Using single-cell sequencing technology to detect circulating tumor cells in solid tumors

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

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

Adoptive cell therapy for solid tumors beyond CAR-T: Current challenges and emerging therapeutic advances

Adoptive cellular immunotherapy using immune cells expressing chimeric antigen receptors (CARs) is a highly specific anti-tumor immunotherapy that has shown promise in the treatment of hematological malignancies. However, there has been a slow progress toward the treatment of solid tumors owing to the complex tumor microenvironment that affects the localization and killing ability of the CAR cells. Solid tumors with a strong immunosuppressive microenvironment and complex vascular system are unaffected by CAR cell infiltration and attack. To improve their efficacy toward solid tumors, CAR cells have been modified and upgraded by "decorating" and "pruning". This review focuses on the structure and function of CARs, the immune cells that can be engineered by CARs and the transformation strategies to overcome solid tumors, with a view to broadening ideas for the better application of CAR cell therapy for the treatment of solid tumors.

Cell-nanocarrier drug delivery system: a promising strategy for cancer therapy

Tumor targeting has been a great challenge for drug delivery systems. A number of nanotechnology-derived drug carriers have been developed for cancer treatment to improve efficacy and biocompatibility. Among them, the emergence of cell-nanocarriers has attracted great attention, which simulates cell function and has good biocompatibility. They can also escape the clearance of reticuloendothelial system, showing a long-cycle effect. The inherent tumor migration and tumor homing ability of cells increase their significance as tumor-targeting vectors. In this review, we focus on the combination of stem cells, immune cells, red blood cells, and cell membranes to nanocarriers, which enable chemotherapy agents to efficiently target lesion sites and improve drug distribution while being low toxic and safe. In addition, we discuss the pros and cons of these nanoparticles as well as the challenges and opportunities that lie ahead. Although research to address these limitations is still ongoing, this promising tumor-targeted drug delivery system will provide a safe and effective platform against cancer.

Decoding the tumor microenvironment and molecular mechanism: unraveling cervical cancer subpopulations and prognostic signatures through scRNA-Seq and bulk RNA-seq analyses

Background

Cervical carcinoma (CC) represents a prevalent gynecological neoplasm, with a discernible rise in prevalence among younger cohorts observed in recent years. Nonetheless, the intrinsic cellular heterogeneity of CC remains inadequately investigated.

Methods

We utilized single-cell RNA sequencing (scRNA-seq) transcriptomic analysis to scrutinize the tumor epithelial cells derived from four specimens of cervical carcinoma (CC) patients. This method enabled the identification of pivotal subpopulations of tumor epithelial cells and elucidation of their contributions to CC progression. Subsequently, we assessed the influence of associated molecules in bulk RNA sequencing (Bulk RNA-seq) cohorts and performed cellular experiments for validation purposes.

Results

Through our analysis, we have discerned C3 PLP2+ Tumor Epithelial Progenitor Cells as a noteworthy subpopulation in cervical carcinoma (CC), exerting a pivotal influence on the differentiation and progression of CC. We have established an independent prognostic indicator-the PLP2+ Tumor EPCs score. By stratifying patients into high and low score groups based on the median score, we have observed that the high-score group exhibits diminished survival rates compared to the low-score group. The correlations observed between these groups and immune infiltration, enriched pathways, single-nucleotide polymorphisms (SNPs), drug sensitivity, among other factors, further underscore their impact on CC prognosis. Cellular experiments have validated the significant impact of ATF6 on the proliferation and migration of CC cell lines.

Conclusion

This study enriches our comprehension of the determinants shaping the progression of CC, elevates cognizance of the tumor microenvironment in CC, and offers valuable insights for prospective CC therapies. These discoveries contribute to the refinement of CC diagnostics and the formulation of optimal therapeutic approaches.

Molecular Classifications in Gastric Cancer: A Call for Interdisciplinary Collaboration

Gastric cancer (GC) is a heterogeneous disease, often diagnosed at advanced stages, with a 5-year survival rate of approximately 20%. Despite notable technological advancements in cancer research over the past decades, their impact on GC management and outcomes has been limited. Numerous molecular alterations have been identified in GC, leading to various molecular classifications, such as those developed by The Cancer Genome Atlas (TCGA) and the Asian Cancer Research Group (ACRG). Other authors have proposed alternative perspectives, including immune, proteomic, or epigenetic-based classifications. However, molecular stratification has not yet transitioned into clinical practice for GC, and little attention has been paid to alternative molecular classifications. In this review, we explore diverse molecular classifications in GC from a practical point of view, emphasizing their relationships with clinicopathological factors, prognosis, and therapeutic approaches. We have focused on classifications beyond those of TCGA and the ACRG, which have been less extensively reviewed previously. Additionally, we discuss the challenges that must be overcome to ensure their impact on patient treatment and prognosis. This review aims to serve as a practical framework to understand the molecular landscape of GC, facilitate the development of consensus molecular categories, and guide the design of innovative molecular studies in the field.

Dissemination of Circulating Tumor Cells in Breast and Prostate Cancer: Implications for Early Detection

Burgeoning evidence suggests that circulating tumor cells (CTCs) may disseminate into blood vessels at an early stage, seeding metastases in various cancers such as breast and prostate cancer. Simultaneously, the early-stage CTCs that settle in metastatic sites [termed disseminated tumor cells (DTCs)] can enter dormancy, marking a potential source of late recurrence and therapy resistance. Thus, the presence of these early CTCs poses risks to patients but also holds potential benefits for early detection and treatment and opportunities for possibly curative interventions. This review delves into the role of early DTCs in driving latent metastasis within breast and prostate cancer, emphasizing the importance of early CTC detection in these diseases. We further explore the correlation between early CTC detection and poor prognoses, which contribute significantly to increased cancer mortality. Consequently, the detection of CTCs at an early stage emerges as a critical imperative for enhancing clinical diagnostics and allowing for early interventions.

