Single-Cell Sequencing-Enabled Hexokinase 2 Assay for Noninvasive Bladder Cancer Diagnosis and Screening by Detecting Rare Malignant Cells in Urine

Unlocking the potential of tumor-derived DNA in urine for cancer detection: methodological challenges and opportunities

High cancer mortality rates and the rising cancer burden worldwide drive the development of innovative methods in order to advance cancer diagnostics. Urine contains a viable source of tumor material and allows for self-collection from home. Biomarker testing in this liquid biopsy represents a novel approach that is convenient for patients and can be effective in detecting cancer at a curable stage. Here, we set out to provide a detailed overview of the rationale behind urine-based cancer detection, with a focus on non-urological cancers, and its potential for cancer diagnostics. Moreover, evolving methodological challenges and untapped opportunities for urine biomarker testing are discussed, particularly emphasizing DNA methylation of tumor-derived cell-free DNA. We also provide future recommendations for technical advancements in urine-based cancer detection and elaborate on potential mechanisms involved in the transrenal transport of cell-free DNA.

Liquid biopsy in urothelial carcinoma: Detection techniques and clinical applications

The types of urothelial carcinoma (UC) include urothelial bladder cancer and upper tract urothelial carcinoma. Current diagnostic techniques cannot meet the needs of patients. Liquid biopsy is an accurate method of determining the molecular profile of UC and is a cutting-edge and popular technique that is expected to complement existing detection techniques and benefit patients with UC. Circulating tumor cells, cell-free DNA, cell-free RNA, extracellular vesicles, proteins, and metabolites can be found in the blood, urine, or other bodily fluids and are examined during liquid biopsies. This article focuses on the components of liquid biopsies and their clinical applications in UC. Liquid biopsies have tremendous potential in multiple aspects of precision oncology, from early diagnosis and treatment monitoring to predicting prognoses. They may therefore play an important role in the management of UC and precision medicine.

Glucose Metabolism Reprogramming in Bladder Cancer: Hexokinase 2 (HK2) as Prognostic Biomarker and Target for Bladder Cancer Therapy

Proliferating cancer cells are able to reprogram their energy metabolism, favouring glycolysis even in the presence of oxygen and fully functioning mitochondria. Research is needed to validate the glycolysis-related proteins as prognostic/predictive biomarkers in urothelial bladder carcinoma (UBC), a malignancy tagged by high recurrence rates and poor response to chemotherapy. Here, we assessed GLUT1, HK2, PFKL, PKM2, phospho-PDH, and LDHA immunoexpression in 76 UBC samples, differentiating among urothelial, fibroblast, and endothelial cells and among normoxic versus hypoxic areas. We additionally studied the functional effects of the HK2 inhibitor 2-deoxy-D-glucose (2DG) in "in vitro" and "in vivo" preclinical UBC models. We showed that the expression of the glycolysis-related proteins is associated with UBC aggressiveness and poor prognosis. HK2 remained as an independent prognostic factor for disease-free and overall survival. 2DG decreased the UBC cell's viability, proliferation, migration, and invasion; the inhibition of cell cycle progression and apoptosis occurrence was also verified. A significant reduction in tumour growth and blood vessel formation upon 2DG treatment was observed in the chick chorioallantoic membrane assay. 2DG potentiated the cisplatin-induced inhibition of cell viability in a cisplatin-resistant subline. This study highlights HK2 as a prognostic biomarker for UBC patients and demonstrates the potential benefits of using 2DG as a glycolysis inhibitor. Future studies should focus on integrating 2DG into chemotherapy design, as an attempt to overcome cisplatin resistance.

Single-cell sequencing technologies in bladder cancer research: Applications and challenges

Bladder cancer is among the most common malignant tumors with highly heterogeneous molecular characteristics. Despite advancements of the available therapeutic options, several bladder cancer patients exhibit unsatisfactory clinical outcomes. The lack of specific biomarkers for effective targeted therapy or immunotherapy remains a major obstacle in treating bladder cancer. The rapid development of single-cell techniques is transforming our understanding of the intra-tumoral heterogeneity, thereby providing us with a powerful high-throughput sequencing tool that can reveal tumorigenesis, progression, and invasion in bladder tumors. In this review, we summarise and discuss how single-cell sequencing technologies have been applied in bladder cancer research, to advance our collective knowledge on the heterogeneity of bladder tumor cells, as well as to provide new insights into the complex ecosystem of the tumor microenvironment. The application of single-cell approaches also uncovers the therapeutic resistance mechanism in bladder cancer and facilitates the detection of urinary-exfoliated tumor cells. Moreover, benefiting from the powerful technical advantages of single-cell techniques, several key therapeutic targets and prognostic models of bladder cancer have been identified. It is hoped that this paper can provide novel insights into the precision medicine of bladder cancer.

