

The dynamic field of ctDNA technologies is rapidly evolving and holds significant promise for research. Several trials have successfully validated the clinical utility of ctDNA in metastatic GIST, laying the foundations for its prospective integration into the routine clinical management of GIST patients.

Decoding the Dynamics of Circulating Tumor DNA in Liquid Biopsies

Circulating tumor DNA (ctDNA), a fragment of tumor DNA found in the bloodstream, has emerged as a revolutionary tool in cancer management. This review delves into the biology of ctDNA, examining release mechanisms, including necrosis, apoptosis, and active secretion, all of which offer information about the state and nature of the tumor. Comprehensive DNA profiling has been enabled by methods such as whole genome sequencing and methylation analysis. The low abundance of the ctDNA fraction makes alternative techniques, such as digital PCR and targeted next-generation exome sequencing, more valuable and accurate for mutation profiling and detection. There are numerous clinical applications for ctDNA analysis, including non-invasive liquid biopsies for minimal residual disease monitoring to detect cancer recurrence, personalized medicine by mutation profiling for targeted therapy identification, early cancer detection, and real-time evaluation of therapeutic response. Integrating ctDNA analysis into routine clinical practice creates promising avenues for successful and personalized cancer care, from diagnosis to treatment and follow-up.

Clinical applications of next-generation sequencing-based ctDNA analyses in breast cancer: defining treatment targets and dynamic changes during disease progression

The advancements in the detection and characterization of circulating tumor DNA (ctDNA) have revolutionized precision medicine and are likely to transform standard clinical practice. The non-invasive nature of this approach allows for molecular profiling of the entire tumor entity, while also enabling real-time monitoring of the effectiveness of cancer therapies as well as the identification of resistance mechanisms to guide targeted therapy. Although the field of ctDNA studies offers a wide range of applications, including in early disease, in this review we mainly focus on the role of ctDNA in the dynamic molecular characterization of unresectable locally advanced and metastatic BC (mBC). Here, we provide clinical practice guidance for the rapidly evolving field of molecular profiling of mBC, outlining the current landscape of liquid biopsy applications and how to choose the right ctDNA assay. Additionally, we underline the importance of exploring the clinical relevance of novel molecular alterations that potentially represent therapeutic targets in mBC, along with mutations where targeted therapy is already approved. Finally, we present a potential roadmap for integrating ctDNA analysis into clinical practice.

Screening for Colorectal Cancer

Colorectal cancer remains the third leading cause of cancer death in the United States. Colorectal cancer screening allows for prevention and early detection of precancerous and cancerous lesions, and screening has been shown to be effective in preventing colorectal cancer deaths. Screening recommendations vary by patient risk profile. A variety of screening modalities exist.

State-of-the-Art Management of Colorectal Cancer: Treatment Advances and Innovation

Colorectal cancer (CRC) remains a significant global health challenge, ranking among the leading causes of cancer-related morbidity and mortality worldwide. Recent advancements in molecular characterization have revolutionized our understanding of the heterogeneity within colorectal tumors, particularly in the context of tumor sidedness. Tumor sidedness, referring to the location of the primary tumor in either the right or left colon, has emerged as a critical factor influencing prognosis and treatment responses in metastatic CRC. Molecular underpinnings of CRC, the impact of tumor sidedness, and how this knowledge guides therapeutic decisions in the era of precision medicine have led to improved outcomes and better quality of life in patients. The emergence of circulating tumor DNA as a prognostic and predictive tool in CRC heralds promising advancements in the diagnosis and monitoring of the disease. This innovation facilitates better patient selection for exploration of additional treatment options. As the field progresses, with investigational agents demonstrating potential as future treatments for refractory metastatic CRC, new avenues for enhancing outcomes in this challenging disease are emerging.

Liquid biopsy for human cancer: cancer screening, monitoring, and treatment

Currently, tumor treatment modalities such as immunotherapy and targeted therapy have more stringent requirements for obtaining tumor growth information and require more accurate and easy-to-operate tumor information detection methods. Compared with traditional tissue biopsy, liquid biopsy is a novel, minimally invasive, real-time detection tool for detecting information directly or indirectly released by tumors in human body fluids, which is more suitable for the requirements of new tumor treatment modalities. Liquid biopsy has not been widely used in clinical practice, and there are fewer reviews of related clinical applications. This review summarizes the clinical applications of liquid biopsy components (e.g., circulating tumor cells, circulating tumor DNA, extracellular vesicles, etc.) in tumorigenesis and progression. This includes the development process and detection techniques of liquid biopsies, early screening of tumors, tumor growth detection, and guiding therapeutic strategies (liquid biopsy-based personalized medicine and prediction of treatment response). Finally, the current challenges and future directions for clinical applications of liquid biopsy are proposed. In sum, this review will inspire more researchers to use liquid biopsy technology to promote the realization of individualized therapy, improve the efficacy of tumor therapy, and provide better therapeutic options for tumor patients.

Assessing circulating tumour DNA (ctDNA) as a prognostic biomarker in locally advanced rectal cancer: a systematic review and meta-analysis

INTRODUCTION

Circulating tumour DNA (ctDNA) has emerged as a promising biomarker in various cancer types, including locally advanced rectal cancer (LARC), offering potential insights into disease progression, treatment response and recurrence. This review aims to comprehensively evaluate the utility of ctDNA as a prognostic biomarker in LARC.