Targeting circulating tumor cells to prevent metastases

Circulating tumor cells (CTCs) are cancer cells that detach from the primary tumor, enter the bloodstream or body fluids, and spread to other body parts, leading to metastasis. Their presence and characteristics have been linked to cancer progression and poor prognosis in different types of cancer. Analyzing CTCs can offer valuable information about tumors' genetic and molecular diversity, which is crucial for personalized therapy. Epithelial-mesenchymal transition (EMT) and the reverse process, mesenchymal-epithelial transition (MET), play a significant role in generating and disseminating CTCs. Certain proteins, such as EpCAM, vimentin, CD44, and TGM2, are vital in regulating EMT and MET and could be potential targets for therapies to prevent metastasis and serve as detection markers. Several devices, methods, and protocols have been developed for detecting CTCs with various applications. CTCs interact with different components of the tumor microenvironment. The interactions between CTCs and tumor-associated macrophages promote local inflammation and allow the cancer cells to evade the immune system, facilitating their attachment and invasion of distant metastatic sites. Consequently, targeting and eliminating CTCs hold promise in preventing metastasis and improving patient outcomes. Various approaches are being explored to reduce the volume of CTCs. By investigating and discussing targeted therapies, new insights can be gained into their potential effectiveness in inhibiting the spread of CTCs and thereby reducing metastasis. The development of such treatments offers great potential for enhancing patient outcomes and halting disease progression.

Exploration and validation of key genes associated with early lymph node metastasis in thyroid carcinoma using weighted gene co-expression network analysis and machine learning

Background

Thyroid carcinoma (THCA), the most common endocrine neoplasm, typically exhibits an indolent behavior. However, in some instances, lymph node metastasis (LNM) may occur in the early stages, with the underlying mechanisms not yet fully understood.

Materials and methods

LNM potential was defined as the tumor's capability to metastasize to lymph nodes at an early stage, even when the tumor volume is small. We performed differential expression analysis using the 'Limma' R package and conducted enrichment analyses using the Metascape tool. Co-expression networks were established using the 'WGCNA' R package, with the soft threshold power determined by the 'pickSoftThreshold' algorithm. For unsupervised clustering, we utilized the 'ConsensusCluster Plus' R package. To determine the topological features and degree centralities of each node (protein) within the Protein-Protein Interaction (PPI) network, we used the CytoNCA plugin integrated with the Cytoscape tool. Immune cell infiltration was assessed using the Immune Cell Abundance Identifier (ImmuCellAI) database. We applied the Least Absolute Shrinkage and Selection Operator (LASSO), Support Vector Machine (SVM), and Random Forest (RF) algorithms individually, with the 'glmnet,' 'e1071,' and 'randomForest' R packages, respectively. Ridge regression was performed using the 'oncoPredict' algorithm, and all the predictions were based on data from the Genomics of Drug Sensitivity in Cancer (GDSC) database. To ascertain the protein expression levels and subcellular localization of genes, we consulted the Human Protein Atlas (HPA) database. Molecular docking was carried out using the mcule 1-click Docking server online. Experimental validation of gene and protein expression levels was conducted through Real-Time Quantitative PCR (RT-qPCR) and immunohistochemistry (IHC) assays.

Results

Through WGCNA and PPI network analysis, we identified twelve hub genes as the most relevant to LNM potential from these two modules. These 12 hub genes displayed differential expression in THCA and exhibited significant correlations with the downregulation of neutrophil infiltration, as well as the upregulation of dendritic cell and macrophage infiltration, along with activation of the EMT pathway in THCA. We propose a novel molecular classification approach and provide an online web-based nomogram for evaluating the LNM potential of THCA (http://www.empowerstats.net/pmodel/?m=17617_LNM). Machine learning algorithms have identified ERBB3 as the most critical gene associated with LNM potential in THCA. ERBB3 exhibits high expression in patients with THCA who have experienced LNM or have advanced-stage disease. The differential methylation levels partially explain this differential expression of ERBB3. ROC analysis has identified ERBB3 as a diagnostic marker for THCA (AUC=0.89), THCA with high LNM potential (AUC=0.75), and lymph nodes with tumor metastasis (AUC=0.86). We have presented a comprehensive review of endocrine disruptor chemical (EDC) exposures, environmental toxins, and pharmacological agents that may potentially impact LNM potential. Molecular docking revealed a docking score of -10.1 kcal/mol for Lapatinib and ERBB3, indicating a strong binding affinity.

Conclusion

In conclusion, our study, utilizing bioinformatics analysis techniques, identified gene modules and hub genes influencing LNM potential in THCA patients. ERBB3 was identified as a key gene with therapeutic implications. We have also developed a novel molecular classification approach and a user-friendly web-based nomogram tool for assessing LNM potential. These findings pave the way for investigations into the mechanisms underlying differences in LNM potential and provide guidance for personalized clinical treatment plans.

