This study was performed to evaluate the outcomes of advanced radiotherapy techniques, including image-guided adaptive brachytherapy (IGABT), in International Federation of Gynecology and Obstetrics (FIGO) stage IVA cervical cancer patients with adjacent organ infiltration. A further aim was to identify prognostic factors influencing overall survival (OS) and local control (LC) in these patients, with a particular focus on toxicity and patient-reported outcomes (PROs).

This retrospective, single-center study included 31 patients with FIGO stage IVA cervical cancer treated with definitive chemoradiotherapy between 2010 and 2020. All 31 patients underwent external-beam radiotherapy (EBRT), with concurrent cisplatin-based chemotherapy (CTX) administered in 25 cases and additional high-dose-rate brachytherapy (BT) performed in 24 cases. Treatment-related adverse events were categorized in accordance with the Common Terminology Criteria for Adverse Events (CTCAE; version 5.0) [1]. PROs were evaluated using the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire version 3.0 (EORTC QLQ-C30), while sexual function was assessed through three specific questions adapted from the EORTC QLQ-BR23 module.

Median OS was estimated at 51.7 months, with 2‑ and 5‑year OS rates of 58.1 and 46.2%, respectively. Median progression-free survival (PFS) was 48.1 months (95% CI: 0-96.2 months), with 2‑ and 5‑year PFS rates of 52 and 37%. The 10-year LC probability was 70.4%, showing a significant association with improved OS (p = 0.0039). Eastern Cooperative Oncology Group (ECOG) performance status (p = 0.014) and nodal involvement were identified as prognostic factors. The estimated median OS was 108 months for patients treated with BT and 51.7 months for those without. Patients receiving six fractions or a cumulative BT dose of ≥ 24 Gy demonstrated improved 5‑year OS rates of 62.3%, although the difference was not statistically significant. Acute toxicities were reported in 83.9% of patients, primarily grades 1-2, with severe complications such as fistula formation occurring in 16.1%. Late toxicities, predominantly affecting the gastrointestinal and urogenital systems, were observed in 45.2% of patients. Patient-reported outcomes indicated mild to moderate impairments of quality of life, with fatigue and gastrointestinal symptoms being the most frequently reported issues.

Advanced radiotherapy, particularly IGABT, achieves durable LC in patients with FIGO stage IVA cervical cancer, supporting its use as a cornerstone of curative-intent treatment. However, systemic progression remains a major challenge, highlighting the need for novel therapeutic strategies, including immunotherapy and liquid biopsy for treatment monitoring. Future prospective trials are essential to validate these findings and refine therapeutic protocols, particularly for high-risk subgroups. Ensuring equitable access to these advanced treatments is critical for improving global outcomes in cervical cancer care.

This is a report of biomarker analysis for sunvozertinib, a leading epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor (TKI) targeting EGFR exon 20 insertion mutation (exon20ins) non-small cell lung cancer (NSCLC). There is a positive correlation between positive EGFR exon20ins in plasma circulating tumor DNA (ctDNA) and advanced disease. Shorter progression-free survival and lower objective response rate (45.8% vs. 68.0%) were observed in patients with positive EGFR exon20ins compared to those with negative status. Droplet digital PCR analysis showed that the EGFR exon20ins allele in ctDNA decreased over time in 85.7% of patients, with the earliest clearance occurred after 1 week of sunvozertinib treatment. Acquired EGFR C797S is identified as a potential on-target resistance mutation to sunvozertinib. Finally, efforts are undertaken to investigate therapeutic approaches that aim to overcome the putative acquired resistance to sunvozertinib.

Circulating immune cells play a crucial role in the anti-tumour immune response, yet the systemic immune system in metastatic breast cancers is not fully characterised. Investigating the cellular and molecular changes in peripheral blood mononuclear cells (PBMCs) from breast cancer patients could elucidate the role of circulating immune cells in metastasis and aid in identifying biomarkers for disease burden and progression.

In this study, we characterised the systemic immune landscape associated with varying levels of metastatic burden by analysing the single-cell transcriptomes of PBMCs from breast cancer patients and healthy controls. Our research focused on identifying changes in immune cell composition, transcriptional programs, and immune-cell communication networks linked to metastatic burden. Additionally, we compared these PBMC features onto a single-cell atlas of primary breast tumours to study corresponding traits in tumour-infiltrating immune cells.

In metastatic breast cancer, PBMCs exhibit a significant downregulation of the adaptive immune system and a decreased number and activity of unconventional T cells, such as γδ T cells. Additionally, metastatic burden is associated with impaired cell communication pathways involved in immunomodulatory functions. We also identified a gene signature derived from myeloid cells shared between tumour immune infiltrates and circulating immune cells in breast cancer patients.

Our study provides a comprehensive single-cell molecular profile of the peripheral immune system in breast cancer, offering a valuable resource for understanding metastatic disease in terms of tumour burden. By identifying immune traits linked to metastasis, we have unveiled potential new biomarkers of metastatic disease.

