The approach of neoadjuvant therapy for breast cancer, which involves administering systemic treatment prior to primary surgery, has undergone substantial advancements in recent decades. This strategy is intended to reduce tumor size, thereby enabling less invasive surgical procedures and enhancing patient outcomes. This study presents a comprehensive bibliometric analysis of research trends in neoadjuvant therapy for breast cancer from 2009 to 2024. Using data extracted from the Web of Science Core Collection, a total of 3,674 articles were analyzed to map the research landscape in this field. The analysis reveals a steady increase in publication output, peaking in 2022, with the United States and China identified as the leading contributors. Key institutions, such as the University of Texas System and MD Anderson Cancer Center, have been instrumental in advancing the research on neoadjuvant therapy. The study also highlights the contributions of influential authors like Sibylle Loibl and Gunter von Minckwitz, as well as major journals such as the Journal of Clinical Oncology. Emerging research topics, including immunotherapy, liquid biopsy, and artificial intelligence, are gaining prominence and represent potential future directions for clinical applications. This bibliometric analysis provides critical insights into global research trends, key contributors, and future developments in the field of neoadjuvant therapy for breast cancer, offering a foundation for future research and clinical practice advancements.

Patients with pancreatic ductal adenocarcinoma (PDAC) commonly have occult metastatic dissemination and current standard staging methods have significant limitations in identifying these patients. A clinically available assay allows for the identification of mutant KRAS (mKRAS) circulating tumor DNA (ctDNA) from patient plasma and peritoneal fluid that may identify these patients and impact treatment decision making. We investigated the patterns of diagnostic and prognostic capabilities of mKRAS ctDNA in patients with localized PDAC.

Patients with non-metastatic PDAC were identified and underwent a full staging work-up during their first visit at our institution. Development of metastatic disease and long-term survival outcomes were assessed to compare between the mKRAS testing groups.

Between 2018 and 2022, 785 patients were evaluated. Among the 785 patients who underwent plasma mKRAS testing, 104 were mKRAS positive. Plasma mKRAS-positive patients were more likely to develop metastatic disease and had worse overall survival. In the 419 patients who underwent peritoneal mKRAS, 123 were mKRAS-positive and were more likely to harbor occult metastases or develop peritoneal rather than hematogenous metastases. For patients who underwent both baseline plasma and peritoneal mKRAS testing, any positive mKRAS test regardless of compartment was associated with worse outcomes.

Detection of mKRAS ctDNA in plasma and peritoneal fluid of patients with localized PDAC is not only feasible but also identifies those at high risk of metastatic progression and worse survival outcomes. It allows for better prognostication and can significantly impact subsequent treatment decisions, particularly in patients where an aggressive surgical approach is being considered.

Sensitive detection of circulating tumor cells (CTCs) from peripheral blood can serve as an effective tool in the early diagnosis and prognosis of cancer. Many methods based on modern object detectors were proposed in recent years for automatic abnormal cells detection in slide images. Although the modes of these methods can also be applied to the CTCs detection, several practical difficulties lead to suboptimal performance of them, such as accurate capture of CTCs in a large number of mixed cells and identification of CTCs and CTC-like cells with similar visual characteristics. Here, we develop a new cell-interacting and multi-correcting detector called CMD, and apply H&E-stained slide images to detect CTCs automatically for the first time. Specifically, the proposed method incorporates two task-oriented novel modules: (1) a self-attention module for aggregating feature interactions between cells and allowing the model to pay more attention to key abnormal cells, (2) a hard sample mining sampler for progressively correcting predictions of cells with ambiguous classification boundaries. Experiments conducted on a multi-center dataset of 1247 annotated slide images confirm the superiority of our method over state-of-the-art cell detection methods. The results of ablation experiment part also prove the effectiveness of two modules. The source codes of this paper are available at https://github.com/zx333445/CMD.

KRAS exon 2 mutations are highly prevalent in human malignancies, making them attractive targets for detection and monitoring in cell-free DNA (cfDNA) of cancer patients. Drop-off assays designed for digital polymerase chain reaction (ddPCR drop-off) span entire mutational hotspots and detect any mutated allele within the covered region, overcoming a major limitation of mutation-specific ddPCR assays. We therefore set out to develop a novel KRAS codon 12/13 ddPCR drop-off assay for the robust, highly sensitive and specific detection of KRAS exon 2 hotspot mutations in cfDNA.

We designed, optimized and extensively validated a KRAS codon 12/13 ddPCR drop-off assay. We compared assay performance to a commercially available KRAS multiplex assay. For clinical validation, we analyzed plasma samples collected from patients with KRAS-mutated gastrointestinal malignancies.