The Role of Myeloid Cells in Hepatotoxicity Related to Cancer Immunotherapy

Simple Summary

Immune-modulating cancer treatments have proved to be highly effective in a wide range of tumour types. They interrupt the usual communication between cells in the immune system, encouraging them to become more active in identifying and destroying cancer cells. Although these therapies are very successful in treating cancer, patients frequently experience liver injury as a side effect related to over activation of the immune system. If cancer patients develop this side effect, they need to stop their cancer therapy and be given strong immunosuppressants. Researchers are now working on understanding the mechanisms involved in the development of liver inflammation. In this review we will summarise findings identifying classes of immune cells that are of particular importance in this context and highlight ways in which we can use this knowledge to improve the safety of these new cancer drugs.

Abstract

Drug-related hepatotoxicity is an emerging clinical challenge with the widening use of immunotherapeutic agents in the field of oncology. This is an important complication to consider as more immune oncological targets are being identified to show promising results in clinical trials. The application of these therapeutics may be complicated by the development of immune-related adverse events (irAEs), a serious limitation often requiring high-dose immunosuppression and discontinuation of cancer therapy. Hepatoxicity presents one of the most frequently encountered irAEs and a better understanding of the underlying mechanism is crucial for the development of alternative therapeutic interventions. As a novel drug side effect, the immunopathogenesis of the condition is not completely understood. In the liver, myeloid cells play a central role in the maintenance of homeostasis and promotion of inflammation. Recent research has identified myeloid cells to be associated with hepatic adverse events of various immune modulatory monoclonal antibodies. In this review article, we provide an overview of the role of myeloid cells in the immune pathogenesis during hepatoxicity related to cancer immunotherapies and highlight potential treatment options.

An Overview on Single-Cell Technology for Hepatocellular Carcinoma Diagnosis

Hepatocellular carcinoma is a primary liver cancer caused by the accumulation of genetic mutation patterns associated with epidemiological conditions. This lethal malignancy exhibits tumor heterogeneity, which is considered as one of the main reasons for drug resistance development and failure of clinical trials. Recently, single-cell technology (SCT), a new advanced sequencing technique that analyzes every single cell in a tumor tissue specimen, aids complete insight into the genetic heterogeneity of cancer. This helps in identifying and assessing rare cell populations by analyzing the difference in gene expression pattern between individual cells of single biopsy tissue which normally cannot be identified from pooled cell gene expression pattern (traditional sequencing technique). Thus, SCT improves the clinical diagnosis, treatment, and prognosis of hepatocellular carcinoma as the limitations of other techniques impede this cancer research progression. Application of SCT at the genomic, transcriptomic, and epigenomic levels to promote individualized hepatocellular carcinoma diagnosis and therapy. The current review has been divided into ten sections. Herein we deliberated on the SCT, hepatocellular carcinoma diagnosis, tumor microenvironment analysis, single-cell genomic sequencing, single-cell transcriptomics, single-cell omics sequencing for biomarker development, identification of hepatocellular carcinoma origination and evolution, limitations, challenges, conclusions, and future perspectives.

Single-Cell Genomics-Based Molecular Algorithm for Early Cancer Detection

As one of the prime applications of liquid biopsy, the detection of tumor-derived whole cells and molecular markers is enabled in a noninvasive means before symptoms or hints from imaging procedures used for cancer screening. However, liquid biopsy is not a diagnostic test of malignant diseases per se because it fails to establish a definitive cancer diagnosis. Although single-cell genomics provides a genome-wide genetic alternation landscape, it is technologically challenging to confirm cell malignancy of a suspicious cell in body fluids due to unknown technical noise of single-cell sequencing and genomic variation among cancer cells, especially when tumor tissues are unavailable for sequencing as the reference. To address this challenge, we report a molecular algorithm, named scCancerDx, for confirming cell malignancy based on single-cell copy number alternation profiles of suspicious cells from body fluids, leading to a definitive cancer diagnosis. The scCancerDx algorithm has been trained with normal cells and cancer cell lines and validated with single tumor cells disassociated from clinical samples. The established scCancerDx algorithm then validates hexokinase 2 (HK2) as an efficient metabolic function-associated marker of identifying disseminated tumor cells in different body fluids across many cancer types. The HK2-based test, together with scCancerDx, has been investigated for the early detection of bladder cancer (BC) at a preclinical phase by detecting high glycolytic HK2^high tumor cells in urine. Early BC detection improves patient prognosis and avoids radical resection for enhancing life quality.