Chemometrics represents a potent tool for optimizing the experimental setup and subsequently boosting the performance of analytical methods. In particular, design of experiments (DoE) allows the experimental conditions to be optimized with high accuracy and a lower number of experiments when compared with the classical univariate approach, also known as one variable at a time (OVAT), which provides only a partial understanding on how factors affect the response. In this work, DoE was exploited, specifically a D-optimal design was used, to improve the analytical performance of a hybridization-based paper-based electrochemical biosensor, taking as target of the study the miRNA-29c (miR-29c) that is related to triple negative breast cancer. The sensing platform is composed of six variables to be optimized, including both those related to the sensor's manufacture (i.e., gold nanoparticles, immobilized DNA probe) and those related to the working conditions (i.e., ionic strength, probe-target hybridization, electrochemical parameters). The adoption of DoE allowed us to optimize the device using only 30 experiments with respect to the 486 that would have been required with the OVAT approach, and as a consequence of the more accurate optimal conditions that have been reached, the detection of miRNA was more sensitive and repeatable when compared with previous data reported using the univariate approach for optimization, leading to a 5-fold limit of detection (LOD) improvement toward miRNA. It confirms that chemometrics might be considered a fundamental tool to be used in the development of various kinds of sensors and biosensors.

Next-generation sequencing (NGS) has emerged as a pivotal technology in the field of oncology, transforming the approach to cancer diagnosis and treatment. This paper provides a comprehensive overview of the integration of NGS into clinical settings, emphasizing its significant contributions to precision medicine. NGS enables detailed genomic profiling of tumors, identifying genetic alterations that drive cancer progression and facilitating personalized treatment plans targeting specific mutations, thereby improving patient outcomes. This capability facilitates the development of personalized treatment plans targeting specific mutations, leading to improved patient outcomes and the potential for better prognosis. The application of NGS extends beyond identifying actionable mutations; it is instrumental in detecting hereditary cancer syndromes, thus aiding in early diagnosis and preventive strategies. Furthermore, NGS plays a crucial role in monitoring minimal residual disease, offering a sensitive method to detect cancer recurrence at an early stage. Its use in guiding immunotherapy by identifying biomarkers that predict response to treatment is also highlighted. Ethical issues related to genetic testing, such as concerns around patient consent and data privacy, are also important considerations that need to be addressed for the broader implementation of NGS. These include the complexities of data interpretation, the need for robust bioinformatics support, cost considerations, and ethical issues related to genetic testing. Addressing these challenges is essential for the widespread adoption of NGS. Looking forward, advancements such as single-cell sequencing and liquid biopsies promise to further enhance the precision of cancer diagnostics and treatment. This review emphasizes the transformative impact of NGS in oncology and advocates for its incorporation into routine clinical practice to promote molecularly driven cancer care.

Midline structures in the central nervous system include the thalamus, brainstem, and spinal cord. Within the midline tumors, Diffuse midline gliomas (DMGs) and diffuse intrinsic pontine gliomas (DIPG) have a poor prognosis. DMGs are inclusive of all diffuse intrinsic pontine gliomas (DIPG), previously usually used for only pontine gliomas, to emphasize that these lesions are not solely centered in the pons/brainstem. In this retrospective review, we aim to report the frequency and outcomes of midline gliomas amongst all midline tumors in a tertiary care setup.

Data were collected retrospectively from the medical records at Aga Khan University Hospital between 2013 and 2023. All patients aged 18 and younger with tumors in midline locations were reviewed, and 102 patients were included. A few tumor samples were also sent to SickKids, Toronto, for molecular testing.

Our cohort represents 102 patients with midline tumors, a median age of 11 years (interquartile range (IQR): 7.75-15 years), and a similar male-to-female ratio. Most patients presented with limb weakness and headache (median duration: 1.5 months, IQR: 1-4 months). The most common site of tumors was the brainstem, followed by the spine and thalamus. Sixty-six patients had surgery: 2 DIPGs, 15 low-grade gliomas, 13 ependymomas, 8 high-grade gliomas, 12 diffuse midline glioma, and 16 other tumors were identified. All of the patients diagnosed with DMG had H3K27 alteration on immunohistochemistry. Thirty-six patients were diagnosed via radiology: 33 DIPG and 3 tectal plate glioma. Only 10 patients received chemotherapy, and radiation therapy was given to 24 patients. Overall survival for all midline tumors was 53.9%, with 47 events.

Our study depicts poor survival outcomes at one year of patients diagnosed with DMG (16.7%) and DIPG (14.3%) amongst all midline tumors, regardless of radiation therapy or concurrent chemoradiotherapy. To improve the care and survival of all midline tumors, there is a dire need for affordable diagnostic techniques in specialized centers across low- and middle-income countries.

Liquid biopsy gained significant interest in the area of cancer management. This study aims to evaluate the effectiveness of molecular testing using ctDNA (circulating tumor DNA) to; detect genetic alterations, screen for abnormalities, identify mutations associated with treatment sensitivity or resistance and guide therapy decision for several types of cancer in patients with metastasis. A total of 85 samples were collected from 74 patients recruited at our center, as part of their routine clinical follow-up. 17 different cancer types were analyzed. Genetic testing was conducted in patients with metastasis after failure of standard treatments. Sequencing was conducted in plasma-ctDNA samples; and when it was possible on the tumor tissue as well. Our analysis revealed that 88% (65 patients) of patients were eligible for treatment guidance using liquid biopsy. Among them, 64% (47 patients) received an FDA-approved drug, and treatment decisions were based on molecular testing using ctDNA. Somatic gene mutations were detected in 89% (66 patients) of the patients tested; 81% (60 patients) of patients had at least two mutations, 8% (6 patients) had only one mutation and 11% (8 patients) had no detected mutations. Interestingly, among the genes tested, BRCA2, EGFR, MSH6, and NF1 were the most frequently mutated in our patients. Our study highlights the potential benefits of personalized medicine through a non-invasive genetic testing across patients with metastasis regardless of the cancer types. Moreover, our study identified the frequent occurrence of specific gene mutations across various types of cancer, which paves the way for considering targeted therapies that could be applicable to multiple cancer types, rather than being restricted to just a few.