Limit of detection of the newly established ddPCR drop-off assay was 0.57 copies/µL, limit of blank was 0.13 copies/µ. The inter-assay precision (r2) was 0.9096. Our newly developed KRAS ddPCR drop-off assay accurately identified single nucleotide variants in 35/36 (97.2%) of circulating tumor DNA-positive samples from the patient validation cohort. Assay cross-validation showed that the newly established KRAS codon 12/13 ddPCR drop-off assay outperformed a commercially available KRAS multiplex ddPCR assay in terms of specificity. Moreover, the newly developed assay proved to be suitable for multiplexing with mutation-specific probes.

We developed and clinically validated a highly accurate ddPCR drop-off assay for KRAS exon 2 hot-spot detection in cfDNA with broad applicability for clinic and research.

While primary breast cancer (BC) is often effectively managed, metastasis remains the primary cause of BC-related fatalities. Gaps remain in our understanding of the mechanisms regulating cancer cell organotropism with predilection to specific organs. Unraveling mediators of site-specific metastasis could enhance early detection and enable more tailored interventions. Liquid biopsy represents an innovative approach in cancer involving the analysis of biological materials such as circulating tumor DNA and tumor-derived extracellular vesicles (EV) found in body fluids like blood or urine. This offers valuable insights for characterizing and monitoring tumor genomes to advance personalized medicine in metastatic cancers.

We performed in-depth analyses of EV cargo associated with BC metastasis using eight murine cell line models with distinct metastatic potentials and organotropism to the lung, the bone, the liver, and the brain. We characterized the secretome of these cells to identify unique biomarkers specific to metastatic sites.

Small EVs isolated from all cell lines were quantified and validated for established EV markers. Tracking analysis and electron microscopy revealed EV secretion patterns that differed according to cell line. Cell-free (cf)DNA and EV-associated DNA (EV-DNA) were detected from all cell lines with varying concentrations. We detected a TP53 mutation in both EV-DNA and cfDNA. Mass spectrometry-based proteomics analyses identified 698 EV-associated proteins, which clustered according to metastatic site. This analysis highlighted both common EV signatures and proteins involved in cancer progression and organotropism unique to metastatic cell lines. Among these, 327 significantly differentially enriched proteins were quantified with high confidence levels across BC and metastatic BC cells. We found enrichment of specific integrin receptors in metastatic cancer EVs compared to EVs secreted from non-transformed epithelial cells and matched tumorigenic non-metastatic cells. Pathway analyses revealed that EVs derived from parental cancer cells display a cell adhesion signature and are enriched with proteins involved in cancer signaling pathways.

Taken together, the characterization of EV cargo in a unique model of BC organotropism demonstrated that EV-DNA and EV proteomes were informative of normal and cancer states. This work could help to identify BC biomarkers associated with site-specific metastasis and new therapeutic targets.

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 tumor DNA is a critical biomarker in cancer diagnostics, but its accurate interpretation requires careful consideration of clonal hematopoiesis (CH), which can contribute to variants in cell-free DNA and potentially obscure true tumor-derived signals. Accurate detection of somatic variants of CH origin in plasma samples remains challenging in the absence of matched white blood cells sequencing. Here we present an open-source machine learning framework (MetaCH) which classifies variants in cfDNA from plasma-only samples as CH or tumor origin, surpassing state-of-the-art classification rates.

Colorectal cancer (CRC) is the third most common cancer worldwide and the second leading cause of cancer-related deaths. The current standard of care for patients with early-stage CRC includes surgical resection and, in selected patients, adjuvant chemotherapy. Circulating tumor DNA (ctDNA) testing is an important component of liquid biopsy, and with the development of testing technology, its value for clinical application has attracted widespread attention. The aim of this study was to help researchers review what has been achieved and better understand the direction of future research through bibliometric analysis.

We used the Web of Science Core Collection database to search for ctDNA in CRC-related articles published between 2014 - 2023. Bibliometric analyses of major keywords, authors, countries, institutions, literature and journals in the field were performed using CiteSpace and VOSviewer.

The number of publications in the field has continued to increase over the last decade. The United States has the highest number of publications, and Italian research scholars have made outstanding contributions. Cancers is the journal with the highest number of publications.

This study systematically summarizes the research findings in the field of ctDNA in CRC from 2014 to 2023 and describes the research hotspots and trends worldwide that can guide future research.

Small-cell lung cancer (SCLC) remains one of the deadliest cancers worldwide. Patients' survival remains poor due to its rapid growth, high metastatic rate and limited possibilities of treatment. For many years, SCLC management has been based mostly on chemo and radiotherapy. However, new therapeutic approaches have been proposed in the past few years, including immunotherapy, which is currently implemented in clinical practice. Unfortunately, in many cases, response to therapy, especially chemotherapy, remains poor, or the patient becomes resistant to initially effective treatment. One of the crucial problems during SCLC patient care is a lack of appropriate predictive biomarkers for various therapeutic approaches. Another critical issue is the scarcity of collected tissue during biopsy, which may be insufficient or of too poor quality for analysis. A liquid biopsy might be the key to solving both of those problems as it is collected in a non-invasive way and enables the measurement of various biomarkers, including circulating tumor DNA (ctDNA) and circulating tumor cells (CTCs). In this review, we discuss various approaches to potentially incorporating liquid biopsy into clinical application - as a companion to imaging during SCLC diagnostics, a new approach to molecular subtyping, and a material enabling predictive or prognostic biomarkers assessment. We also summarize ongoing clinical trials encompassing SCLC patients in which liquid biopsy is collected and examined.