Recent Progress in Enhanced Cancer Diagnosis, Prognosis, and Monitoring Using a Combined Analysis of the Number of Circulating Tumor Cells (CTCs) and Other Clinical Parameters

Analysis of circulating tumor cells (CTCs) holds promise to diagnose cancer or monitor its development. Among the methods, counting CTC numbers in blood samples could be the simplest way to implement it. Nevertheless, its clinical utility has not yet been fully accepted. The reasons could be due to the rarity and heterogeneity of CTCs in blood samples that could lead to misleading results from assays only based on single CTC counts. To address this issue, a feasible direction is to combine the CTC counts with other clinical data for analysis. Recent studies have demonstrated the use of this new strategy for early detection and prognosis evaluation of cancers, or even for the distinguishment of cancers with different stages. Overall, this approach could pave a new path to improve the technical problems in the clinical applications of CTC counting techniques. In this review, the information relevant to CTCs, including their characteristics, clinical use of CTC counting, and technologies for CTC enrichment, were first introduced. This was followed by discussing the challenges and new perspectives of CTC counting techniques for clinical applications. Finally, the advantages and the recent progress in combining CTC counts with other clinical parameters for clinical applications have been discussed.

Metastasis-Related Signature for Clinically Predicting Prognosis and Tumor Immune Microenvironment of Osteosarcoma Patients

Osteosarcoma is the most prevalent clinical malignant bone tumor in adolescents. The prognosis of metastatic osteosarcoma is still very poor. The aim of our study was to investigate the clinical diagnosis and prognostic significance of metastasis related genes (MRGs) in patients with osteosarcoma. Clinical information and RNA sequencing data with osteosarcoma patients were obtained and set as the training set from UCSC databases. GSE21257 were downloaded and chosen as the verification cohort. An eight gene metastasis related risk signature including MYC, TAC4, ABCA4, GADD45GIP1, TNFRSF21, HERC5, MAGEA11, and PDE1B was built to predict the overall survival of osteosarcoma patients. Based on risk assessments, patients were classified into high- and low-risk groups. The high-risk patients had higher risk score and shorter survival time. ROC curves revealed that this risk signature can accurately predict survival times of osteosarcoma patients at the 1-, 2-, 3-, 4- and 5- year. GSEA revealed that MYC targets, E2F targets, mTORC1 signaling, Wnt /β-catenin signaling and cell cycle were upregulated, and cell adhesion molecules, and primary immunodeficiency were decreased in high-risk group. MRGs were highly linked with the tumor immune microenvironment and ICB response. These results identified that MRGs as a novel prognostic and diagnostic biomarker in osteosarcoma.

Feasibility of mass cytometry proteomic characterisation of circulating tumour cells in head and neck squamous cell carcinoma for deep phenotyping

BACKGROUND

Circulating tumour cells (CTCs) are a potential cancer biomarker, but current methods of CTC analysis at single-cell resolution are limited. Here, we describe high-dimensional single-cell mass cytometry proteomic analysis of CTCs in HNSCC.

METHODS

Parsortix microfluidic-enriched CTCs from 14 treatment-naïve HNSCC patients were analysed by mass cytometry analysis using 41 antibodies. Immune cell lineage, epithelial-mesenchymal transition (EMT), stemness, proliferation and immune checkpoint expression was assessed alongside phosphorylation status of multiple signalling proteins. Patient-matched tumour gene expression and CTC EMT profiles were compared. Standard bulk CTC RNAseq was performed as a baseline comparator to assess mass cytometry data.

RESULTS

CTCs were detected in 13/14 patients with CTC counts of 2-24 CTCs/ml blood. Unsupervised clustering separated CTCs into epithelial, early EMT and advanced EMT groups that differed in signalling pathway activation state. Patient-specific CTC cluster patterns separated into immune checkpoint low and high groups. Patient tumour and CTC EMT profiles differed. Mass cytometry outperformed bulk RNAseq to detect CTCs and characterise cell phenotype.

DISCUSSION

We demonstrate mass cytometry allows high-plex proteomic characterisation of CTCs at single-cell resolution and identify common CTC sub-groups with potential for novel biomarker development and immune checkpoint inhibitor treatment stratification.

Single-cell analysis technologies for cancer research: from tumor-specific single cell discovery to cancer therapy

Single-cell sequencing (SCS) technology is changing our understanding of cellular components, functions, and interactions across organisms, because of its inherent advantage of avoiding noise resulting from genotypic and phenotypic heterogeneity across numerous samples. By directly and individually measuring multiple molecular characteristics of thousands to millions of single cells, SCS technology can characterize multiple cell types and uncover the mechanisms of gene regulatory networks, the dynamics of transcription, and the functional state of proteomic profiling. In this context, we conducted systematic research on SCS techniques, including the fundamental concepts, procedural steps, and applications of scDNA, scRNA, scATAC, scCITE, and scSNARE methods, focusing on the unique clinical advantages of SCS, particularly in cancer therapy. We have explored challenging but critical areas such as circulating tumor cells (CTCs), lineage tracing, tumor heterogeneity, drug resistance, and tumor immunotherapy. Despite challenges in managing and analyzing the large amounts of data that result from SCS, this technique is expected to reveal new horizons in cancer research. This review aims to emphasize the key role of SCS in cancer research and promote the application of single-cell technologies to cancer therapy.

