Circulating tumour DNA (ctDNA) is an emerging biomarker for monitoring cancers. The personalised disease monitoring in metastatic breast cancer (PDM-MBC) study is an ongoing study instigated to evaluate ctDNA as a biomarker to individualise imaging requirements in patients with MBC. Patients receiving first-line endocrine therapy (aromatase inhibitor + cyclin-dependent kinase 4/6 inhibitor) had plasma samples collected pre-treatment, weeks 2 and 4, and concurrently with imaging until progressive disease (PD). Here, we apply an experimental analytical workflow for ultrasensitive ctDNA analysis, utilising personalised ctDNA panels designed from mutations identified in tumour tissue, and present results for 24 patients. Twenty patients (83%) had detectable ctDNA pre-treatment. The median progression-free survival was 25.6 months, and 13 patients experienced PD, with rising ctDNA detected at or prior to PD in 12 patients (92%). If imaging had been omitted until the detection of rising ctDNA for at least one mutation, 68% (n = 71) of the scans performed amongst ctDNA-positive patients would have been avoided. Our results demonstrate that integration of personalised ctDNA monitoring of patients with MBC has potential to substantially reduce the imaging needs in patients showing ctDNA response to treatment.

DNA detection via nanoporous-based electrochemical biosensors is a promising method for rapid pathogen identification and disease diagnosis. These sensors detect electrical current variations caused by DNA hybridization in a nanoporous layer on an electrode. Current fabrication techniques for the typically micrometers-thick nanoporous layer often suffer from insufficient control over nanopore dimensions and involve complex fabrication steps, including handling and stacking of a brittle porous membrane. Here, we introduce a bottom-up fabrication process based on the self-assembly of high molecular weight block copolymers with sol-gel precursors to create an inorganic nanoporous thin film directly on electrode surfaces. This approach eliminates the need for elaborate manipulation of the nanoporous membrane, provides fine control over the structural features, and enables surface modification with DNA capture probes. Using this nanoarchitecture with a thickness of 150 nm, we detected DNA sequences derived from 16S rRNA gene fragments of the E. coli genome electrochemically in less than 20 minutes, achieving a limit of detection of 30 femtomolar (fM) and a limit of quantification of 500 fM. This development marks a significant step towards a portable, rapid, and accurate DNA detection system.

Cholangiocarcinoma (CCA) is a highly aggressive and heterogeneous malignancy arising from the epithelial cells of the biliary tract. The limitations of the current methods in the diagnosis of CCA highlight the urgent need for new, accurate tools for early cancer detection, better prognostication and patient monitoring. Liquid biopsy (LB) is a modern and non-invasive technique comprising a diverse group of methodologies aiming to detect tumour biomarkers from body fluids. These biomarkers include circulating tumour cells, cell-free DNA, circulating tumour DNA, RNA and extracellular vesicles. The aim of this review is to explore the current and potential future applications of LB in CCA management, with a focus on diagnosis, prognostication and monitoring. We examine both its significant potential and the inevitable limitations associated with this technology. We conclude that LB holds considerable promise, but further research is necessary to fully integrate it into precision oncology for CCA.

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

The prognosis of patients with locally recurrent oral cavity squamous cell carcinoma (LR-OCSCC) remains poor even when salvage surgery can be performed. Therefore, the current study aimed to identify adverse prognostic factors in these patients and use recursive partitioning analysis (RPA), a machine learning statistical method, to develop a prognostic classification based on these factors.

The clinical data of 75 patients who underwent salvage surgery for LR-OCSCC at the National Cancer Center between 2010 and 2022 were retrospectively reviewed. Prognostic factors were analyzed using Cox proportional hazards regression models. Patients were classified by survival outcomes using RPA. Survival rates were determined using the Kaplan-Meier method.

The 3-year overall survival (OS) and locoregional recurrence rates for all patients who underwent salvage surgery were 53.4% and 32.7%, respectively. The univariate Cox proportional hazards regression analysis identified concurrent regional recurrence, previous history of radiotherapy to the neck, and recurrence within 12 months from initial treatment as adverse prognostic factors. RPA was performed using these variables and patients were classified into low-, intermediate-, and high-risk groups based on a combination of concurrent regional recurrence and time to recurrence. The 3-year OS rates for the low-, intermediate-, and high-risk groups were 73.3%, 53.3%, and 24.4%, respectively.

A novel prognostic classification for LR-OCSCC salvage surgery was developed to facilitate development of treatment strategies and identification of patients that would not benefit from this procedure.

Tracheobronchial tuberculosis (TBTB) is a specific form of pulmonary tuberculosis characterized by Mycobacterium tuberculosis involvement in the tracheobronchial tree. Rapid and accurate diagnostic tools for TBTB are crucial. Raman spectroscopy (RS) is a noninvasive tool that accesses molecular vibrations and sample characteristics, enabling the creation of a molecular fingerprint of biological samples, which has enormous potential on clinical diagnosis for TBTB. This study aimed to develop and validate a diagnostic model based on RS in bronchial biopsies for identifying TBTB. The training set included patients with TBTB (n = 18), airway malignant diseases (n = 20), and normal mucosal tissue biopsies as the healthy controls (n = 20). The spectral analysis results indicated that differential changes in tissue biomolecules, particularly certain amino acids, among the three groups. K-Nearest Neighbors (KNN), principal component analysis-linear discriminant analysis (PCA-LDA), principal component analysis-support vector machine (PCA-SVM) and decision tree methods were implemented to classify this same spectral data set. The PCA-SVM method exhibited highest classification accuracy, with a sensitivity of 88.89 % and an area under the receiver operating characteristic curve (AUROC) of 0.919. Subsequently, an independent validation set comprising 121 patients with suspected TBTB was enrolled to evaluate the performance of RS model using the PCA-SVM method. The sensitivity of RS model was 87.69 % (57/65) for diagnosing TBTB, higher than that of sputum smear, bronchial brush smear, the Bactec MGIT 960 Culture of bronchoalveolar lavage fluid, and comparable to GeneXpert sensitivity. In conclusion, the RS model using bronchial tissue provides a rapid and accurate method of identifying TBTB, showing potential as a powerful noninvasive tool for TBTB diagnosis under bronchoscopy.