Cholangiocarcinoma (CCA) is one of the most aggressive cancers with a poor prognosis. Current treatment strategies involve hepatobiliary surgery, chemotherapy, radiotherapy, and supportive care; however, the success of these treatments remains limited. Therefore, this study investigated the potential of Atractylodes lancea (Thunb) D.C. (AL) in limiting the progress of CCA by targeting the expression of cancer-related genes involved in immune responses and circulating tumor cells. The study was part of Phase 2A clinical trial in advanced-stage intrahepatic iCCA (iCCA) patients: Group 1 (n = 16) received low-dose AL (capsule formulation of the standardized extract of AL: CMC-AL) with standard supportive care, Group 2 (n = 16) received high-dose AL with standard supportive care, and Group 3 (n = 16) received standard supportive care alone. Venous whole blood samples (EDTA, 5 ml) were collected from each patient on Day 1 and Day 90 and the non-CCA subjects (n = 16) on Day 1. Fifty-nine samples (48 and 11 samples for Day 1 and Day 90, respectively) were processed for total RNA isolation. Gene expression was evaluated using reverse transcription followed by a PCR array. Regardless of dosage, gene expression patterns in the AL-treated groups closely resembled those of the healthy subjects. Specifically, cancer-associated genes, including VEGF-A, NR4A3, Ki-67, and EpCAM, were significantly down-regulated. Additionally, the expression levels of immune-related genes were modulated in AL-treated patients. The treatment groups exhibited lower levels of the pro-inflammatory cytokine IL-6, increased expression of the anti-inflammatory cytokine IL-10, and cell-mediated immune-related molecules such as CTLA4 and PFR1. These findings suggest the potential of AL for iCCA treatment. However, additional studies are required to confirm the correlation between gene and protein expression profiles, as well as CTCs profile.

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related mortality worldwide, with rising incidence and mortality. Early-stage HCC is often asymptomatic, and the lack of reliable early diagnostic markers leads to late-stage diagnosis with limited treatment options. Current treatment relies on tumour staging and patient status, but accurate staging requires invasive procedures that fail to capture tumour heterogeneity and progression. There is an urgent need for less invasive diagnostic strategies, such as liquid biopsy technologies, which allow for repeated sampling and real-time analysis of tumour dynamics. Liquid biopsies, including circulating tumour cells (CTCs) and circulating tumour DNA (ctDNA), offer the potential to monitor recurrence, metastasis, and treatment responses, potentially transforming HCC clinical management by enabling earlier intervention and personalised treatment strategies.

Recent studies emphasise the potential of ctDNA as a non-invasive biomarker by targeting DNA methylation for early HCC detection, enabling timely intervention and personalised treatment to improve patient outcomes. Comparative analyses have shown that ctDNA mutation testing outperforms alpha-fetoprotein (AFP), with a sensitivity of 85% and a specificity of 92%, compared to 60% sensitivity and 80% specificity for AFP. Additionally, profiling the ctDNA mutation landscape of 100 HCC patients has identified recurrent mutations in genes such as TP53, CTNNB1, and AXIN1. ctDNA appears to be a promising non-invasive biomarker in the clinical management of HCC patients, with the sensitivity and specificity improving by 41.67% and 15% respectively. The ctDNA mutations, particularly those targeting DNA methylation, highlight great potential for precision medicine, critical for early diagnosis and prognosis of HCC.