Self-supervised deep clustering of single-cell RNA-seq data to hierarchically detect rare cell populations

Single-cell RNA sequencing (scRNA-seq) is a widely used technique for characterizing individual cells and studying gene expression at the single-cell level. Clustering plays a vital role in grouping similar cells together for various downstream analyses. However, the high sparsity and dimensionality of large scRNA-seq data pose challenges to clustering performance. Although several deep learning-based clustering algorithms have been proposed, most existing clustering methods have limitations in capturing the precise distribution types of the data or fully utilizing the relationships between cells, leaving a considerable scope for improving the clustering performance, particularly in detecting rare cell populations from large scRNA-seq data. We introduce DeepScena, a novel single-cell hierarchical clustering tool that fully incorporates nonlinear dimension reduction, negative binomial-based convolutional autoencoder for data fitting, and a self-supervision model for cell similarity enhancement. In comprehensive evaluation using multiple large-scale scRNA-seq datasets, DeepScena consistently outperformed seven popular clustering tools in terms of accuracy. Notably, DeepScena exhibits high proficiency in identifying rare cell populations within large datasets that contain large numbers of clusters. When applied to scRNA-seq data of multiple myeloma cells, DeepScena successfully identified not only previously labeled large cell types but also subpopulations in CD14 monocytes, T cells and natural killer cells, respectively.

Circulating Tumor Cells as a Promising Tool for Early Detection of Hepatocellular Carcinoma

Liver cancer is a significant contributor to the cancer burden, and its incidence rates have recently increased in almost all countries. Hepatocellular carcinoma (HCC) is the most common type of primary liver cancer and is the second leading cause of cancer-related deaths worldwide. Because of the late diagnosis and lack of efficient therapeutic modality for advanced stages of HCC, the death rate continues to increase by ~2-3% per year. Circulating tumor cells (CTCs) are promising tools for early diagnosis, precise prognosis, and follow-up of therapeutic responses. They can be considered to be an innovative biomarker for the early detection of tumors and targeted molecular therapy. In this review, we briefly discuss the novel materials and technologies applied for the practical isolation and detection of CTCs in HCC. Also, the clinical value of CTC detection in HCC is highlighted.

Advances in novel strategies for isolation, characterization, and analysis of CTCs and ctDNA

Over the past decade, the detection and analysis of liquid biopsy biomarkers such as circulating tumor cells (CTCs) and circulating tumor DNA (ctDNA) have advanced significantly. They have received recognition for their clinical usefulness in detecting cancer at an early stage, monitoring disease, and evaluating treatment response. The emergence of liquid biopsy has been a helpful development, as it offers a minimally invasive, rapid, real-time monitoring, and possible alternative to traditional tissue biopsies. In resource-limited settings, the ideal platform for liquid biopsy should not only extract more CTCs or ctDNA from a minimal sample volume but also accurately represent the molecular heterogeneity of the patient's disease. This review covers novel strategies and advancements in CTC and ctDNA-based liquid biopsy platforms, including microfluidic applications and comprehensive analysis of molecular complexity. We discuss these systems' operational principles and performance efficiencies, as well as future opportunities and challenges for their implementation in clinical settings. In addition, we emphasize the importance of integrated platforms that incorporate machine learning and artificial intelligence in accurate liquid biopsy detection systems, which can greatly improve cancer management and enable precision diagnostics.

Deciphering the Biology of Circulating Tumor Cells through Single-Cell RNA Sequencing: Implications for Precision Medicine in Cancer

Circulating tumor cells (CTCs) hold unique biological characteristics that directly involve them in hematogenous dissemination. Studying CTCs systematically is technically challenging due to their extreme rarity and heterogeneity and the lack of specific markers to specify metastasis-initiating CTCs. With cutting-edge technology, single-cell RNA sequencing (scRNA-seq) provides insights into the biology of metastatic processes driven by CTCs. Transcriptomics analysis of single CTCs can decipher tumor heterogeneity and phenotypic plasticity for exploring promising novel therapeutic targets. The integrated approach provides a perspective on the mechanisms underlying tumor development and interrogates CTCs interactions with other blood cell types, particularly those of the immune system. This review aims to comprehensively describe the current study on CTC transcriptomic analysis through scRNA-seq technology. We emphasize the workflow for scRNA-seq analysis of CTCs, including enrichment, single cell isolation, and bioinformatic tools applied for this purpose. Furthermore, we elucidated the translational knowledge from the transcriptomic profile of individual CTCs and the biology of cancer metastasis for developing effective therapeutics through targeting key pathways in CTCs.

Sequence-Based Platforms for Discovering Biomarkers in Liquid Biopsy of Non-Small-Cell Lung Cancer

Lung cancer detection and monitoring are hampered by a lack of sensitive biomarkers, which results in diagnosis at late stages and difficulty in tracking response to treatment. Recent developments have established liquid biopsies as promising non-invasive methods for detecting biomarkers in lung cancer patients. With concurrent advances in high-throughput sequencing technologies and bioinformatics tools, new approaches for biomarker discovery have emerged. In this article, we survey established and emerging biomarker discovery methods using nucleic acid materials derived from bodily fluids in the context of lung cancer. We introduce nucleic acid biomarkers extracted from liquid biopsies and outline biological sources and methods of isolation. We discuss next-generation sequencing (NGS) platforms commonly used to identify novel biomarkers and describe how these have been applied to liquid biopsy. We highlight emerging biomarker discovery methods, including applications of long-read sequencing, fragmentomics, whole-genome amplification methods for single-cell analysis, and whole-genome methylation assays. Finally, we discuss advanced bioinformatics tools, describing methods for processing NGS data, as well as recently developed software tailored for liquid biopsy biomarker detection, which holds promise for early diagnosis of lung cancer.

ZEB1-activated Notch1 promotes circulating tumor cell migration and invasion in lung squamous cell carcinoma

BACKGROUND

Lung squamous cell carcinoma (LUSC) is recognized as the major subtypes of non-small cell lung cancer (NSCLC). Circulating tumor cells (CTCs) are critical players in tumor metastasis. A molecular profiling of CTCs has previously identified notch receptor 1 (Notch1) as an important mediator in NSCLC. Therefore, we investigate Notch1 roles in LUSC and its related mechanisms.