Biological microenvironment detection is crucial for deciphering the mechanisms underlying malignant progression and predicting the treatment efficacy of diseases. Nevertheless, only very limited progress has been made toward non-invasive and quantitative detection of microenvironment abnormal factors, let alone with clinically compatible imaging modalities. Herein, a smart nuclear medicine probe is proposed, innovatively designed for quantitative visualization of glutathione (GSH) in vivo. This probe contains a disulfide bond that links two molecular segments labeled with 125I and 177Lu, respectively. Upon systemic delivery, the probe preferentially accumulates in the liver, where GSH cleaves it into two fragments with completely different metabolic fates: one retained at the response site and the other rapidly excreted. This unique feature provides an opportunity to use the 177Lu/125I signal ratio to non-invasively characterize the GSH concentration in vivo, enabling highly sensitive quantification of GSH that is strongly associated with many hepatic diseases. Moreover, the strategy also provides a reliable method for the quantitative visualization of GSH levels in tumors. It is thus believed the current study provides a groundbreaking method for non-invasively and quantitatively revealing disease-related microenvironment factors, not limited to GSH, in vivo.

Liquid biopsies represent a promising and minimally invasive approach to diagnosing and monitoring cancer. In recent years, studies across a multitude of solid organ malignancies have suggested the clinical utility of biomarkers such as circulating tumor DNA (ctDNA). Particular attention has been given to serial assessment of such biomarkers in an effort to detect minimal residual disease (MRD), in order to predict which patients may be at highest risk of relapse following curative-intent surgical or medical intervention. Such investigations are particularly relevant to sarcomas, which are highly heterogeneous malignancies and commonly develop treatment resistance. While preliminary research described herein is promising, there remain key barriers to widespread adoption of liquid biopsy in sarcoma, including the lack of standardized detection methods, high cost, and the need for large, prospective studies to validate their clinical utility. Given the high level of interest in liquid biopsy in the biomedical community, it is plausible such obstacles may be overcome in the near future. With such advancements, one can anticipate that liquid biopsies may become a key tool in the sarcoma oncologists armamentarium, and offer a path toward improved outcomes for patients with sarcoma.

Early-onset gastric cancer (EOGC) is a lethal malignancy. It differs from late-onset gastric cancer (LOGC) in clinical and molecular characteristics. The current strategies for EOGC detection have certain limitations in diagnostic performance due to the rising trend in EOGC.

We developed a liquid biopsy signature for EOGC detection.

We use a systematic discovery approach by analysing genome-wide transcriptomic profiling data from EOGC (n=43), LOGC (n=31) and age-matched non-disease controls (n=37) tissue samples. An extracellular vesicle-derived long non-coding RNA (EV-lncRNA) signature was identified in blood samples from a training cohort (n=299), and subsequently confirmed by qPCR in two external validation cohorts (n=462 and n=438), a preoperative/postoperative cohort (n=66) and a gastrointestinal tumour cohort (n=225).

A three EV-lncRNA (NALT1, PTENP1 and HOTTIP) liquid biopsy signature was developed for EOGC detection with an area under the receiver operating characteristic curve (AUROC) of 0.924 (95% CI 0.889 to 0.953). This EV-lncRNA signature provided robust diagnostic performance in two external validation cohorts (Xi'an cohort: AUROC, 0.911; Beijing cohort: AUROC, 0.9323). Furthermore, the EV-lncRNA signature reliably identified resectable stage EOGC patients (stage I/II) and demonstrated better diagnostic performance than traditional GC-related biomarkers in distinguishing early-stage EOGC (stage I) from precancerous lesions. The low levels of this biomarker in postsurgery and other gastrointestinal tumour plasma samples indicated its GC specificity.

The newly developed EV-lncRNA signature effectively identified EOGC patients at a resectable stage with enhanced precision, thereby improving the prognosis of patients who would have otherwise missed the curative treatment window.

Circulating tumor DNA (ctDNA) is nowadays considered a robust source to search for druggable tumoral genetic alterations, and in some specific settings liquid biopsy (LB) is already part of the diagnostics scenario and it has successfully implemented in the everyday practice. Three strengths make LB an extraordinary tool: i) to represent the complex molecular mosaicism that characterizes spatially heterogeneous malignancies; ii) to monitor in real-time the tumoral molecular landscape (i.e. to depict the longitudinal/temporal tumor evolution); iii) to ensure molecular profiling even in those cases in which tissue sampling is not feasible or not adequate. This review provides a snapshot of the current state of the art concerning ctDNA assay utility in gastric cancer (GC), testing its robustness as marker and seeking to understand the reasons for the delay in its application in clinical practice.

The quantification of circulating tumour DNA (ctDNA) in blood enables non-invasive surveillance of cancer progression. Here we show that a deep-learning model can accurately quantify ctDNA from the density distribution of cell-free DNA-fragment lengths. We validated the model, which we named 'Fragle', by using low-pass whole-genome-sequencing data from multiple cancer types and healthy control cohorts. In independent cohorts, Fragle outperformed tumour-naive methods, achieving higher accuracy and lower detection limits. We also show that Fragle is compatible with targeted sequencing data. In plasma samples from patients with colorectal cancer, longitudinal analysis with Fragle revealed strong concordance between ctDNA dynamics and treatment responses. In patients with resected lung cancer, Fragle outperformed a tumour-naive gene panel in the prediction of minimal residual disease for risk stratification. The method's versatility, speed and accuracy for ctDNA quantification suggest that it may have broad clinical utility.