Circulating melanoma cells (CMCs) are responsible for the hematogenous spread of melanoma and, ultimately, metastasis. However, their study has been limited by the low abundance in patient blood and the heterogeneous expression of surface markers. The FDA-approved CellSearch platform enriches CD146-positive CMCs, whose number correlates with progression-free survival and overall survival. However, a single marker may not be sufficient to identify them all. The Parsortix system allows enrichment of CMCs based on their size and deformability, keeping them viable and suitable for downstream molecular analyses. In this study, we tested the strengths, weaknesses and potential convergences of both platforms to integrate the counting of CMCs with a protocol for their genetic analysis. Samples run on Parsortix were labeled with a customized melanoma antibody cocktail, which efficiently labeled and distinguished CMCs from endothelial cells/leukocytes. The capture rate of CellSearch and Parsortix was comparable for cell lines, but Parsortix had a higher capture rate in real-life samples. Moreover, double enrichment with both CellSearch and Parsortix succeeded in removing most of the leukocyte contamination, resulting in an almost pure CMC sample suitable for genetic analysis. In this regard, a proof-of-concept analysis of CMCs from a paradigmatic case of a metastatic uveal melanoma patient led to the identification of multiple genetic alterations. In particular, the GNAQ p.Q209L was identified as homozygous, while a deletion in BAP1 exon 9 was found hemizygous. Moreover, an isochromosome 8 and a homozygous deletion of the CDKN2A gene were detected. In conclusion, we have optimized an approach to successfully enrich and retrieve viable CMCs from metastatic melanoma patients. Moreover, this study provides proof-of-principle for the feasibility of a marker-agnostic CMC enrichment followed by CMC phenotypic identification and genetic analysis.Kindly check and confirm the processed contributed equally is correctly identify We confirm.

Polymerase Chain Reaction (PCR) has transformed forensic DNA analysis but is still limited when dealing with compromised trace or inhibitor-containing samples. Nanotechnology has been integrated into nanoPCR (nanoparticle-assisted PCR) to overcome these obstacles. Nanomaterials improve PCR sensitivity, selectivity, and efficiency. Examples of these materials are semiconductor quantum dots and metal nanoparticles. They enhance DNA binding to primers, stabilize enzymes, and function as effective heat conductors, making accurate amplification possible even with tainted samples. The developments in nanoPCR have potential uses in forensics, as they allow for the more sensitive analysis of smaller, polluted, or deteriorated samples. Nevertheless, there are methodological and ethical issues. To provide credible and legitimate forensic evidence, rigorous validation and standardization of NanoPCR techniques are vital. The article addresses the relevant ethical and methodological aspects in forensic casework while examining the integration of nanotechnology into PCR.

Malignant tumors represent a significant worldwide health challenge, with elevated morbidity and mortality rates necessitating enhanced early identification and individualized treatment. Liposomes, as biomimetic lipid-based nanovesicles, have developed as a multifaceted platform for detecting and treating malignant tumors due to their excellent biocompatibility, stability, and membrane fusion properties. Circulating tumor markers, such as circulating tumor cells (CTCs), extracellular vesicles (EVs), circulating tumor proteins (CTPs), and circulating tumor nucleic acids (ctNAs), play a key role in early cancer diagnosis, disease progression monitoring, and personalized therapy. Liposome-based platforms enable effective molecular recognition, targeted detection, and signal amplification by targeting circulating tumor biomarkers, significantly increasing the potential for early tumor diagnosis and treatment. This review systematically summarizes advancements in the study of liposomes concerning circulating tumor markers, including applications in targeted recognition, early detection, and disease diagnosis, while discussing present problems and prospective applications of existing technology.

Circulating tumor cells (CTCs) are a crucial indicator of cancer metastasis, and are vital for early diagnosis, disease monitoring, and treatment response evaluation. However, their extremely low concentration and the complexities of isolation techniques pose a significant challenge in capturing and analyzing CTCs. In this study, we developed a novel microfluidic system that integrates magnetic capture and invasive screening onto a single microfluidic chip. By attaching positively charged magnetic nanoparticles to negatively charged CTCs, the magnetic separation of CTCs within the chip effectively eliminates interference from blood cells. A total of 2 mL blood sample can be processed within 3 min, achieving an impressive tumor capture efficiency of 84 %. Using the chip, we also successfully achieved long-term culture of CTCs, and identified CTCs with high activity and invasive potential in blood samples from 11 patients with colorectal cancer. Finally, we analyzed telomerase activity in cultured CTCs on the microfluidic chip. Significantly higher invasive potential and telomerase activity were observed in CTCs from the malignant tumor group compared to the benign group (P < 0.01), highlighting their increased aggressiveness. This study offers a novel approach for efficient CTCs isolation, culture, and telomerase analysis, clarifying the crucial role of telomerase in tumor metastasis and providing profound insights for future research on telomerase-targeted tumor metastasis.

The Liquid Biopsy (LB) represents an ideal surrogate of tumor Tissue Biopsy (TB) when the aim is to obtain useful information on patient prognosis and personalized therapy. This technique renders it possible to isolate circulating tumor cells, circulating tumor DNA and other molecules from biological fluids. The most commonly used fluid for liquid biopsy is blood, but depending on the case it could be necessary to isolate the tumor components from other biological fluids such as urine, pleural effusion, cerebrospinal fluid, and others. The main advantages of liquid biopsy are the minimally invasive nature of the procedure and the possibility of analyzing all tumor clones. Limitations include difficulties in the isolation of tumor components and the requirement for highly sensitive analysis methods to avoid the risk of technical artifacts. In our review we will focus on describing circulating tumor biomarkers to illustrate the variety of information that can be obtained from biological fluids, particularly blood. We will then discuss the advanced biotechnological techniques suitable for the identification and analysis of Circulating Tumor DNA (ctDNA), examining both the potential and limitations of analytical methods and the clinical applicability of liquid biopsy for cancer diagnosis, monitoring, and therapeutic prediction. Additionally, we will explore strategies to enhance this valuable alternative to the more invasive tissue biopsy, with a dedicated focus on ongoing clinical studies, currently approved tests, and guideline recommendations.