METHODS

The serum levels of Notch1 were measured by reverse transcription-quantitative polymerase chain reaction (RT-qPCR). The CTCs isolated from blood samples were characterized via an immunofluorescence method. Cell motion was determined using Transwell chambers. The regulatory relationship between Notch1 and zinc finger E-box-binding homeobox 1 (ZEB1) was verified by chromatin immunoprecipitation (ChIP) and luciferase reporter assays. The protein levels were detected by western blotting.

RESULTS

Higher Notch1 expression in patients with LUSC than that in normal controls was observed. Notch1 knockdown inhibited cell motion and epithelial-mesenchymal transition (EMT). ZEB1 transcriptionally activated Notch1. ZEB1 upregulation exacerbated the malignant phenotypes of CTCs.

CONCLUSION

ZEB1-activated Notch1 promotes malignant phenotypes of CTCs in LUSC and indicates poor prognosis.

Spatial RNA sequencing methods show high resolution of single cell in cancer metastasis and the formation of tumor microenvironment

Cancer metastasis often leads to death and therapeutic resistance. This process involves the participation of a variety of cell components, especially cellular and intercellular communications in the tumor microenvironment (TME). Using genetic sequencing technology to comprehensively characterize the tumor and TME is therefore key to understanding metastasis and therapeutic resistance. The use of spatial transcriptome sequencing enables the localization of gene expressions and cell activities in tissue sections. By examining the localization change as well as gene expression of these cells, it is possible to characterize the progress of tumor metastasis and TME formation. With improvements of this technology, spatial transcriptome sequencing technology has been extended from local regions to whole tissues, and from single sequencing technology to multimodal analysis combined with a variety of datasets. This has enabled the detection of every single cell in tissue slides, with high resolution, to provide more accurate predictive information for tumor treatments. In this review, we summarize the results of recent studies dealing with new multimodal methods and spatial transcriptome sequencing methods in tumors to illustrate recent developments in the imaging resolution of micro-tissues.

Liquid biopsy at the frontier in renal cell carcinoma: recent analysis of techniques and clinical application

Renal cell carcinoma (RCC) is a major pathological type of kidney cancer and is one of the most common malignancies worldwide. The unremarkable symptoms of early stages, proneness to postoperative metastasis or recurrence, and low sensitivity to radiotherapy and chemotherapy pose a challenge for the diagnosis and treatment of RCC. Liquid biopsy is an emerging test that measures patient biomarkers, including circulating tumor cells, cell-free DNA/cell-free tumor DNA, cell-free RNA, exosomes, and tumor-derived metabolites and proteins. Owing to its non-invasiveness, liquid biopsy enables continuous and real-time collection of patient information for diagnosis, prognostic assessment, treatment monitoring, and response evaluation. Therefore, the selection of appropriate biomarkers for liquid biopsy is crucial for identifying high-risk patients, developing personalized therapeutic plans, and practicing precision medicine. In recent years, owing to the rapid development and iteration of extraction and analysis technologies, liquid biopsy has emerged as a low cost, high efficiency, and high accuracy clinical detection method. Here, we comprehensively review liquid biopsy components and their clinical applications over the past 5 years. Additionally, we discuss its limitations and predict its future prospects.

Current Status of Circulating Tumor Cells in Head and Neck Squamous Cell Carcinoma: A Review

OBJECTIVE

Circulating tumor cells (CTCs) are found in the blood of patients with cancer, including head and neck squamous cell carcinomas (HNSCCs). The aim is to review the most up-to-date status of CTCs for applications in patients with HNSCC.

DATA SOURCES

English articles in PubMed.

REVIEW METHODS

All the studies on CTCs in HNSCCs in the literature were reviewed.

CONCLUSIONS

There is emerging information on the diagnostic and prognostic value of CTCs in HNSCCs. Evidence also highlights the advantages of various downstream analysis approaches over circulating tumor DNA (ctDNA), such as single-CTC analysis, ex vivo, and in vivo expansion of CTCs. Multiple phenotypic surface markers (cytokeratins, EpCAM, vimentin, etc.), used for CTCs characterization using different immunoassays, could predict disease progression as well as patients' response to treatment efficacy. Immune checkpoint inhibitors' status in CTCs could also provide better insight into treatment. Clonal expansion of CTCs and single-cell analysis of CTCs are the most emerging fields nowadays which may offer an understanding of the mechanism of tumor evolution as well as therapeutic efficacy. Although several clinical trials are ongoing, limitations still exist in the detection and characterization of CTCs. Due to the lack of a gold standard protocol, the sensitivity and specificity of CTC enumeration methods vary.

IMPLICATIONS FOR PRACTICE

Prospective clinical trials are still needed before CTCs can be employed as diagnostic and prognostic markers in the clinical management of patients with HNSCC.