Ovarian cancer, the most deadly gynecologic malignancy, is often resistant to conventional antitumor therapy due to various factors such as severe side effects, unexpected recurrence, and significant tissue damage. The limitations of current treatments and the resistance of invasive tumor cells contribute to these challenges. Hydrogel therapy has recently emerged as a potential treatment option for ovarian cancer, offering advantages such as controllability, biocompatibility, high drug loading capacity, prolonged drug release, and responsiveness to specific stimuli. Hence, the utilization of biodegradable hydrogels as carriers for chemotherapeutic agents has emerged as a significant concern in the field. Injectable hydrogel-based drug delivery systems, in particular, have demonstrated superior efficacy compared to traditional systemic chemotherapy for cancer treatment. The pliability of hydrogel therapy allows for access to anatomical regions that may be challenging for surgical intervention. This review article examines recent advancements in the application of hydrogels for diagnosing and treating ovarian cancer, while also proposing a novel direction for the use of hydrogel technology in this context. The objective of this article is to offer a novel point of reference and serve as a source of inspiration for the advancement of more precise and individualized cancer therapies.

Heterogeneities among tumor cells significantly contribute towards cancer progression and therapeutic inefficiency. Hence, understanding the nature of cancer through liquid biopsies and isolation of circulating tumor cells (CTCs) has gained considerable interest over the years. Microfluidics has emerged as one of the most popular platforms for performing liquid biopsy applications. Various label-free and labeling techniques using microfluidic platforms have been developed, the majority of which focus on CTC isolation from normal blood cells. However, sorting and profiling of various cell phenotypes present amongst those CTCs is equally important for prognostics and development of personalized therapies. In this review, firstly, we discuss the biophysical and biochemical heterogeneities associated with tumor cells and CTCs which contribute to cancer progression. Moreover, we discuss the recently developed microfluidic platforms for sorting and profiling of tumor cells and CTCs. These techniques are broadly classified into biophysical and biochemical phenotyping methods. Biophysical methods are further classified into mechanical and electrical phenotyping. While biochemical techniques have been categorized into surface antigen expressions, metabolism, and chemotaxis-based phenotyping methods. We also shed light on clinical studies performed with these platforms over the years and conclude with an outlook for the future development in this field.

The utility of circulating tumor DNA (ctDNA) analysis has not been well-established for disease detection and monitoring of childhood cancers, especially leukemias. We developed PeCan-Seq, a deep sequencing method targeting diverse somatic genomic variants in cell-free samples in childhood cancer. Plasma samples were collected at diagnosis from 233 children with hematologic, solid and brain tumors. All children with hematologic malignancy (n = 177) had detectable ctDNA at diagnosis. The median ctDNA fraction was 0.77, and 97% of 789 expected tumor variants were identified, including sequence mutations, copy number variations, and structural variations responsible for oncogenic fusions. In contrast, ctDNA was detected in 19 of 38 solid tumor patients and 1 of 18 brain tumor patients. Somatic variants from ctDNA were correlated with minimal residual disease levels as determined by flow cytometry in serial plasma samples from patients with B-cell acute lymphoblastic leukemia (B-ALL). We showcase multi-tumor detection by ctDNA analysis for a patient with concurrent B-ALL and neuroblastoma. In conclusion, PeCan-seq sensitively identified heterogeneous ctDNA alterations from 1 mL plasma for childhood hematologic malignancies and a subset of solid tumors. PeCan-seq provides a robust, non-invasive approach to augment comprehensive genomic profiling at diagnosis and mutation-specific detection during disease monitoring.

Semaglutide, a glucagon-like peptide-1 (GLP-1) receptor agonist, is a widely used drug for the treatment of type 2 diabetes that offers significant cardiovascular benefits.

This review systematically examines the proteomic and metabolomic indicators associated with the cardiovascular effects of semaglutide. A comprehensive literature search was conducted to identify relevant studies. The review utilizes advanced analytical technologies such as mass spectrometry and nuclear magnetic resonance (NMR) to investigate the molecular mechanisms underlying the effects of semaglutide on insulin secretion, weight control, anti-inflammatory activities and lipid metabolism. These "omics" approaches offer critical insights into metabolic changes associated with cardiovascular health. However, challenges remain such as individual variability in expression, the need for comprehensive validation and the integration of these data with clinical parameters. These issues need to be addressed through further research to refine these indicators and increase their clinical utility.

Future integration of proteomic and metabolomic data with artificial intelligence (AI) promises to improve prediction and monitoring of cardiovascular outcomes and may enable more accurate and effective management of cardiovascular health in patients with type 2 diabetes. This review highlights the transformative potential of integrating proteomics, metabolomics and AI to advance cardiovascular medicine and improve patient outcomes.

Previously, we demonstrated that changes in circulating tumor DNA (ctDNA) are promising biomarkers for early response prediction (ERP) to immune checkpoint inhibitors (ICIs) in metastatic urothelial cancer (mUC). In this study, we investigated the value of whole-blood immunotranscriptomics for ERP-ICI and integrated both biomarkers into a multimodal model to boost accuracy.

Blood samples of 93 patients were collected at baseline and after 2-6 weeks of ICI for ctDNA (n = 88) and immunotranscriptome (n = 79) analyses. ctDNA changes were dichotomized into increase or no increase, the latter including patients with undetectable ctDNA. For RNA model development, the cohort was split into discovery (n = 29), test (n = 29), and validation sets (n = 21). Finally, RNA- and ctDNA-based predictions were integrated in a multimodal model. Clinical benefit (CB) was defined as progression-free survival beyond 6 months.