Accurate non-invasive tests to improve early detection and diagnosis of lung cancer are urgently needed. However, no regulatory-approved blood tests are available for this purpose. We aimed to improve pulmonary nodule classification to identify malignant nodules in a high-prevalence patient group.

This study involved 806 participants with undiagnosed nodules larger than 5 mm, focusing on assessing nucleosome levels and histone modifications (H3.1 and H3K27Me3) in circulating blood. Nodules were classified as malignant or benign. For model development, the data were randomly divided into training (n = 483) and validation (n = 121) datasets. The model's performance was then evaluated using a separate testing dataset (n = 202).

Among the patients, 755 (93.7%) had a tissue diagnosis. The overall malignancy rate was 80.4%. For all datasets, the areas under curves were as follows: training, 0.74; validation, 0.86; and test, 0.79 (accuracy range: 0.80-0.88). Sensitivity showed consistent results across all datasets (0.91, 0.95, and 0.93, respectively), whereas specificity ranged from 0.37 to 0.64. For smaller nodules (5-10 mm), the model recorded accuracy values of 0.76, 0.88, and 0.85. The sensitivity values of 0.91, 1.00, and 0.94 further highlight the robust diagnostic capability of the model. The performance of the model across the reporting and data system (RADS) categories demonstrated consistent accuracy.

Our epigenetic biomarker panel detected non-small-cell lung cancer early in a high-risk patient group with high sensitivity and accuracy. The epigenetic biomarker model was particularly effective in identifying high-risk lung nodules, including small, part-solid, and non-solid nodules, and provided further evidence for validation.

Breast cancer management has traditionally relied on tissue biopsies and imaging, which offer limited insights into the disease. However, the discovery of circulating tumor DNA (ctDNA) and minimal residual disease (MRD) detection has revolutionized our approach to breast cancer. ctDNA, which is fragmented tumor DNA found in the bloodstream, provides a minimally invasive way to understand the tumor's genomic landscape, revealing heterogeneity and critical mutations that biopsies may miss. MRD, which indicates cancer cells that remain after treatment, can now be detected using ctDNA and other advanced methods, improving our ability to predict disease recurrence. This allows for personalized adjuvant therapies based on individual MRD levels, avoiding unnecessary treatments for patients with low MRD. This review discusses how ctDNA and MRD represent a paradigm shift towards personalized, genomically guided cancer care, which has the potential to significantly improve patient outcomes in breast cancer.

This study investigated whether digital polymerase chain reaction (dPCR)-based circulating tumor DNA (ctDNA) monitoring can allow longer intervals between computed tomography (CT) scans during postoperative surveillance of colorectal cancer (CRC).

Practical guidelines still recommend intensive postoperative surveillance of CRC using periodical CT scans and serum carcinoembryonic antigen testing.

The longitudinal dynamics of ctDNA for 52 patients with CRC as measured by dPCR using probes targeting 87 individual tumor-specific mutations (1-5 per patient) were compared with results from conventional (ie, clinical) surveillance using serum tumor markers and CT.

A total of 382 CT procedures were carried out for the patient cohort (3.3/year per patient) and the median lead time from ctDNA relapse to clinical relapse was 182 days (range, 0-376 days). If the CT interval was annual, potential delays in the detection of clinical relapse would have occurred for 7 of the 10 patients who experienced clinical relapse (9 of 13 events), with a median delay of 164 days (range, 0-267 days). If annual CT surveillance was performed together with ctDNA monitoring, 218 (57.1%) CTs would not have been needed to detect the first clinical relapse. In addition, the ctDNA monitoring would have provided a lead time of 339 days for detection of clinical relapse (range, 42-533 days).

Our findings suggest that the ctDNA monitoring as part of postoperative surveillance and clinical relapse detection for patients with CRC could allow the CT interval to be lengthened.

This trial was registered with University Hospital Medical Information Network Clinical Trial Registry (UMIN000045114).

Monitoring of metastatic breast cancer (mBC) is an important issue in the clinical management of patients. Liquid biopsy has become a non-invasive method for detecting and monitoring cancer in body fluids. The presence of circulating tumor cells (CTCs) and circulating tumor DNA (ctDNA) in peripheral blood indicates poor prognosis and may contribute to early detection of progression, but assessment of these levels is still not routine clinical management. The main objective of this study was to estimate the frequency and clinical value of the ESR1 and PIK3CA mutations identified in circulating free DNA (cfDNA.) The second goal was to evaluate whether simultaneous evaluation of CTCs and mutation status in cfDNA increases the prognostic value of liquid biopsy. The results of the analysis of the CTC number and ESR1 and PIK3CA mutations in blood collected from 179 patients with metastatic breast cancer show that ESR1 mutations are more frequent in patients with advanced luminal breast cancer regardless of the type of the treatment. ESR1 mutations appear primarily during progression, as no mutations were found in primary tumor samples. The main conclusion of the study is that combined assessment of CTCs and ESR1 status in liquid biopsy may improve the prognostic value of liquid biopsy.