Novel Molecular Aptamer Beacon for the Specific Simultaneous Analysis of Circulating Tumor Cells and Exosomes of Colorectal Cancer Patients

Liquid biopsy provides non-invasive and real-time detection for cancer diagnosis, but the lack of specific markers targeted to liquid biopsy components, such as circulating tumor cells (CTCs) and exosomes, has impeded its effective utilization in clinical settings. W3 is an aptamer, and its target has been previously demonstrated to be a predictor of colorectal cancer (CRC) metastasis. Herein, we developed a W3-based molecular beacon (MAB-W3-3G) to specifically detect CTCs and exosomes derived from CRC patients by modifying the W3 sequence and adding a fluorescent group FAM at the 5' end and a quencher group BHQ1 at the 3' end, resulting in a detectable green fluorescence only in the presence of the target. MAB-W3-3G retained features similar to those of the original W3, including high specificity and affinity for metastatic CRC cells, as well as excellent plasma stability. Notably, W3 target-positive CTCs were visualized, positive exosomes were quantified in CRC patients' whole blood without any sample pretreatment, and both detections could be finished in one step without any routine washing procedures. For CRC, the W3 target-positive CTC enumeration in metastasis was higher than that in non-metastasis (p < 0.01), and the quantitation of positive exosomes was correlated with CRC patients (p < 0.0001). Moreover, the MAB-W3-3G-based simultaneous detection of CTCs and exosomes was proven to have the potential for more precise clinical diagnosis. In conclusion, MAB-W3-3G could detect CTCs and exosomes in the blood samples of tumor patients with simple manipulation, rapid analysis, and high specificity, providing an effective liquid biopsy tool for the prediction of CRC.

Identification and validation of a novel signature based on cell-cell communication in head and neck squamous cell carcinoma by integrated analysis of single-cell transcriptome and bulk RNA-sequencing

Background

The heterogeneous crosstalk between tumor cells and other cells in their microenvironment means a notable difference in clinical outcomes of head and neck squamous cell carcinoma (HNSCC). CD8+ T cells and macrophages are effector factors of the immune system, which have direct killing and phagocytosis effects on tumor cells. How the evolution of their role in the tumor microenvironment influences patients clinically remains a mystery. This study aims to investigate the complex communication networks in the HNSCC tumor immune microenvironment, elucidate the interactions between immune cells and tumors, and establish prognostic risk model.

Methods

20 HNSCC samples single-cell rna sequencing (scRNA-seq) data and bulk rna-seq data were derived from public databases. The "cellchat" R package was used to identify cell-to-cell communication networks and prognostic related genes, and then cell-cell communication (ccc) molecular subtypes were constructed by unsupervised clustering. Kaplan-Meier(K-M) survival analysis, clinical characteristics analysis, immune microenvironment analysis, immune cell infiltration analysis and CD8+T cell differentiation correlation analysis were performed. Finally, the ccc gene signature including APP, ALCAM, IL6, IL10 and CD6 was constructed based on univariate Cox analysis and multivariate Cox regression. Kaplan-Meier analysis and time-dependent receiver operating characteristic (ROC) analysis were used to evaluate the model in the train group and the validation group, respectively.

Results

With CD8+T cells from naive to exhaustion state, significantly decreased expression of protective factor (CD6 gene) is associated with poorer prognosis in patients with HNSCC. The role of macrophages in the tumor microenvironment has been identified as tumor-associated macrophage (TAM), which can promote tumor proliferation and help tumor cells provide more nutrients and channels to facilitate tumor cell invasion and metastasis. In addition, based on the strength of all ccc in the tumor microenvironment, we identified five prognostic ccc gene signatures (cccgs), which were identified as independent prognostic factors by univariate and multivariate analysis. The predictive power of cccgs was well demonstrated in different clinical groups in train and test cohorts.

Conclusion

Our study highlights the propensity for crosstalk between tumors and other cells and developed a novel signature on the basis of a strong association gene for cell communication that has a powerful ability to predict prognosis and immunotherapy response in patients with HNSCC. This may provide some guidance for developing diagnostic biomarkers for risk stratification and therapeutic targets for new therapeutic strategies.

Circulating tumor cells dynamics during chemotherapy predict survival and response in advanced non-small-cell lung cancer patients

Background

Circulating tumor cells (CTCs) are prognostic biomarker in non-small-cell lung cancer (NSCLC). CTCs could also be used as predictor of efficacy of systemic treatments in advanced NSCLC.

Objectives

We described the dynamic changes of CTCs during first-line platinum-based chemotherapy in advanced NSCLC and clarified the correlation between CTC counts and efficacy of chemotherapy.

Design

Chemotherapy is administered and blood specimens are collected at four time points from baseline to disease progression for CTC detection.

Methods

This multicenter prospective study enrolled patients with previously untreated stage III or IV NSCLC fit for standard platinum-based chemotherapy. Bloods were sampled as per standard operating procedures at baseline, cycle 1 and cycle 4 of chemotherapy, and at disease progression for CTC analysis using the CellSearch system.

Results

Among 150 patients enrolled, median overall survival (OS) was 13.8, 8.4, and 7.9 months in patients with CTC^-, KIT^-CTC, and KIT⁺CTC at baseline (p = 0.002). Patients with persistent negative CTC (46.0%) had longer progression-free survival [5.7 months, 95% confidence interval (CI): 5.0-6.5 versus 3.0 months, 0.6-5.4; hazard ratio (HR): 0.34, 95% CI: 0.18-0.67) and OS (13.1 months, 10.9-15.3 versus 5.6 months, 4.1-7.1; HR: 0.17, 0.08-0.36) compared with patients with persistent positive CTC (10.7%), which was not impacted by chemotherapy. Chemotherapy decreased CTC from 36.0% (54/150) to 13.7% (13/95).

Conclusions

CTC persistent presence during treatment represents poor prognosis and resistance to chemotherapy in advanced NSCLC. Chemotherapy could effectively eliminate CTCs. Molecular characterization and the functionalization of CTC will be warranted for further intensive investigation.

Trial registration

NCT01740804.