Sensitivity (SN) and specificity (SP) of ctDNA increase for predicting non-CB (N-CB) was 59% and 92%, respectively. Immunotranscriptome analysis revealed upregulation of T cell activation, proliferation, and interferon signaling during treatment in the CB group, in contrast with N-CB patients. Based on these differences, a 10-gene RNA model was generated, reaching an SN and SP of 73% and 79%, respectively, in the test and 67% and 67% in the validation set for predicting N-CB. Multimodal model integration led to superior performance, with an SN and SP of 79% and 100%, respectively, in the validation cohort.

The combination of whole-blood immunotranscriptome and ctDNA in a multimodal model showed promise for ERP-ICI in mUC and accurately identified patients with N-CB.

Eurostars grant E! 114908 - PRECISE, Paul Speth Foundation (Bullseye project).

Renal cell carcinoma (RCC) is a common malignancy, with patients frequently diagnosed at an advanced stage due to the absence of sufficiently sensitive detection technologies, significantly compromising patient survival and quality of life. Advances in cell-free DNA (cfDNA) methylation profiling using liquid biopsies offer a promising non-invasive diagnostic option, but robust biomarkers for early detection are current not available. This study aimed to identify methylation biomarkers for RCC and establish a DNA methylation signature-based prognostic model for this disease.

High-throughput methylation sequencing was performed on peripheral blood samples obtained from 49 primarily Stage I RCC patients and 44 healthy controls. Comparative analysis and Least Absolute Shrinkage and Selection Operator (LASSO) regression methods were employed to identify RCC methylation signatures.Subsequently, methylation markers-based diagnostic and prognostic models for RCC were independently trained and validated using random forest and Cox regression methodologies, respectively.

Comparative analysis revealed 864 differentially methylated CpG islands (DMCGIs), 96.3% of which were hypermethylated. Using a training set from The Cancer Genome Atlas (TCGA) dataset of 443 early-stage RCC tumors and matched normal tissues, we applied LASSO regression and identified 23 methylation signatures. We then constructed a random forest-based diagnostic model for early-stage RCC and validated the model using two independent datasets: a TCGA set of 460 RCC tumors and controls, and a blood sample set from our study of 15 RCC cases and 29 healthy controls. For Stage I RCC tissue, the model showed excellent discrimination (AUC-ROC: 0.999, sensitivity: 98.5%, specificity: 100%). Blood sample validation also yielded commendable results (AUC-ROC: 0.852, sensitivity: 73.9%, specificity: 89.7%). Further analysis using Cox regression identified 7 of the 23 DMCGIs as prognostic markers for RCC, allowing the development of a prognostic model with strong predictive power for 1-, 3-, and 5-year survival (AUC-ROC > 0.7).

Our findings highlight the critical role of hypermethylation in RCC etiology and progression, and present these identified biomarkers as promising candidates for diagnostic and prognostic applications.

Large-scale, pan-cancer analysis is enabled by data driven knowledge bases that link tumor molecular profiles with phenotypes. A debilitating cancer-related phenotype is skeletal muscle loss, or cachexia, which occurs partly from tumor products secreted into circulation. Using the LinkedOmicsKB knowledge base assembled from the Clinical Proteomics Tumor Analysis Consortium proteogenomic analysis, along with catalogs of human secretome proteins, ligand-receptor pairs and molecular signatures, we sought to identify candidate pan-cancer proteins secreted to blood that could regulate skeletal muscle phenotypes in multiple solid cancers. Tumor proteins having significant pan-cancer associations with muscle were referenced against secretome proteins secreted to blood from the Human Protein Atlas, then verified as increased in paired tumor vs. normal tissues in pan-cancer manner. This workflow revealed seven secreted proteins from cancers afflicting kidneys, head and neck, lungs and pancreas that classified as protein-binding activity modulator, extracellular matrix protein or intercellular signaling molecule. Concordance of these biomarkers with validated molecular signatures of cachexia and senescence supported relevance to muscle and cachexia disease biology, and high tumor expression of the biomarker set associated with lower overall survival. In this article, we discuss avenues by which skeletal muscle and cachexia may be regulated by these candidate pan-cancer proteins secreted to blood, and conceptualize a strategy that considers them collectively as a biomarker signature with potential for refinement by data analytics and radiogenomics for predictive testing of future risk in a non-invasive, blood-based panel amenable to broad uptake and early management.

Breast cancer CTCs have recently been recognized as an emerging biomarker for liquid biopsy of breast cancer. In this work, based on two-dimensional (2D) noble metal PtCo@rGO nanozymes and Au@CNTs bioconjugates, a novel electrochemiluminescence (ECL) cytosensor was developed in order to detect breast cancer CTCs (MCF-7) ultrasensitively.

The PtCo@rGO nanozymes possessed large specific surface area and high efficiency peroxidase-like activity, which can be used as nanocarriers to anchor and catalyze luminol ECL emission efficiently. Moreover, the PtCo@rGO nanozymes have fractal nanostructures similar to that of CTCs and can capable of enhancing the adhesion of MCF-7 when assembled together with aptamers containing HS-modified epithelial specific cell adhesion molecules (EpCAM, S1). Importantly, the S1/Au@CNTs bioconjugates loaded on the glassy carbon electrode (GCE) can effectively capture MCF-7 cells. Benefiting from the above-mentioned advantages, the ECL cytosensor constructed for MCF-7 cells detection performed well with a wide linear range (2-1 × 104 cells mL-1) and a low limit of detection (1 cells mL-1).