The surgeon's subjective intraoperative evaluation is the standard of care to assess postoperative residual disease (RD) in advanced epithelial ovarian cancer (EOC). We investigated the feasibility of ctDNA as an objective marker for postoperative RD.

This prospective study included 27 patients with advanced ovarian cancer (FIGO IIIA1-IVB) who underwent primary surgery between July 2021 and July 2022. Blood samples were analyzed preoperatively and on days 2 (d2) and 10 (d10) postoperatively. Low-coverage whole genome sequencing (WGS) was used to identify structural variants (SVs) at single-base pair resolution, single nucleotide variants (SNVs), and indels in tumor tissue to develop personalized, tumor-informed digital polymerase chain reaction (dPCR) fingerprint assays for each patient.

dPCR fingerprint assays were successfully developed for all patients by identifying one to eight SVs/SNVs per patient. ctDNA was detected in 96% (n = 26/27) of patients preoperatively and in 81% (n = 22/27) of patients at d10. Median ctDNA levels at d10 were significantly higher in patients with postoperative RD (median 367.38 copies (cps)/mL, 2.84% variant allele frequency; VAF) than in patients without postoperative RD (median 0.92 cps/mL, 0.017% VAF, p < 0.001). In patients with postoperative RD, ctDNA levels increased from the preoperative stage to d10 in seven out of eight patients (p = 0.016). In patients with complete tumor resection, ctDNA levels decreased from the preoperative stage to d10 in 17/19 patients (p < 0.001).

A tumor-informed personalized ctDNA approach demonstrated feasibility, providing extremely high detection rates pre- and postoperatively. These results indicate that this approach could potentially be used for postoperative RD assessment in patients with primary advanced EOC.

Tumor heterogeneity and clonal evolution are related to the treatment resistance and disease progression in metastatic breast cancer (MBC). However, the process of clonal evolution and their relationship to prognosis remain unclear. This study aimed to elucidate the evolution of MBC through circulating tumor DNA (ctDNA) analysis and to develop a novel indicator for predicting treatment efficacy and prognosis.

This multicenter retrospective study enrolled MBC patients who underwent next-generation sequencing between April 2016 and October 2022. The clonal evolution of tumors was inferred using PyClone and CITUP software.

The study included 406 MBC patients. A cohort of 139 patients from the National Cancer Center served as the training cohort, while 267 patients from other centers comprised the validation cohort. In the training cohort, clonal analysis revealed that most MBCs exhibited branched clonal evolution, while a minority showed linear evolution. The branched evolution pattern was associated with slower disease progression (HR, 0.53; 95% CI, 0.32-0.87; P = 0.012). We introduced tumor clonal evolution rate (TER) as a novel concept to reflect the speed of clonal evolution. Survival analysis demonstrated that compared to the TER-high group, patients in the TER-low group had better progression-free survival (PFS) (HR, 0.62; 95% CI, 0.40-0.96; P = 0.033) and overall survival (OS) (HR, 0.45; 95% CI, 0.24-0.85; P = 0.013). Similarly, in the validation cohort, although the median OS was not reached, patients in the TER-low group had better prognosis compared to those in the TER-high group (HR, 0.41; 95% CI, 0.21-0.83; P < 0.001).

Patients with branched evolution have better treatment efficacy than those with linear evolution. The TER shows potential as a biomarker for treatment efficacy and prognosis, providing new evidence that ctDNA is a valuable molecular indicator for predicting treatment outcomes in metastatic breast cancer.

Early detection and precise tumor localization are critical for improving treatment outcomes and enabling more targeted and minimally invasive therapies as biotechnology evolves. However, endogenous biomarkers from early lesions face significant challenges, such as short circulation times and blood dilution, which hinder early diagnostic efforts. In this study, we present a multimodal nanosensor specifically engineered to target cancer by responding to CD44 and tumor-associated enzymes within the microenvironment. Following systemic administration, the nanosensor selectively accumulates at the disease site, delivering hexaminolevulinate (HAL) to produce protoporphyrin IX (PpIX) as a synthetic biomarker, thus amplifying disease signals for analysis via a microfluidics-based device. Concurrently, embedded Gd2O3 nanoclusters facilitate tumor visualization through magnetic resonance imaging (MRI). Beyond tumor diagnosis, this innovative methodology supports the multimodal monitoring of drug response through the assessment of blood reporter signals and MRI imaging. This multifunctional system addresses critical limitations in traditional cancer diagnostics, which typically rely on sequential blood biomarker tests, followed by imaging. Our approach enhances diagnostic efficiency, minimizes the need for invasive procedures, and promotes more accurate and personalized cancer care.

Melanoma is one of the deadliest skin cancers and challenges clinicians worldwide due to rising incidence, potential aggressiveness, and propensity for metastasis, necessitating comprehensive follow-up programs after primary treatment. Circulating tumor DNA (ctDNA) is a promising biomarker that may indicate disease progression earlier than traditional surveillance methods, including 18F-FDG PET-CT, ultrasound, and clinical examination. This study examines ctDNA detection in blood as a minimally invasive method for early identification of progression following primary treatment of melanoma. The aim is to overcome the limitations of current methods, potentially improving prognosis and survival.

Patients with high risk of recurrence following primary treatment of melanoma are offered inclusion. Blood sampling is performed at each follow-up visit. In case of recurrence, patient-specific mutations are identified through next-generation sequencing (NGS) of formalin and paraffin embedded tissue from diagnostic routine. Detection of mutation-specific ctDNA is performed on blood using digital droplet polymerase chain reaction (ddPCR) or NGS. This allows determination of the value and sensitivity of ctDNA for early detection of recurrence.