A narrative review of circulating tumor cells clusters: A key morphology of cancer cells in circulation promote hematogenous metastasis

Circulating tumor cells (CTCs) that survive in the blood are playing an important role in the metastasis process of tumor. In addition, they have become a tool for tumor diagnosis, prognosis and recurrence monitoring. CTCs can exist in the blood as individual cells or as clumps of aggregated cells. In recent years, more and more studies have shown that clustered CTCs have stronger metastasis ability compared to single CTCs. With the deepening of studies, scholars have found that cancer cells can combine not only with each other, but also with non-tumor cells present in the blood, such as neutrophils, platelets, etc. At the same time, it was confirmed that non-tumor cells bound to CTCs maintain the survival and proliferation of cancer cells through a variety of ways, thus promoting the occurrence and development of tumor. In this review, we collected information on tumorigenesis induced by CTC clusters to make a summary and a discussion about them. Although CTC clusters have recently been considered as a key role in the transition process, many characteristics of them remain to be deeply explored. A detailed understanding of their vulnerability can prospectively pave the way for new inhibitors for metastasis.

Clonal barcoding with qPCR detection enables live cell functional analyses for cancer research

Single-cell analysis methods are valuable tools; however, current approaches do not easily enable live cell retrieval. That is a particular issue when further study of cells that were eliminated during experimentation could provide critical information. We report a clonal molecular barcoding method, called SunCatcher, that enables longitudinal tracking and live cell functional analysis. From complex cell populations, we generate single cell-derived clonal populations, infect each with a unique molecular barcode, and retain stocks of individual barcoded clones (BCs). We develop quantitative PCR-based and next-generation sequencing methods that we employ to identify and quantify BCs in vitro and in vivo. We apply SunCatcher to various breast cancer cell lines and combine respective BCs to create versions of the original cell lines. While the heterogeneous BC pools reproduce their original parental cell line proliferation and tumor progression rates, individual BCs are phenotypically and functionally diverse. Early spontaneous metastases can also be identified and quantified. SunCatcher thus provides a rapid and sensitive approach for studying live single-cell clones and clonal evolution, and performing functional analyses.

Clinical significance of chromosomal integrity in gastric cancers

BACKGROUND

A whole-exome or targeted cancer genes panel by next-generation sequencing has been used widely in assisting individualized treatment decisions. Currently, multiple algorithms are developed to estimate DNA copy numbers based on sequencing data, which makes a comprehensive global glance at chromosomal integrity possible. We aim to classify gastric cancers based on chromosomal integrity to guide personalized therapy.

METHODS

We investigated copy number variations (CNV) across the entire genome of 124 gastric carcinomas via exome or targeted sequencing. Chromosomal integrity was classified as chromosomal stability (CS), chromosomal instability (CIN) and intermediate state (CIN/CS) based on CNV results. Chromosomal integrity was correlated to molecular features and clinical characteristics.

RESULTS

According the states of chromosomal integrity, gastric carcinomas can be stratified into two cohorts: CS and CIN. Our results showed a significant relationship between CIN status and TP53 mutation, but not RB1, phosphatase and tensin homolog (PTEN), or other reported DNA damage repair genes. The mutation frequency of the TP53 gene had great relevance. Our study initially revealed clinical significance of chromosomal integrity that CIN patients were prone to HER2-positive and mucinous adenocarcinoma, while CS patients were a diffuse subtype and poorly differentiated but had longer overall survival.

CONCLUSIONS

We classified gastric carcinomas into two states of chromosomal integrity with clinical implications. The dichotomy is applicable to clinical transformation. We proposed that classifying gastric cancers based on chromosomal integrity would enable us to achieve personalized therapy for patients and may be beneficial to patient stratification in future clinical trials.

Recent advances in targeted drug delivery systems for resistant colorectal cancer

Colorectal cancer (CRC) is one of the deadliest cancers in the world, the incidences and morality rate are rising and poses an important threat to the public health. It is known that multiple drug resistance (MDR) is one of the major obstacles in CRC treatment. Tumor microenvironment plus genomic instability, tumor derived exosomes (TDE), cancer stem cells (CSCs), circulating tumor cells (CTCs), cell-free DNA (cfDNA), as well as cellular signaling pathways are important issues regarding resistance. Since non-targeted therapy causes toxicity, diverse side effects, and undesired efficacy, targeted therapy with contribution of various carriers has been developed to address the mentioned shortcomings. In this paper the underlying causes of MDR and then various targeting strategies including exosomes, liposomes, hydrogels, cell-based carriers and theranostics which are utilized to overcome therapeutic resistance will be described. We also discuss implication of emerging approaches involving single cell approaches and computer-aided drug delivery with high potential for meeting CRC medical needs.

The Janus of Protein Corona on nanoparticles for tumor targeting, immunotherapy and diagnosis

The therapeutics based on nanoparticles (NPs) are considered as the promising strategy for tumor detection and treatment. However, one of the most challenges is the adsorption of biomolecules on NPs after their exposition to biological medium, leading unpredictable in vivo behaviors. The interactions caused by protein corona (PC) will influence the biological fate of NPs in either negative or positive ways, including (i) blood circulation, accumulation and penetration of NPs at targeting sites, and further cellular uptake in tumor targeting delivery; (ii) interactions between NPs and receptors on immune cells for immunotherapy. Besides, PC on NPs could be utilized as new biomarker in tumor diagnosis by identifying the minor change of protein concentration led by tumor growth and invasion in blood. Herein, the mechanisms of these PC-mediated effects will be introduced. Moreover, the recent advances about the strategies will be reviewed to reduce negative effects caused by PC and/or utilize positive effects of PC on tumor targeting, immunotherapy and diagnosis, aiming to provide a reasonable perspective to recognize PC with their applications.