The designed ECL cytosensor could provide a promising platform for CTC-based liquid biopsy and have broad application prospects in breast cancer early diagnosis and prognostic monitoring.

In principle, the measurement of mechanical property differences between cancer cells and their benign counterparts enables the detection, diagnosis, and classification of diseases. Despite the existence of various mechanophenotyping methods, the ability to perform high-throughput single-cell deformability measurements on liquid and/or solid tissue biopsies remains an unmet challenge within clinical settings. To address this issue, we present an ultrahigh-throughput viscoelastic microfluidic platform able to measure the mechanical properties of single cells at rates of up to 100,000 cells per second (and up to 10,000 cells per second in real time). To showcase the utility of the presented platform in clinical scenarios, we perform single-cell phenotyping of both liquid and solid tumor biopsies, cytoskeletal drug analysis, and identification of malignant lymphocytes in peripheral blood samples. Our viscoelastic microfluidic methodology offers opportunities for high-throughput, label-free single-cell analysis, with diverse applications in clinical diagnostics and personalized medicine.

Liquid biopsies have been receiving tremendous attention for their potential to reshape cancer management. Though current studies of cancer liquid biopsy primarily focus on applying biochemical assays to characterize the genetic/molecular profiles of circulating tumor cells (CTCs) and their secondary products shed from tumor sites in bodily fluids, delineating the nanomechanical properties of tumor-associated materials in liquid biopsy specimens yields complementary insights into the biology of tumor dissemination and evolution. Particularly, atomic force microscopy (AFM) has become a standard and versatile toolbox for characterizing the mechanical properties of living biological systems at the micro/nanoscale, and AFM has been increasingly utilized to probe the nanomechanical properties of various tumor-derived analytes in liquid biopsies, including CTCs, tumor-associated cells, circulating tumor DNA (ctDNA) molecules, and extracellular vesicles (EVs), offering additional possibilities for understanding cancer pathogenesis from the perspective of mechanobiology. Herein, the applications of AFM in cancer liquid biopsy are summarized, and the challenges and future directions of AFM as a nanomechanical analysis tool in cancer liquid biopsy towards clinical utility are discussed and envisioned.

Neuroendocrine neoplasms (NENs) arise from neuroendocrine cells in a wide variety of organs. One of the most affected disease sites is the gastrointestinal system, which originates the gastro-entero-pancreatic NENs (GEP-NENs), a heterogenous group of malignancies that are rapidly increasing in incidence. These tumors can be functioning, with secretory activity leading to identifiable clinical syndromes, or non-functioning, with no secretory activity but with local symptoms of tumor growth and metastasis. A limitation in biomarkers is a crucial unmet need in non-secretory NEN management, as clinical decision-making is made more difficult by obstacles in tumor classification, prognostic evaluation, assessment of treatment response and surveillance. The objective of this review is to present existing and novel biomarkers for NENs that can function as prognostic factors and monitor disease progression or regression longitudinally, with a special emphasis on innovative research into novel multianalyte biomarkers.

Current approaches for prostate cancer (PCa) diagnosis and risk stratification require greater accuracy. Extracellular vesicles and particles (EVPs) containing diverse cargos from parent cells are released into the extracellular microenvironment and play a critical role in intercellular communication. Accumulating evidence demonstrates that EVPs are emerging as a promising focus for the exploration of cancer biomarkers and therapeutic targets. However, the precise categorisation and nomenclature of EVP subpopulations remains challenging due to their compositional complexity, inherent heterogeneity in molecular composition, and structure. The recent identification of two novel non-vesicular extracellular particle subtypes, exomeres and supermeres, has altered our understanding of the distinct subpopulations of EVPs and their roles in biological and physiological processes. Here, we discuss recent advances in the field of EVPs, describe characteristics of EVP subpopulations, focus on the application and potential of EVPs in PCa diagnosis and risk stratification by liquid biopsy, and highlight the major challenges and prospects of EVP research in PCa area.

Mucin 1 (MUC1) is frequently overexpressed in various cancers and is essential for early cancer detection. Current methods to detect MUC1 are expensive, time-consuming, and require skilled personnel. Therefore, developing a simple, sensitive, highly selective MUC1 detection sensor is necessary. In this study, we proposed a novel "signal-on-off" strategy that, in the presence of MUC1, synergistically integrates catalytic hairpin assembly (CHA) with DNA tetrahedron (Td)-based nonlinear hybridization chain reaction (HCR) to enhance the immobilization of electrochemically active methylene blue (MB) on magnetic nanoparticles (MNP), marking the MB signal "on". Concurrently, the activation of CRISPR-Cas12a by isothermal amplification products triggers the cleavage of single-stranded DNA (ssDNA) at the electrode surface, resulting in a reduction of MgAl-LDH@Fc-AuFe-MIL-101 (containing ferrocene, Fc) on the electrode, presenting the "signal-off" state. Both MB and MgAl-LDH@Fc-AuFe-MIL-101 electrochemical signals were measured and analyzed. Assay parameters were optimized, and sensitivity, stability, and linear range were assessed. Across a concentration spectrum of MUC1 spanning from 10 fg/mL to 100 ng/mL, the MB and MgAl-LDH@Fc-AuFe-MIL-101 signals were calibrated with each other, demonstrating a "signal-on-off" dual electrochemical signaling pattern. This allows for the precise and quantitative detection of MUC1 in clinical samples, offering significant potential for medical diagnosis.