For validation purposes, we conducted a small pilot study using blood samples from 10 patients who had experienced recurrence and had a clinically confirmed BRAF V600E mutation. Detection of BRAF V600E ctDNA using ddPCR varied from 0/5 (0%) in DNA harvested from 4 mL plasma, to 3/5 (60%) in DNA from 8 mL of plasma. These results show promise and highlight the importance of high sensitivity and sampling volumes to ensure accurate detection of low levels of ctDNA.

Disruption of cyclin D-dependent kinases (CDKs), particularly CDK4/6, drives cancer cell proliferation via abnormal protein phosphorylation. This open-label, single-arm, phase Ib/II trial evaluated the efficacy of the CDK4/6 inhibitor, abemaciclib, combined with paclitaxel against CDK4/6-activated tumors.

Patients with locally advanced or metastatic solid tumors with CDK4/6 pathway aberrations were included. Based on phase Ib, the recommended phase II doses were determined as abemaciclib 100 mg twice daily and paclitaxel 70 mg/m2 on days 1, 8, and 15, over 4-week-long cycles. The primary endpoint for phase II was the overall response rate (ORR). The secondary endpoints included the clinical benefit rate (CBR), progression-free survival (PFS), overall survival (OS), and safety. Tissue-based next-generation sequencing and exploratory circulating tumor DNA analyses were carried out.

Between February 2021 and April 2022, 30 patients received abemaciclib/paclitaxel (median follow-up: 15.7 months), and 27 were included in the efficacy analysis. CDK4/6 amplification (50%) and CCND1/3 amplification (20%) were common activating mutations. The ORR was 7.4%, with two partial responses, and the CBR was 66.7% (18/27 patients). The median OS and PFS were 9.9 months [95% confidence interval (CI) 5.7-14.0 months] and 3.5 months (95% CI 2.6-4.3 months), respectively. Grade 3 adverse events (50%, 21 events) were mainly hematologic. Genetic analysis revealed a 'poor genetic status' subgroup characterized by mutations in key signaling pathways (RAS, Wnt, PI3K, and NOTCH) and/or CCNE amplification, correlating with poorer PFS.

Abemaciclib and paclitaxel showed moderate clinical benefits for CDK4/6-activated tumors. We identified a poor genetic group characterized by bypass signaling pathway activation and/or CCNE amplification, which negatively affected treatment response and survival. Future studies with homogeneous patient groups are required to validate these findings.

Not all breast cancer (BC) patients can benefit from neoadjuvant therapy (NAT). A poor response may result in patients missing the best opportunity for treatment, ultimately leading to a poor prognosis. Thus, to identify an effective predictor that can assess and predict patient response at early time points, we focused on circulating tumor DNA (ctDNA), which is a vital noninvasive liquid biopsy biomarker. We performed a meta-analysis to explore the predictive value of response by monitoring ctDNA at four time points of NAT using pathologic complete response (pCR) and residual cancer burden (RCB).

By searching Embase, PubMed, the Cochrane Library, and the Web of Science until December 24, 2023, we selected studies concerning the relationship between ctDNA and response or prognosis. We analysed the results at the following various time points: baseline (T0), first cycle of NAT (T1), mid-treatment (MT), and end of NAT (EOT). pCR and RCB were used to evaluate the response as the primary endpoint. The secondary endpoint was to investigate the relationship between ctDNA and prognosis. Odds ratios (ORs) and hazard ratios (HRs) were used as effect indicators.

Thirteen reports from twelve studies were eligible for inclusion in this meta-analysis. The results demonstrated that ctDNA negativity was associated with pCR at T1 (OR = 0.34; 95% CI: 0.21-0.57), MT (OR = 0.35; 95% CI: 0.20-0.60), and EOT (OR = 0.38; 95% CI: 0.22-0.66). When RCB was used to evaluate responses, ctDNA negativity was associated with RCB-0/I at the MT (OR = 0.34; 95% CI: 0.21-0.55) and EOT (OR = 0.26; 95% CI: 0.15-0.46). Furthermore, ctDNA positivity at T1 predicted a worse prognosis for patients (HR = 2.73; 95% CI: 1.29-5.75). We also performed a subgroup analysis to more accurately assess the predictive value of ctDNA for triple-negative breast cancer.

Our meta-analysis suggested that the ctDNA status at the early stage of NAT can predict patient response, which provides evidence for adjusting personalized treatment strategies and improving patient survival.

CRD42024496465.

Colorectal cancer (CRC) represents a heterogeneous group of diseases that imposes a considerable global and national health burden. Although most CRC patients are diagnosed at an early stage and undergo potentially curative treatment, a significant proportion experience recurrence. Currently, adjuvant chemotherapy decisions are primarily based on clinicopathological characteristics, which have well-recognized limitations in accurately identifying patients harboring minimal residual disease (MRD), often resulting in unnecessary chemotherapy exposure. Circulating tumor DNA (ctDNA) has emerged as a promising surrogate marker for MRD, offering a more precise approach to identifying patients at risk of recurrence after curative-intent surgery and refining adjuvant chemotherapy decisions. Growing evidence from multiple studies has demonstrated that ctDNA outperforms traditional clinicopathological factors as a marker for MRD. This review synthesizes key studies supporting the role of ctDNA in MRD detection for CRC patients and evaluates clinical trials investigating the application of ctDNA in guiding adjuvant therapy decisions. This emerging strategy holds the potential to transform the adjuvant treatment paradigm in colorectal cancer by optimizing therapeutic precision and minimizing unnecessary treatment.