Recent advances and application of whole genome amplification in molecular diagnosis and medicine

Whole genome amplification (WGA) is a technology for non-selective amplification of the whole genome sequence, first appearing in 1992. Its primary purpose is to amplify and reflect the whole genome of trace tissues and single cells without sequence bias and to provide sufficient DNA template for subsequent multigene and multilocus analysis, along with comprehensive genome research. WGA provides a method to obtain a large amount of genetic information from a small amount of DNA and provides a valuable tool for preserving limited samples in molecular biology. WGA technology is especially suitable for forensic identification and genetic disease research, along with new technologies such as next-generation sequencing (NGS). In addition, WGA is also widely used in single-cell sequencing. Due to the small amount of DNA in a single cell, it is often unable to meet the amount of samples needed for sequencing, so WGA is generally used to achieve the amplification of trace samples. This paper reviews WGA methods based on different principles, summarizes both amplification principle and amplification quality, and discusses the application prospects and challenges of WGA technology in molecular diagnosis and medicine.

Single-Cell RNA-Seq Reveals the Promoting Role of Ferroptosis Tendency During Lung Adenocarcinoma EMT Progression

Epithelial-mesenchymal transition (EMT) and ferroptosis are two important processes in biology. In tumor cells, they are intimately linked. We used single-cell RNA sequencing to investigate the regulatory connection between EMT and ferroptosis tendency in LUAD epithelial cells. We used Seurat to construct the expression matrix using the GEO dataset GSE131907 and extract epithelial cells. We found a positive correlation between the trends of EMT and ferroptosis tendency. Then we used SCENIC to analyze differentially activated transcription factors and constructed a molecular regulatory directed network by causal inference. Some ferroptosis markers (GPX4, SCP2, CAV1) were found to have strong regulatory effects on EMT. Cell communication networks were constructed by iTALK and implied that Ferro_High_EMT_High cells have a higher expression of SDC1, SDC4, and activation of LGALS9-HARVCR2 pathways. By deconvolution of bulk sequencing, the results of CIBERSORTx showed that the co-occurrence of ferroptosis tendency and EMT may lead to tumor metastasis and non-response to immunotherapy. Our findings showed there is a strong correlation between ferroptosis tendency and EMT. Ferroptosis may have a promotive effect on EMT. High propensities of ferroptosis and EMT may lead to poor prognosis and non-response to immunotherapy.

Single-Cell RNA Sequencing Reveals Multiple Pathways and the Tumor Microenvironment Could Lead to Chemotherapy Resistance in Cervical Cancer

Background

Cervical cancer is one of the most common gynecological cancers worldwide. The tumor microenvironment significantly influences the therapeutic response and clinical outcome. However, the complex tumor microenvironment of cervical cancer and the molecular mechanisms underlying chemotherapy resistance are not well studied. This study aimed to comprehensively analyze cells from pretreated and chemoresistant cervical cancer tissues to generate a molecular census of cell populations.

Methods

Biopsy tissues collected from patients with cervical squamous cell carcinoma, cervical adenocarcinoma, and chronic cervicitis were subjected to single-cell RNA sequencing using the 10× Genomics platform. Unsupervised clustering analysis of cells was performed to identify the main cell types, and important cell clusters were reclustered into subpopulations. Gene expression profiles and functional enrichment analysis were used to explore gene expression and functional differences between cell subpopulations in cervicitis and cervical cancer samples and between chemoresistant and chemosensitive samples.

Results

A total of 24,371 cells were clustered into nine separate cell types, including immune and non-immune cells. Differentially expressed genes between chemoresistant and chemosensitive patients enriched in the phosphoinositide 3-kinase (PI3K)/AKT pathway were involved in tumor development, progression, and apoptosis, which might lead to chemotherapy resistance.

Conclusions

Our study provides a comprehensive overview of the cancer microenvironment landscape and characterizes its gene expression and functional difference in chemotherapy resistance. Consequently, our study deepens the insights into cervical cancer biology through the identification of gene markers for diagnosis, prognosis, and therapy.

Circulating tumor cells: biology and clinical significance

Circulating tumor cells (CTCs) are tumor cells that have sloughed off the primary tumor and extravasate into and circulate in the blood. Understanding of the metastatic cascade of CTCs has tremendous potential for the identification of targets against cancer metastasis. Detecting these very rare CTCs among the massive blood cells is challenging. However, emerging technologies for CTCs detection have profoundly contributed to deepening investigation into the biology of CTCs and have facilitated their clinical application. Current technologies for the detection of CTCs are summarized herein, together with their advantages and disadvantages. The detection of CTCs is usually dependent on molecular markers, with the epithelial cell adhesion molecule being the most widely used, although molecular markers vary between different types of cancer. Properties associated with epithelial-to-mesenchymal transition and stemness have been identified in CTCs, indicating their increased metastatic capacity. Only a small proportion of CTCs can survive and eventually initiate metastases, suggesting that an interaction and modulation between CTCs and the hostile blood microenvironment is essential for CTC metastasis. Single-cell sequencing of CTCs has been extensively investigated, and has enabled researchers to reveal the genome and transcriptome of CTCs. Herein, we also review the clinical applications of CTCs, especially for monitoring response to cancer treatment and in evaluating prognosis. Hence, CTCs have and will continue to contribute to providing significant insights into metastatic processes and will open new avenues for useful clinical applications.