Previous studies mainly concentrate on neoadjuvant chemotherapy (NACT) for delivery delay in FIGO Stage IB1-IIIB cervical cancer during pregnancy to prevent early preterm delivery while not affecting maternal outcome.

Here, we described two pregnant patients with FIGO Stage IIIC cervical cancer about their diagnosis, treatment, and outcome. Both patients underwent cesarean delivery, left enlarged lymph node dissection, and longitudinal monitoring by circulating tumor DNA. Our study suggested that pregnant patient was completely response to NACT, which was confirmed by ctDNA monitoring, followed by left pelvic enlarged lymph node dissection during cesarean section and adjuvant chemoradiotherapy postpartum. The infant grew normally, without any evidence of chemotherapy-related side effects after delivery.

In pregnant women with advanced cervical cancer, longitudinal ctDNA monitoring might be able to evaluate maternal response to NACT and confirm if delivery delay to optimize fetal outcome would compacting the maternal outcomes or not. Cervical cancer may not transmit across the placental barrier and so it is safe for delayed delivery until fetal maturity in utero during pregnancy.

Currently, no biomarkers are available to identify resistance to androgen-deprivation therapies (ADT) in men with hormone-naive prostate cancer. Since 5-hydroxymethylcytosines (5hmC) in gene body are associated with gene activation, in this study, we evaluated whether 5hmC signatures in cell-free DNA (cfDNA) predicts early resistance to ADT.

We collected a total of 139 serial plasma samples from 55 prostate cancer patients receiving ADT at three time points including baseline (prior to initiating ADT, N=55), 3-month (after initiating ADT, N=55), and disease progression (N=15) within 24 months or 24-month if no progression was detected (N=14). To quantify 5hmC abundance across the genome, we used selective chemical labeling sequencing and mapped sequence reads to individual genes. Differential methylation analysis in baseline samples identified significant 5hmC difference in 1,642 of 23,433 genes between patients with and without progression (false discovery rate, FDR<0.1). Patients with disease progression showed significant 5hmC enrichments in multiple hallmark gene sets with androgen responses as top enriched gene set (FDR=1.19E-13). Interestingly, this enrichment was driven by a subgroup of patients featuring a significant 5hmC hypermethylation in the gene sets involving AR , FOXA1 and GRHL2 . To quantify overall activities of these gene sets, we developed a gene set activity scoring algorithm and observed significant association of high activity scores with poor progression-free survival (P<0.05). Longitudinal analysis showed that the high activity scores were significantly reduced after 3-months of initiating ADT (P<0.0001) but returned to higher levels when the disease was progressed (P<0.05).

This study demonstrates that 5hmC-based activity scores from gene sets involved in AR , FOXA1 and GRHL2 may be used as biomarkers to determine early treatment resistance, monitor disease progression, and potentially identify patients who would benefit from upfront treatment intensification.

Aim: Advances in circulating tumor DNA (ctDNA) analysis for diffuse large B-cell lymphoma (DLBCL) have prompted the evaluation of its utility in other non-Hodgkin lymphomas (NHLs), leading to significant insights into its potential applications.Methods: We retrospectively studied paired plasma and tissue/bone marrow biopsies of 203 non-DLBCL NHLs [87 follicular lymphomas (FL), 64 mantle cell lymphomas (MCL), 30 chronic lymphocytic leukemia/small lymphocytic lymphomas (CLL/SLL) and 22 marginal zone lymphomas (MZL)]. Genomic profiling was performed using a targeted next generation sequencing panel (Hemasalus™). Longitudinal analyses were performed to explore plasma ctDNA utility in disease monitoring.Results: High plasma ctDNA detection rates were observed across NHL subtypes (FL: 88.5%, MCL: 90.6%, CLL/SLL: 100%, MZL: 68.2%), with high concordance of actionable mutations (FL: 87.4%, MCL: 93.8%, CLL/SLL: 93.3%, MZL: 81.8%) and multiple genetic aberrations exclusively identified in plasma. Particularly, IGH-BCL2 and IGH-CCND1 fusions were concordant between plasma and tumor biopsies in FLs (91.1%) and MCLs (91.3%), respectively. Longitudinal data demonstrated that ctDNA clearance correlated with complete response but ctDNA increases preceded radiological relapses.Conclusion: ctDNA exhibited high concordance with tumor biopsy in detecting genetic aberrations and demonstrated potential as a promising noninvasive approach to disease surveillance in non-DLBCL NHLs.

In the era of precision oncology, the management of triple-negative breast cancer (TNBC) is rapidly changing and becoming more complicated with a variety of chemotherapy, immunotherapy, and targeted treatment options. Currently, TNBC treatment is based on prognostic and predictive factors including immunohistochemical biomarkers [e.g. programmed death-ligand 1 (PD-L1)] and germline BRCA mutations. Given the current limitation of existing biomarkers, liquid biopsies may serve as clinically useful tools to determine treatment efficacy and response in both the (neo)adjuvant and metastatic settings, for detecting early relapse, and for monitoring clonal evolution during treatment. In this review, we comprehensively summarize current and future liquid biopsy applications. Specifically, we highlight the role of circulating tumor cell characterization, circulating tumor DNA, and other preclinical liquid biopsy technologies including circulating exosomes, RNA liquid biopsy, and circulating immune-based biomarkers. In the near future, these biomarkers may serve to identify early disease relapse, therapeutic targets, and disease clonality for patients with TNBC in the clinical setting.