Triple-positive breast cancer (TPBC), defined by the co-expression of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2), poses unique therapeutic challenges due to complex signaling interactions and resulting treatment resistance. This review summarizes key findings on the molecular mechanisms and cross-talk among ER, PR, and HER2 pathways, which drive tumor proliferation and resistance to conventional therapies. Current strategies in TPBC treatment, including endocrine and HER2-targeted therapies, are explored alongside emerging approaches such as immunotherapy and CRISPR/Cas9 gene editing. Additionally, we discuss the tumor microenvironment (TME) and its role in treatment resistance, highlighting promising avenues for intervention through combination therapies and predictive biomarkers. By addressing these interdependent pathways and optimizing therapeutic strategies, precision medicine holds significant potential for improving TPBC patient outcomes and advancing individualized cancer care.

Plasma cell-free DNA (cfDNA) analysis to track estrogen receptor 1 (ESR1) mutations is highly beneficial for the identification of tumor molecular dynamics and the improvement of personalized treatments for patients with metastatic breast cancer (MBC). Plasma-cfDNA is, up to now, the most frequent liquid biopsy analyte used to evaluate ESR1 mutational status. Circulating tumor cell (CTC) enumeration and molecular characterization analysis provides important clinical information in patients with MBC. In this study, we investigated whether analysis of CTCs and circulating tumor DNA (ctDNA) provide similar or complementary information for the analysis of ESR1 mutations. We analyzed both plasma-cfDNA (n = 90) and paired CTC-derived genomic DNA (gDNA; n = 42) from 90 MBC patients for seven ESR1 mutations. Eight out of 90 (8.9%) plasma-cfDNA samples tested using the ddPLEX Mutation Detection Assay (Bio-Rad, Hercules, CA, USA), were found positive for one ESR1 mutation, whereas 11/42 (26.2%) CTC-derived gDNA samples were found positive for at least one ESR1 mutation. Direct comparison of paired samples (n = 42) revealed that the ESR1 mutation rate was higher in CTC-derived gDNA (11/42, 26.2%) than in plasma-cfDNA (6/42, 14.3%) samples. Our results, using this highly sensitive ddPLEX assay, reveal a higher percentage of mutations in CTC-derived gDNAs than in paired ctDNA in patients with MBC. CTC-derived gDNA analysis should be further evaluated as an important and complementary tool to ctDNA for identifying patients with ESR1 mutations and for guiding individualized therapy.

Biomarkers reflecting real-time response to therapy and recurrence are lacking. We assessed the clinical value of detecting cell-free circulating tumor DNA (ctDNA) mutations in endometrial cancer (EC) and ovarian cancer (OC) patients.

EC/OC patients undergoing primary surgery were consented for tissue banking and 2-year serial blood draws. Tumor tissue DNA and plasma ctDNA underwent next generation sequencing using a targeted gene panel for somatic mutations.

Of 44 patients (24 EC, 17 OC, 2 synchronous endometrial and ovarian carcinomas [SEOC] and 1 endocervical adenocarcinoma [EA]) at least one somatic mutation was identified in tumor tissue in 40 (91%, 20/24 EC, all OC/SEOC/EA), and in preoperative plasma ctDNA in 12 (27%) patients (6/24 [25%] EC and 6/17 [35%] OC). Detection of preoperative ctDNA mutations was associated with advanced stage, higher preoperative CA125, and subsequent disease recurrence. In 5/12 (42%) patients with preoperative ctDNA mutations, examination/imaging suggested clinical stage I however final pathology revealed stage II/III. In 11 patients where serial timepoints were assessed during treatment for ctDNA and CA125, ctDNA clearance preceded normalization of CA125. Thirteen patients developed recurrent disease (4 EC, 8 OC, 1 EA); 8 in whom ctDNA mutations were detected postoperatively, and 4 followed through time of recurrence with ctDNA mutations identified 2-5 months prior to clinical/radiologic/biomarker progression in 3.

ctDNA can reflect larger tumor volume/metastases, treatment response and subsequent disease recurrence in EC and OC. Careful patient selection is critical to direct resources to patients most likely to benefit, considering disease burden and risk group.

Circulating tumor DNA (ctDNA) quantification surpasses cancer antigen 15 to 3 for metastatic breast cancer surveillance. Clinical translation, however, is limited because of uncertainties about the optimal method and clinically valid ctDNA decision thresholds. Plasma-SeqSensei Breast Cancer IVD kit (PSS) is a novel assay for ctDNA molecular counting, detecting ≥0.06% variant allele fractions in AKT1, ERBB2, ESR1, KRAS, PIK3CA, and TP53. PSS was validated against droplet digital PCR (ddPCR) in 201 samples from 16 subjects with PIK3CA/TP53-mutated cancers, longitudinally sampled for a median of 93 (range, 18 to 113) weeks, three to five weekly. PSS and ddPCR ctDNA levels correlate significantly (Spearman ρ, 0.923; 95% CI, 0.898-0.941) across 0% to 43% variant allele frequency (VAF) range. PSS predicts 12-week progression with high clinical accuracy (area under the curve, 0.848; 95% CI, 0.790-0.894). PSS validates a previously developed ddPCR classifier: <10 copies/mL (0.25% VAF); excludes >100 copies/mL (2.5% VAF); and confirms progression, with negative predictive value (95% CI) of 83% (76%-88%) and positive predictive value (95% CI) of 91% (81%-96%) (weighted κ, 0.856; 95% CI, 0.797-0.915). PSS thus confirms robust clinical thresholds (10 to 100 copies/mL, 0.25% to 2.5% VAF) for metastatic breast cancer surveillance, using absolute molecular counting.