METHODS

PubMed, EMBASE and Web of Science were searched as part of our review. Studies investigating the utility of ctDNA in locally advanced rectal cancer (LARC) were assessed for eligibility. Quality assessment of included studies was performed using the Newcastle Ottawa Scale (NOS) risk of bias tool. Outcomes extracted included basic participant characteristics, ctDNA details and survival data. A meta-analysis was performed on eligible studies to determine pooled recurrence-free survival (RFS).

RESULTS

Twenty-two studies involving 1676 participants were included in our analysis. Methodological quality categorised by the Newcastle Ottawa Scale was generally satisfactory across included studies. ctDNA detected at various time intervals was generally associated with poor outcomes across included studies. Meta-analysis demonstrated a pooled hazard ratio of 8.87 (95% CI 4.91-16.03) and 15.15 (95% CI 8.21-27.95), indicating an increased risk of recurrence with ctDNA positivity in the post-neoadjuvant and post-operative periods respectively.

CONCLUSION

Our systematic review provides evidence supporting the prognostic utility of ctDNA in patients with LARC, particularly in identifying patients at higher risk of disease recurrence in the post-neoadjuvant and post-operative periods.

CRISPR/Cas13a-based supersensitive circulating tumor DNA assay for detecting EGFR mutations in plasma

Despite recent technological advancements in cell tumor DNA (ctDNA) mutation detection, challenges persist in identifying low-frequency mutations due to inadequate sensitivity and coverage of current procedures. Herein, we introduce a super-sensitivity and specificity technique for detecting ctDNA mutations, named HiCASE. The method utilizes PCR-based CRISPR, coupled with the restriction enzyme. In this work, HiCASE focuses on testing a series of EGFR mutations to provide enhanced detection technology for non-small cell lung cancer (NSCLC), enabling a detection sensitivity of 0.01% with 40 ng cell free DNA standard. When applied to a panel of 140 plasma samples from 120 NSCLC patients, HiCASE exhibits 88.1% clinical sensitivity and 100% specificity with 40 μL of plasma, higher than ddPCR and Super-ARMS assay. In addition, HiCASE can also clearly distinguish T790M/C797S mutations in different positions at a 1% variant allele frequency, offering valuable guidance for drug utilization. Indeed, the established HiCASE assay shows potential for clinical applications.

Tumor biomarkers for diagnosis, prognosis and targeted therapy

Tumor biomarkers, the substances which are produced by tumors or the body's responses to tumors during tumorigenesis and progression, have been demonstrated to possess critical and encouraging value in screening and early diagnosis, prognosis prediction, recurrence detection, and therapeutic efficacy monitoring of cancers. Over the past decades, continuous progress has been made in exploring and discovering novel, sensitive, specific, and accurate tumor biomarkers, which has significantly promoted personalized medicine and improved the outcomes of cancer patients, especially advances in molecular biology technologies developed for the detection of tumor biomarkers. Herein, we summarize the discovery and development of tumor biomarkers, including the history of tumor biomarkers, the conventional and innovative technologies used for biomarker discovery and detection, the classification of tumor biomarkers based on tissue origins, and the application of tumor biomarkers in clinical cancer management. In particular, we highlight the recent advancements in biomarker-based anticancer-targeted therapies which are emerging as breakthroughs and promising cancer therapeutic strategies. We also discuss limitations and challenges that need to be addressed and provide insights and perspectives to turn challenges into opportunities in this field. Collectively, the discovery and application of multiple tumor biomarkers emphasized in this review may provide guidance on improved precision medicine, broaden horizons in future research directions, and expedite the clinical classification of cancer patients according to their molecular biomarkers rather than organs of origin.

External Quality Assessment on Molecular Tumor Profiling with Circulating Tumor DNA-Based Methodologies Routinely Used in Clinical Pathology within the COIN Consortium

BACKGROUND

Identification of tumor-derived variants in circulating tumor DNA (ctDNA) has potential as a sensitive and reliable surrogate for tumor tissue-based routine diagnostic testing. However, variations in pre(analytical) procedures affect the efficiency of ctDNA recovery. Here, an external quality assessment (EQA) was performed to determine the performance of ctDNA mutation detection work flows that are used in current diagnostic settings across laboratories within the Dutch COIN consortium (ctDNA on the road to implementation in The Netherlands).

METHODS

Aliquots of 3 high-volume diagnostic leukapheresis (DLA) plasma samples and 3 artificial reference plasma samples with predetermined mutations were distributed among 16 Dutch laboratories. Participating laboratories were requested to perform ctDNA analysis for BRAF exon 15, EGFR exon 18-21, and KRAS exon 2-3 using their regular circulating cell-free DNA (ccfDNA) analysis work flow. Laboratories were assessed based on adherence to the study protocol, overall detection rate, and overall genotyping performance.

RESULTS

A broad range of preanalytical conditions (e.g., plasma volume, elution volume, and extraction methods) and analytical methodologies (e.g., droplet digital PCR [ddPCR], small-panel PCR assays, and next-generation sequencing [NGS]) were used. Six laboratories (38%) had a performance score of >0.90; all other laboratories scored between 0.26 and 0.80. Although 13 laboratories (81%) reached a 100% overall detection rate, the therapeutically relevant EGFR p.(S752_I759del) (69%), EGFR p.(N771_H773dup) (50%), and KRAS p.(G12C) (48%) mutations were frequently not genotyped accurately.

CONCLUSIONS

Divergent (pre)analytical protocols could lead to discrepant clinical outcomes when using the same plasma samples. Standardization of (pre)analytical work flows can facilitate the implementation of reproducible liquid biopsy testing in the clinical routine.