The assessment of ctDNA has emerged as a minimally invasive avenue for molecular diagnosis and real-time tracking of tumor progression in NSCLC. However, the evaluation of ctDNA by amplicon-based NGS has been not endorsed by all the healthcare systems and remains to be fully integrated into clinical routine practice. To compare tissue single-gene with plasma multiplexed testing, we retrospectively evaluated 120 plasma samples from 12 consecutive patients with advanced non-squamous NSCLC who were part of a prospective study enrolling treatment-naïve patients and in which tissue samples were evaluated using a single-gene testing approach. While the plasma ctDNA detection of EGFR and BRAF mutations had an acceptable level of concordance with the archival tissue (85%), discordance was seen in all the patients in whom ALK alterations were only detected in tissue samples. Among six responders and six non-responders, early ctDNA mutant allelic frequency (MAF) reduction seemed to predict radiologic responses and longer survival, whereas increasing MAF values with the emergence of co-mutations like BRAFV600E, KRASG12V or TP53M237I seemed to be an early indicator of molecular and radiologic progression. This report using an amplicon-based NGS assay on ctDNA underscores the real-life need for plasma and tissue genotyping as complementary tools in the diagnostic and therapeutic decision-making process.

The standard of care for locally advanced non-small-cell lung cancer (NSCLC) is either surgery combined with chemotherapy pre- or postoperatively or concurrent chemotherapy and radiotherapy. However, older and frail patients may not be candidates for surgery and chemotherapy due to the high mortality risk and are frequently referred to radiotherapy alone, which is better tolerated but carries a high risk of disease recurrence. Recently, immunotherapy with immune checkpoint inhibitors (ICIs) may induce a high response rate among cancer patients with positive programmed death ligand 1 (PD-L1) expression. Immunotherapy is also well tolerated among older patients. Laboratory and clinical studies have reported synergy between radiotherapy and ICI. The combination of ICI and radiotherapy may improve local control and survival for NSCLC patients who are not candidates for surgery and chemotherapy or decline these two modalities. The International Geriatric Radiotherapy Group proposes a protocol combining radiotherapy and immunotherapy based on the presence or absence of PD-L1 to optimize the survival of those patients.

In the era of precision oncology, identifying abnormal genetic and epigenetic alterations has transformed the way cancer is diagnosed, managed, and treated. 5-hydroxymethylcytosine (5hmC) is an emerging epigenetic modification formed through the oxidation of 5-methylcytosine (5mC) by ten-eleven translocase (TET) enzymes. DNA hydroxymethylation exhibits tissue- and cancer-specific patterns and is essential in DNA demethylation and gene regulation. Recent advancements in 5hmC detection methods and the discovery of 5hmC in cell-free DNA (cfDNA) have highlighted the potential for cell-free 5hmC as a cancer biomarker. This review explores the current and emerging techniques and applications of DNA hydroxymethylation in cancer, particularly in the context of cfDNA.

The primary reason for high mortality rates among cancer patients is metastasis, where tumor cells migrate through the bloodstream from the original site to other parts of the body. Recent advancements in technology have significantly enhanced our comprehension of the mechanisms behind the bloodborne spread of circulating tumor cells (CTCs). One critical process, DNA methylation, regulates gene expression and chromosome stability, thus maintaining dynamic equilibrium in the body. Global hypomethylation and locus-specific hypermethylation are examples of changes in DNA methylation patterns that are pivotal to carcinogenesis. This comprehensive review first provides an overview of the various processes that contribute to the formation of CTCs, including epithelial-mesenchymal transition (EMT), immune surveillance, and colonization. We then conduct an in-depth analysis of how modifications in DNA methylation within CTCs impact each of these critical stages during CTC dissemination. Furthermore, we explored potential clinical implications of changes in DNA methylation in CTCs for patients with cancer. By understanding these epigenetic modifications, we can gain insights into the metastatic process and identify new biomarkers for early detection, prognosis, and targeted therapies. This review aims to bridge the gap between basic research and clinical application, highlighting the significance of DNA methylation in the context of cancer metastasis and offering new avenues for improving patient outcomes.

Despite significant progress in the medical field, there is still a pressing need for minimal-invasive tools to assist with decision-making, especially in cases of polytrauma. Our team explored the potential of serum-derived large extracellular vesicles, so called microparticles/microvesicles/ectosomes, to serve as a supportive tool in decision-making in polytrauma situations. We focused on whether monocyte derived large EVs may differentiate between polytrauma patients with internal organ injury (ISS > 15) and those without. Thus, we compared our EV data to soluble biomarkers such as tumour necrosis factor alpha (TNF alpha) and Interleukin-8 (IL-8). From the blood of 25 healthy and 26 patients with polytrauma large EVs were isolated, purified, and characterized. TNF alpha and IL-8 levels were quantified. We found that levels of these monocyte derived large EVs were significantly higher in polytrauma patients with internal organ damage and correlated with the ISS. Interestingly, we also observed a decline in AnnV+CD14+ large EVs during normal recovery after trauma. Thus, inflammatory serological markers as TNF alpha and as IL-8 demonstrated an inability to discriminate between polytrauma patients with or without internal organ damage, such as spleen, kidney, or liver lacerations/ruptures. However, TNF and IL-8 levels were elevated in polytrauma cases overall when contrasted with healthy non-traumatic controls. These findings suggest that delving deeper into the potential of AnnV+ large EVs derived from monocytes could highly beneficial in the managment of polytrauma, potentially surpassing the efficacy of commonly used serum markers.