Transplant oncology integrates a wide variety of fields, such as surgery, oncology, and transplant medicine, intending to increase the range of studies and treatments for hepatobiliary cancers and other liver-related malignant lesions. Liver transplantation (LT) has proven to be an effective treatment for hepatocellular carcinoma. While the Milan criteria are still the gold standard, several new, more inclusive criteria have been proposed, and hepatocellular carcinoma has become a major indication for liver transplantation. The continuous evolution of diagnostic technologies supported this with higher image quality and more accurate staging. This review describes the current applications of transplant oncology in hepatocellular carcinoma, cholangiocarcinoma, neuroendocrine tumors, and liver metastatic disease from colorectal cancer and discusses the path that led to the development of transplant oncology as an organized approach to managing gastrointestinal malignancies through transplantation. More importantly, the significance of a multidisciplinary approach and criteria in the selection of suitable candidates are discussed. In addition, newer aspects of transplant oncology, such as immunotherapy, circulating tumor DNA (ctDNA), novel surgical techniques, and the utilization of artificial intelligence, are presented. Finally, the opportunities and challenges involved in the field's future, as well as the evolution of the criteria used over the years and insightful thoughts for the future of the criteria, are discussed.

To highlight innovations in ophthalmic oncology through histiocytosis advancements.

Perspective and retrospective review.

The literature outlining the recent advancements in histiocytosis and ocular oncology was reviewed and combined with trial data and personal recollection. Intersections between these two fields were discussed.

The understanding of genetic mutations in disease-both in which cells they occur and the timing of mutation development-has expanded in tandem for the fields of ophthalmic oncology and histiocytosis. Similarly, advancements in diagnostic and treatment technology in one field can help patients in the other. For example, in one study, cell-free DNA testing reliably detected mutations in 14 of 18 (78%) patients with suspected histiocytosis. This technique has also been used in ophthalmic oncology as an alternative to invasive biopsy to avoid the risk of tumor externalization, vision impairment, and other side effects. These and other advancements have allowed both fields to utilize targeted agents to successfully treat diseases with an actionable mutation; or deliver more targeted chemotherapy via the intraarterial technique.

The explosion of molecular genetics technology and targeted therapies has revolutionized cancer treatment, including histiocytosis and ophthalmic oncology. Recent progress in both fields has shown how these seemingly disparate areas have many intersections, and this speaks to the collaborative spirit that is inherent in clinical research.

A 2012 review of therapeutic ultrasound was published to educate researchers and physicians on potential applications and concerns for unintended bioeffects (doi: 10.7863/jum.2012.31.4.623). This review serves as an update to the parent article, highlighting advances in therapeutic ultrasound over the past 12 years. In addition to general mechanisms for bioeffects produced by therapeutic ultrasound, current applications, and the pre-clinical and clinical stages are outlined. An overview is provided for image guidance methods to monitor and assess treatment progress. Finally, other topics relevant for the translation of therapeutic ultrasound are discussed, including computational modeling, tissue-mimicking phantoms, and quality assurance protocols.

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

To investigate the clinical significance of fecal Syndecan-2 (SDC2) gene methylation combined with blood tumor abnormal protein (TAP) detection for the diagnosis of colorectal cancer (CRC) and its precancerous lesions.

A retrospective study was conducted to collect patients diagnosed with CRC or colorectal adenoma (Ade) from March 2020 to March 2023, and healthy people (Nor) without any gastrointestinal diseases during the same period as the control group. All participants underwent the fecal SDC2 gene methylation test, blood TAP test and fecal occult blood test (FOBT). The differences in the positivity rates of each index were compared, receiver operator characteristic curves were plotted and the area under the curve (AUC) was calculated to evaluate the diagnostic effects of different testing methods on CRC and its precancerous lesions.

A total of 146 individuals were included in the study, including 69 CRC patients, 47 patients with Ade and 30 healthy individuals. The results showed that, SDC2, TAP and the combined assay had high comprehensive diagnostic efficacy for the diagnosis of CRC, but there was no significant difference between the three methods in terms of AUC, sensitivity, and specificity. However, for Ade, the combined detection was statistically significant, with a high AUC (0.905), high sensitivity (95.7%), and high specificity (86.7%).

Fecal SDC2 gene methylation combined with blood TAP detection is an effective noninvasive screening and diagnostic method to enhance the early detection and treatment of CRC precancerous lesions, such as Ade, thereby reducing the incidence and mortality of CRC.