This study aimed to analyse the correlation between the expression of cell proliferation-associated antigen (Ki-67), cell cycle protein-dependent kinase 4 (CDK4), epidermal growth factor receptor (EGFR), tumour-infiltrating lymphocytes (TILs) and circulating tumour DNA (ctDNA) with the outcome and prognosis of patients with breast cancer (BC) undergoing neoadjuvant chemotherapy (NACT).

We retrospectively analysed the clinicopathological data of 231 patients with BC who underwent preoperative NACT at XX Hospital between 1 January 2018 and 31 December 2021. Logistic regression models were used to analyse factors influencing NACT efficacy. The Cox risk regression model was used to analyse prognostic factors. The TILs were assessed on pre-treatment biopsies, and ctDNA levels were monitored during NACT. Propensity score matching and subgroup analyses were performed.

After 4-6 cycles of chemotherapy, the response rate was 77.92% (180/231), with 58.87% (136/231) achieving pathological complete response (pCR). Multifactorial analysis showed that tumour, node and metastasis (TNM) stage II, EGFR positivity, low Ki-67 expression, CDK4 negativity, non-triple-negative subtypes and effective NACT results were associated with higher pCR rates. Higher TIL levels correlated with increased pCR rates (72.4% for high TILs vs 39.1% for low TILs, p < 0.001). The ctDNA levels decreased significantly in patients with pCR compared with patients without pCR during NACT (p < 0.001). After propensity score matching, the 3-year disease-free survival rate was significantly higher in the pCR group (88.9% vs 71.1%, p = 0.003). Subgroup analysis revealed varying pCR rates and predictive biomarkers across BC subtypes.

The TNM classification, EGFR, Ki-67, CDK4 expression, BC subtype and NACT results have predictive value for pCR in patients with BC. Lower TNM classification, lower Ki-67 expression and EGFR positivity are associated with better outcomes. High TIL levels and significant decreases in ctDNA during NACT correlate with improved response and prognosis. These findings highlight the potential for integrating traditional clinicopathological factors with novel biomarkers for personalised treatment strategies in BC.

DNA methylation is known to be involved in tumor progression. This is the first study to perform an extensive methylation analysis of plasma circulating tumor DNA (ctDNA) using targeted bisulfite sequencing in gastric cancer (GC) patients to evaluate the usefulness of ctDNA methylation as a new biomarker. Sixteen patients who received chemotherapy for recurrent GC were included. After confirmation of the methylation status of 63 genes using the Cancer Genome Atlas (TCGA) dataset, the methylation status in paired tumor and non-tumor tissues and plasma were investigated using targeted bisulfite sequencing in these genes. Forty-four of the 63 genes were significantly hypermethylated in GC patients in the TCGA cohort. Of these 44 genes, hierarchical clustering showed that five (SPG20, FBN1, SDC2, TFPI2, SEPT9) were particularly hypermethylated in tumor compared to non-tumor tissues in our GC cohort. In plasma methylation analysis, patients with high methylation of these genes had significantly worse overall survival than those with low methylation (log-rank P = 0.009). In a patient who underwent blood sampling at multiple points, the methylation levels of these five genes varied closely with clinical tumor status. The plasma ctDNA methylation levels of these five genes could be useful as a noninvasive prognostic biomarker for GC.

The use of liquid biopsy of total cell-free DNA (cfDNA) to identify otherwise undetectable cancers has attracted interest; however, its efficacy remains unknown. We explored whether analysis using total cfDNA is efficacious for Japanese patients with oral squamous cell carcinoma (OSCC).

We collected total cfDNA from nine patients with OSCC preoperatively, 1 month postoperatively, and every 3 months thereafter to analyze this association. We used a target DNA sequence for genetic mutation analysis of tumor tissues collected from 33 patients, including the aforementioned nine patients.

Patients with good disease control showed negligible changes in preoperative and postoperative total cfDNA concentrations. A rapid increase in total cfDNA concentration was observed in patients who developed systemic metastases. Patients whose tumor tissue DNA showed genetic mutations had the same mutations in preoperative circulating tumor DNA.

Our data suggested that analyzing total cfDNA is efficacious for patients with OSCC.

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.

Breast cancer is the most common malignant tumour in women, with more than 685,000 women dying of breast cancer each year. The heterogeneity of breast cancer complicates both treatment and diagnosis. Traditional methods based on histopathology and hormone receptor status are now no longer sufficient. Recently, advances in multi-omics techniques, including genomic, proteomic, and transcriptomic analyses, have deepened our understanding of breast cancer. Combining these approaches allows for precise molecular subtyping, which is essential for the detection of key mutations, protein interactions and gene expression patterns that are highly relevant to different therapeutic strategies. Genomic analyses have been effectively identifying key mutations in cancer. Meanwhile, proteomics and transcriptomics complement by identifying new therapeutic targets and elucidating gene expression dynamics. Integrating multi-omics and conventional diagnostics improves tumour characterisation and enables prognostic accuracy comparable to established standards and treatment response. Existing and emerging technologies enable real-time enhanced tumour follow-up and data analysis through liquid biopsy and artificial intelligence, respectively. Despite these clinical implementation challenges, multi-omics including clinical phenotyping offers significant potential for precision breast cancer treatment. This article describes recent advances in molecular subtyping and multi-omics technologies that are driving key innovations to optimise patient outcomes and further develop personalised medicine in the context of breast cancer care.