Liquid biopsy-based biomarkers offer several advantages since they are minimally invasive, can be useful in longitudinal monitoring of the disease and have higher patient compliance. We describe a protocol using minimal volumes of archival and prospective serum/plasma samples to define the RNA contents of EVs and discuss its benefits and limitations.

RNA-seq analysis of matched tumor biopsy, circulating EVs from breast cancer patients (EV-C, n = 26) and healthy donors (EV-H, n = 4) was performed and differentially expressed genes were validated by RT-PCR in a separate series of samples (EV-C, n = 32 and EV-H, n = 22). A total of 84 samples were studied.

RNA-seq data from 500 μl serum samples yielded more than 17000 genes, of which 320 were DEGs (adjusted p value ≤ 0.05) between EV-C and EV-H samples. Pathways for Myc V1, reactive oxygen species, angiogenesis, allograft rejection and Interferon regulated genes were over-represented in EV-C samples. Computational deconvolution algorithms for cell signatures identified immune cells such as Th1 and memory T-cells, endothelial cells, and osteoblasts from the stromal compartment as significant. Top 6 genes were validated by qRT-PCR in all samples (n = 84) and they consistently and correctly classified cancer and healthy groups. An independent set of 374 and 640 DEGs could segregate ER positive/ER negative and non-metastatic versus metastatic samples, respectively. EVs from metastatic samples had higher variability in gene expression patterns whereas those from non-metastatic samples showed a better correlation.

By using low serum amounts successfully for EV transcriptomics, we demonstrate that a minimally invasive technique could be converted to a microinvasive format. These data lay the foundation for EV RNA based biomarker discovery for segregating breast cancers.

Small cell lung cancer (SCLC) remains a challenge in oncology due to its aggressive behavior and dismal prognosis. Despite advances in treatments, novel strategies are urgently needed. Enter liquid biopsy-a game-changer in SCLC management. This revolutionary non-invasive approach allows for the analysis of circulating tumor cells (CTCs), offering insights into tumor behavior and treatment responses. Our review focuses on a groundbreaking frontier: harnessing CTCs to create three-dimensional (3D) organoid models. These models, derived from CTCs that break away from the primary tumor or metastatic locations, hold immense potential for revolutionizing cancer research, especially in SCLC. We explore the essential conditions for successfully establishing CTC-derived organoids-a transformative approach with profound implications for personalized medicine. Our evaluation spans diverse isolation techniques, shedding light on their advantages and limitations. Furthermore, we uncover the critical factors governing the cultivation of 3D organoids from CTCs, meticulously mimicking the tumor microenvironment. This review comprehensively elucidates the molecular characterization of these organoids, showcasing their potential in identifying treatment targets and predicting responses. In essence, our review amalgamates cutting-edge methodologies for isolating CTCs, establishing transformative CTC-derived organoids, and characterizing their molecular landscape. This represents a promising frontier for advancing personalized medicine in the complex realm of SCLC management and holds significant implications for translational research.

Liquid biopsy, specifically circulating cell-free DNA (cfDNA), has emerged as a powerful tool for cancer early diagnosis, prognosis, and treatment monitoring over a wide range of cancer types. Computational modeling (CM) of cfDNA data is essential to harness its full potential for real-time, noninvasive insights into tumor biology, enhancing clinical decision making.

This work reviews CM-cfDNA methods applied to clinical oncology, emphasizing both machine learning (ML) techniques and mechanistic approaches. The latter integrate biological principles, enabling a deeper understanding of cfDNA dynamics and its relationship with tumor evolution.

Key findings highlight the effectiveness of CM-cfDNA approaches in improving diagnostic accuracy, identifying prognostic markers, and predicting therapeutic outcomes. ML models integrating cfDNA concentration, fragmentation patterns, and mutation detection achieve high sensitivity and specificity for early cancer detection. Mechanistic models describe cfDNA kinetics, linking them to tumor growth and response to treatment, for example, immune checkpoint inhibitors. Longitudinal data and advanced statistical constructs further refine these models for quantification of interindividual and intraindividual variability.

CM-cfDNA represents a pivotal advancement in precision oncology. It bridges the gap between extensive cfDNA data and actionable clinical insights, supporting its integration into routine cancer care. Future efforts should focus on standardizing protocols, validating models across populations, and exploring hybrid approaches combining ML with mechanistic modeling to improve biological understanding.

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.