Cancer cells secrete extracellular vesicles (EV) encapsulating bioactive cargoes to facilitate inter-organ communication in vivo and are emerging as critical mediators of tumor progression and metastasis, a condition which is often accompanied by a dysregulated cholesterol metabolism. Whether EVs are involved in the control of cholesterol homeostasis during tumor metastasis is still undefined and warrant further investigation. Here, we find that breast cancer-derived exosomal miR-9-5p induces the expression of HMGCR and CH25H, two enzymes involved in cholesterol synthesis and the conversion of 25-hydroxycholesterol from cholesterol by targeting INSIG1, INSIG2 and ATF3 genes in the liver. Notably, in vivo miR-9-5p antagomir treatment and genetic CH25H ablation prevents tumor metastasis in a mouse model of breast cancer. Thus, our findings reveal the regulatory mechanism of tumor-derived miR-9-5p in liver metastasis by linking oxysterol metabolism and Kupffer cell polarization, shedding light on future applications for cancer diagnosis and treatment.

Cancer has a high mortality rate across the globe, and tissue biopsy remains the gold standard for tumor diagnosis due to its high level of laboratory standardization, good consistency of results, relatively stable samples, and high accuracy of results. However, there are still many limitations and drawbacks in the application of tissue biopsy in tumor. The emergence of liquid biopsy provides new ideas for early diagnosis and prognosis of tumor. Compared with tissue biopsy, liquid biopsy has many advantages in the diagnosis and treatment of various types of cancer, including non-invasive, quickly and so on. Currently, the application of liquid biopsy in tumor detection has received widely attention. It is now undergoing rapid progress, and it holds significant potential for future applications. Around now, liquid biopsies encompass several components such as circulating tumor cells, circulating tumor DNA, exosomes, microRNA, circulating RNA, tumor platelets, and tumor endothelial cells. In addition, advances in the identification of liquid biopsy indicators have significantly enhanced the possibility of utilizing liquid biopsies in clinical settings. In this review, we will discuss the application, advantages and challenges of liquid biopsy in some common tumors from the perspective of diverse systems of tumors, and look forward to its future development prospects in the field of cancer diagnosis and treatment.

Diagnosis is the most important step in different diseases, especially in cancers and blood malignancies. There are different methods in order to better diagnose of cancer, but many of them are invasive and also, some of them are not useful for immediate diagnosis. Cell-free DNA (cfDNA) or liquid biopsy easily accessible in peripheral blood is one of the non-invasive prognostic biomarkers in various areas of cancer management. In fact, amounts of cfDNA in serum or plasma can be used for diagnosis. In this review, we have considered some cancers such as hepatocellular carcinoma, lung cancer, breast cancer, and hematologic malignancies to compare the various methods of cfDNA diagnosis.

Extracellular vesicles (EVs) are cell-derived small membrane structures that transport various molecules. They have emerged as potential circulating biomarkers for monitoring responses to cancer therapies. This study aimed to comprehensively characterize plasma-carried EVs in hormone receptor-positive (HR+) metastatic breast cancer (MBC) patients treated with first-line CDK4/6 inhibitors (iCDK4/6) combined with endocrine therapy. MBC patients were classified into three groups based on their response to therapy: resistant, intermediate or sensitive. In a prospective cohort, we monitored the concentration of circulating EVs, analyzed their lipid signature and correlated these factors with treatment response. To facilitate the translation of EV research to clinical practice, we established a three-step procedure: (1) EVs were isolated from plasma using semi-automatized size exclusion chromatography (SEC); (2) EV concentration, termed vesiclemia, was determined by drop counting via interferometric light microscopy (ILM); and (3) EV lipid composition was analyzed by mass spectrometry. ILM-based vesiclemia values were highly fluctuating upon iCDK4/6 treatment, while early increase associated with accelerated progression. Of note, vesiclemia remained a steady parameter over a 1-year period in age-matched healthy women. Additionally, analysis of the EV cargo unveiled a distinct sphingolipid profile, characterized by increased levels of ceramides and sphingomyelins in resistant patients within the first 2 months of treatment. Based on 16 sphingolipid species, sensitive and resistant patients were correctly classified with an overall accuracy of 82%. This specific sphingolipid pattern was exclusively discernible within EVs, and not in plasma, highlighting the significance of EVs in the early prediction of individual responses to iCDK4/6 and disease progression. Overall, this study provides insights of the longitudinal characterization of plasma-borne EVs in both a healthy group and HR+ MBC patients under iCDK4/6 therapies. Combined vesiclemia and EV sphingolipid profile emphasize the promising potential of EVs as non-invasive biomarkers for monitoring early treatment response.

The diagnosis of brain tumors typically relies on magnetic resonance imaging (MRI), computed tomography (CT), and invasive procedures like biopsies or surgical resection for confirmation and genetic profiling. However, these methods have limitations, especially in distinguishing treatment effects like pseudo-progression from actual tumor progression, and repeated biopsies pose risks. Liquid biopsy (LB) offers a non-invasive alternative, detecting tumor-derived biomarkers in blood and cerebrospinal fluid (CSF). Despite its potential, the low concentration of brain tumor biomarkers in blood due to the blood-brain barrier (BBB), limits the clinical utility of LB. MRI-guided focused ultrasound (MRgFUS) combined with microbubbles provides a novel solution by temporarily disrupting the BBB, facilitating the passage of therapeutic agents, and enabling tumor biomarker detection. This technique, termed "sonobiopsy," enables non-invasive biomarker collection for liquid biopsy, potentially improving brain tumor diagnosis and monitoring.