Various surface-enhanced Raman scattering (SERS) biosensors offer powerful tools for the ultrasensitive detection of circulating tumor cells (CTCs) and tumor diagnosis. Despite their efficacy, the swift and precise preparation of SERS plasmonic nanostructures poses an ongoing challenge. In this study, we introduce DNA-assisted plasmonic nanostructures capable of producing dual signals and facilitating DNA Walker signal amplification, resulting in the development of a SERS/Fluorescent (FL) dual-mode cytosensor for CTCs detection. Firstly, Au@Ag nanoparticle multimers (Au@AgNMs) featuring interparticle nano-gaps were synthesized through DNA self-assembly and in-situ deposition, which provided plasmonic nanostructures. Hence, the nano-gap distance among Au@AgNMs was meticulously regulated after optimization to achieve both SERS enhancement and fluorescence quenching. Subsequently, the aptamer (Apt) of MUC1 recognized CTCs specifically for strand displacement reaction (SDR) and further triggered the DNA Walker reaction for signal amplification. The limit of detection (LOD) of proposed cytosensor can be obtained as low as 5 cells/mL in SERS mode and 21 cells/mL in FL mode. Hence, SERS mode confers highly precise information, while FL mode allow for rapid quantitative analysis. This dual-mode cytosensor based on plasmonic nanostructures facilitates the early detection and precise treatment of cancer or infectious diseases.

Delving into cancer dormancy has been an inherent task that may drive the lethal recurrence of cancer after primary tumor relief. Cells in quiescence can survive for a short or long term in silence, may undergo genetic or epigenetic changes, and can initiate relapse through certain contextual cues. The state of dormancy can be induced by multiple conditions including cancer drug treatment, in turn, undergoes a life cycle that generally occurs through dissemination, invasion, intravasation, circulation, immune evasion, extravasation, and colonization. Throughout this cascade, a cellular machinery governs the fate of individual cells, largely affected by gene regulation. Despite its significance, a precise view of cancer dormancy is yet hampered. Revolutionizing advanced single cell and long read sequencing through analysis methodologies and artificial intelligence, the most recent stage in the research tool progress, is expected to provide a holistic view of the diverse aspects of cancer dormancy.

Cancer mortality is closely linked to recurrence and distant metastasis, posing challenges in real-time tracking due to the invasiveness of current methods. Circulating tumor cells (CTCs) show promise as potential tools; however, their scarcity remains a significant obstacle.

In this prospective study, we validated a simple culture protocol and investigated the correlation between clinical response and CTC growth status. Following negative selection, the isolated cells were subjected to ex vivo cultivation in a two-dimensional environment supplemented with cytokines for up to 21 days, followed by immunofluorescence staining for analysis.

Among 37 participants with solid tumors and distant metastasis (34.8% head and neck cancer), 47 samples were collected, from which CTCs were detected. The percentages of CTCs, atypical CTCs, and white blood cells during cultivation from days 7-21 were significantly different (p < 0.001, p < 0.001, and p = 0.330, respectively). Patients were further categorized into progressive disease (PD) and non-PD groups based on disease status, revealing significant differences in CTC growth rates, which increases from Days 7-21 between groups (5.5x vs. 2.8x growth, respectively; p < 0.001).

With the proposed protocols, we cultured CTCs from patients with various cancers for 21 days and identified a tool for predicting cancer response. The actual cancer status (PD or non-PD) at CTC isolation correlates to CTC growth rate, guiding the required observation time and parameters for culture.

Routine screening to detect silent but deadly cancers such as pancreatic ductal adenocarcinoma (PDAC) can significantly improve survival, creating an important need for a convenient screening test. High-resolution proton (1H) magnetic resonance spectroscopy (MRS) of plasma identifies circulating metabolites that can allow detection of cancers such as PDAC that have highly dysregulated metabolism.

We first acquired 1H MR spectra of human plasma samples classified as normal, benign pancreatic disease and malignant (PDAC). We next trained a system of artificial neural networks (ANNs) to process and discriminate these three classes using the full spectrum range and resolution of the acquired spectral data. We then identified and ranked spectral regions that played a salient role in the discrimination to provide interpretability of the results. We tested the accuracy of the ANN performance using blinded plasma samples.

We show that our ANN approach yields, in a cross validation-based training of 170 samples, a sensitivity and a specificity of 100% for malignant versus non-malignant (normal and disease combined) discrimination. The trained ANNs achieve a sensitivity and specificity of 87.5% and 93.1% respectively (AUC: ROC = 0.931, P-R = 0.854), with 45 blinded plasma samples. Further, we show that the salient spectral regions of the ANN discrimination correspond to metabolites of known importance for their role in cancers.

Our results demonstrate that the ANN approach presented here can identify PDAC from 1H MR plasma spectra to provide a convenient plasma-based assay for population-level screening of PDAC. The ANN approach can be suitably expanded to detect other cancers with metabolic dysregulation.