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.

Breast cancer (BC) is caused by the uncontrolled proliferation of breast epithelial cells followed by malignant transformation, and it has the highest incidence among female malignant tumors. The metastasis of BC occurs through direct and lymphatic spread. Although ocular metastasis is relatively rare, it is a good indicator of a worse prognosis. We used machine learning (ML) to establish a model to analyze the risk factors of BC eye metastasis.

The clinical data of 2225 patients with BC from 2003 to 2019 were collected and randomly classified into the training and test sets using a ratio of 7:3. Based on the presence or absence of eye metastasis, the patients with BC were classified into the ocular metastasis (OM) and non-ocular metastasis (NOM) groups. Univariate and multivariate logistic regression analyses and least absolute shrinkage and selection operator (LASSO) were conducted. We used six ML algorithms to establish a predictive BC model and used 10-fold cross-validation for internal verification. The area under the receiver operating characteristic (ROC) curve was used to evaluate the predictive ability of the model. In addition, we established a web hazard calculator depending on the best-performing model to facilitate its clinical application. Shapley additive interpretation (SHAP) was used to determine the risk factors and the interpretability of the black box model.

Univariate logistic regression analysis showed that histopathology (other types), axillary lymph node metastasis (ALNM) (> 4), Ca2+, total cholesterol (TC), low-density lipoprotein (LDL), apolipoprotein A (ApoA), carcinoembryonic antigen (CEA), carbohydrate antigen (CA) 125, CA153, CA199, alkaline phosphatase (ALP), and hemoglobin (Hb) were risk factors for BC eye metastasis. Multivariate logistic regression analysis showed that CA153, ApoA, and LDL were hazardous components for BC eye metastasis. LASSO showed that ALNM, LDL, CA125, Hb, ALP, and CA199 were the first six key variables that were useful for the diagnosis of ocular metastasis in breast cancer. Bootstrapped aggregation (BAG) demonstrated the discriminative ability (area under ROC curve [AUC] = 0.992, accuracy = 0.953, sensitivity = 0.987). Based on this, we applied the BAG machine learning model to build an online web computing system to help clinicians assist in determining the risk of BC eye metastasis. In addition, two typical cases are analyzed to determine the interpretability of the model.

We used ML to establish a risk prediction model for BC ocular metastasis, and BAG showed the greatest performance. The model can predict the risk of OM in patients with BC, facilitate early and timely diagnosis and treatment, and reduce the burden on society.

The progress that has been made in recent years in relation to liquid biopsies in general and circulating tumor DNA (ctDNA) in particular can be seen as groundbreaking for the future of breast cancer treatment, monitoring and early detection. Cell-free DNA (cfDNA) consists of circulating DNA fragments released by various cell types into the bloodstream. A portion of this cfDNA, known as ctDNA, originates from malignant cells and carries specific genetic mutations. Analysis of ctDNA provides a minimally invasive method for diagnosis, monitoring response to therapy, and detecting the emergence of resistance. Several methods are available for the analysis of ctDNA, each with distinct advantages and limitations. Quantitative polymerase chain reaction is a well-established technique widely used due to its high sensitivity and specificity, particularly for detecting known mutations. In addition to the detection of individual mutations, multigene analyses were developed that could detect several mutations at once, including rarer mutations. These methods are complementary and can be used strategically depending on the clinical question. In the context of metastatic breast cancer, ctDNA holds particular promise as it allows for the dynamic monitoring of tumor evolution. Through ctDNA analysis, mutations in the ESR1 or PIK3CA genes, which are associated with therapy resistance, can be identified. This enables the early adjustment of treatment and has the potential to significantly enhance clinical outcome. The application of ctDNA in early breast cancer is an ongoing investigation. In (neo)adjuvant settings, there is preliminary data indicating that ctDNA can be used for therapy monitoring and risk stratification to decide on post-neoadjuvant strategies. In the monitoring of aftercare, the detection of ctDNA appears to be several months ahead of routine imaging. However, the feasibility of implementing this approach in a clinical setting remains to be seen. While the use of ctDNA as a screening method for the asymptomatic population would be highly advantageous due to its minimally invasive nature, the available data on its clinical benefit are still insufficient. Nevertheless, ctDNA represents the most promising avenue for fulfilling this potential future need.

Early indicators of metastatic cancer response to therapy are important for evaluating new drugs and stopping ineffective treatment. The RECIST guidelines based on repeat cancer imaging are widely adopted in clinical trials, are used to identify active regimens that may change practice, and contribute to regulatory approvals. However, these criteria do not provide insight before 6 to 12 weeks of treatment and typically require that patients have measurable disease. Recent data suggest that measuring on-treatment changes in the amount or proportion of ctDNA in peripheral blood plasma may accurately identify responding and nonresponding cancers at earlier time points. Over the past year, the RECIST working group has evaluated current evidence for plasma ctDNA kinetics as a treatment response biomarker in metastatic cancers and early endpoint in clinical trials to identify areas of focus for future research and validation. Here, we outline the requirement for large standardized trial datasets, greater scrutiny of optimal ctDNA collection time points and assay thresholds, and consideration of regulatory body guidelines and patient opinions. In particular, clinically meaningful changes in plasma ctDNA abundance are likely to differ by cancer type and therapy class and must be assessed before ctDNA can be considered a potential pan-cancer response evaluation biomarker. Despite the need for additional data, minimally invasive on-treatment ctDNA measurements hold promise to build upon existing response assessments such as RECIST and offer opportunities for developing novel early endpoints for modern clinical trials.