A localized surface plasmon resonance (LSPR) sensor based on tapered optical fiber (TOF) using hollow gold nanoparticles (HAuNPs) for measuring the refractive index (RI) is presented. This optical fiber sensor is a good candidate for a label-free RI biosensor. In practical biosensors, bioreceptors are immobilized on nanoparticles (NPs) that only absorb specific biomolecules. The binding of these biomolecules to the receptors changes the local RI around the sensor and this change is detected by the transmittance spectrum of the fiber. Fast, accurate, easy and low-cost disease diagnosis are the advantages of optical fiber biosensors. In this paper, the structure theory is reviewed and the sensor is simulated by the finite difference time domain (FDTD) method and the finite element method (FEM) and the effect of the thickness and diameter of the HAuNPs and the waist diameter of the TOF is investigated. For the structure with HAuNPs thickness (2.5 nm), diameter (50 nm), and the fiber waist diameter of 10 μm, the wavelength sensitivity of 489.8 nm/RIU and full width at half maximum (FWHM) of 50 nm are obtained, which are better than those specifications in some other LSPR fiber sensors. In addition, the sensitivity of the sensor increases about 2-3 times compared to those of sensors with the same structure. Although there are many parameters in human blood that can change its RI, in practical work, the special bioreceptors on the sensor can deactivate other markers except the specific cancer markers, which changes the effective RI. Therefore, this optical fiber sensor is used for label-free detecting the RI of cancer cells and can be used as a biosensor for the detection of early stages of cancers in a non-invasive way, just using human blood samples.

Circulating tumor cells (CTCs) drive metastasis, the leading cause of death in individuals with breast cancer. Due to their low abundance in the circulation, robust CTC expansion protocols are urgently needed to effectively study disease progression and therapy responses. Here we present the establishment of long-term CTC-derived organoids from female individuals with metastatic breast cancer. Multiomics analysis of CTC-derived organoids along with preclinical modeling with xenografts identified neuregulin 1 (NRG1)-ERBB2 receptor tyrosine kinase 3 (ERBB3/HER3) signaling as a key pathway required for CTC survival, growth and dissemination. Genome-wide CRISPR activation screens revealed that fibroblast growth factor receptor 1 (FGFR1) signaling serves a compensatory function to the NRG1-HER3 axis and rescues NRG1 deficiency in CTCs. Conversely, NRG1-HER3 activation induced resistance to FGFR1 inhibition, whereas combinatorial blockade impaired CTC growth. The dynamic interplay between NRG1-HER3 and FGFR1 signaling reveals the molecular basis of cancer cell plasticity and clinically relevant strategies to target it. Our CTC organoid platform enables the identification and validation of patient-specific vulnerabilities and represents an innovative tool for precision medicine.

Circulating tumor cells (CTCs) are tumor cells that exist in human peripheral blood, which could spread to other tissues or organs via the blood circulation system and develop into metastatic foci, leading to tumor recurrence or metastasis in postoperative patients and thereby increasing the mortality of malignant tumor patients. Evaluation of CTC levels can be used for tumor metastasis prediction, prognosis evaluation, drug exploitation, individualized treatment, liquid biopsy, etc., which exhibit outstanding clinical application prospects. In recent years, accurately capturing and analyzing CTCs has become a research hotspot in the early diagnosis and precise treatment of tumors. This review summarized various enrichment and isolation technologies for evaluating CTCs based on the design principle and discussed the challenges and perspectives in this field.

Although advances in diagnostic techniques, new therapeutic strategies and personalization of breast cancer (BC) care have improved the survival for a number of patients, BC remains a major cause of morbidity and mortality for women. The study of circulating tumor cells (CTCs) has significant potential in translational oncology since these cells represent promising biomarkers throughout the entire course of BC in patients. CTCs also have notable prognostic value in early BC as well as metastatic BC. Based on current knowledge, it seems that the dynamics of CTCs that change during therapy reflect therapy response, and CTCs could serve as a tool for risk stratification and real-time monitoring of treatment in patients with BC. The question of how to use this information in everyday clinical practice and how this information can guide or change therapy to affect the clinical outcome of patients with BC remains unanswered. The present review aims to discuss current completed and ongoing trials that have been designed to demonstrate the clinical significance of CTCs, offer insights into treatment efficacy and assess CTC utility, facilitating their implementation in the routine management of patients with BC.

Each year, millions of new cancer cases and cancer-related deaths underscore the urgent need for effective, affordable screening methods. Circulating tumor cells (CTCs), which derived from tumors and shedding into bloodstream, are considered promising biomarkers for liquid biopsy due to their unique biological significance and the substantial volume of supporting research. Among many advanced CTCs detection methods, electrochemical sensing is rapidly developing due to their high selectivity, high sensitivity, low cost, and rapid detection capability, well meeting the growing demand for non-invasive liquid biopsy. This review focuses on the entire procedure of detecting CTCs using electrochemical cytosensors, starting from sample preparation, detailing bio-recognition elements for capturing CTCs, highlighting design strategies of cytosensor, and discussing the prospects and challenges of electrochemical cytosensor applications.