Application and prospects of single cell sequencing in tumors

Cancer is an intricate disease with inherent intra-tumor heterogeneity at the cellular level because of genetic changes and environmental differences. Cellular heterogeneity exists even within the same tumor type. Small deviations in a genome or transcriptome can lead to significant differences in function. Conventional bulk population sequencing, which produces admixed populations of cells, can only provide an average expression signal for one cell population, ignoring differences between individual cells. Important advances in sequencing have been made in recent years. Single cell sequencing starts in a single cell, thereby increasing our capability to characterize intratumor heterogeneity. This technology has been used to analyze genetic variation, specific metabolic activity, and evolutionary processes in tumors, which may help us understand tumor occurrence and development and improve our understanding of the tumor microenvironment. In addition, it provides a theoretical basis for the development of clinical treatments, especially for personalized medicine. In this article, we briefly introduce Single cell sequencing technology, summarize the application of Single cell sequencing to study the tumor microenvironment, as well as its therapeutic application in different clinical procedures.

Current Development and Application of Anaerobic Glycolytic Enzymes in Urothelial Cancer

Urothelial cancer is a malignant tumor with metastatic ability and high mortality. Malignant tumors of the urinary system include upper tract urothelial cancer and bladder cancer. In addition to typical genetic alterations and epigenetic modifications, metabolism-related events also occur in urothelial cancer. This metabolic reprogramming includes aberrant expression levels of genes, metabolites, and associated networks and pathways. In this review, we summarize the dysfunctions of glycolytic enzymes in urothelial cancer and discuss the relevant phenotype and signal transduction. Moreover, we describe potential prognostic factors and risks to the survival of clinical cancer patients. More importantly, based on several available databases, we explore relationships between glycolytic enzymes and genetic changes or drug responses in urothelial cancer cells. Current advances in glycolysis-based inhibitors and their combinations are also discussed. Combining all of the evidence, we indicate their potential value for further research in basic science and clinical applications.

Immunotherapy in the Treatment of Urothelial Bladder Cancer: Insights From Single-Cell Analysis

Urothelial bladder cancer (UBC) is a global challenge of public health with limited therapeutic options. Although the emergence of cancer immunotherapy, most notably immune checkpoint inhibitors, represents a major breakthrough in the past decade, many patients still suffer from unsatisfactory clinical outcome. A thorough understanding of the fundamental cellular and molecular mechanisms responsible for antitumor immunity may lead to optimized treatment guidelines and new immunotherapeutic strategies. With technological developments and protocol refinements, single-cell approaches have become powerful tools that provide unprecedented insights into the kaleidoscopic tumor microenvironment and intricate cell-cell communications. In this review, we summarize recent applications of single-cell analysis in characterizing the UBC multicellular ecosystem, and discuss how to leverage the high-resolution information for more effective immune-based therapies.

Single-cell sequencing technology in tumor research

Tumor heterogeneity is a key characteristic of malignant tumors and a significant obstacle in cancer treatment and research. Although bulk tissue sequencing has wide coverage and high accuracy, it can only represent the dominant cell signal information of each sample, while masking the unique gene expression of rare cells; therefore it cannot represent genes that are unstable within a subgroup, but unchanged in a majority of cells. With the progress of genomic technology, the emergence of single-cell sequencing (SCS) has effectively solved the above problem. Genetic, transcriptomic and epigenetic sequencing at the single-cell level provides an important basis for us to correctly classify the cell subsets of heterogeneous tumor populations and to reveal the process of complex changes in tumor cells at the molecular level. Single-cell sequencing technology has been applied to the field of cancer, revealing exciting discoveries in the potential mechanisms of tumor driver gene mutation, clonal evolution, invasion and metastasis. It also provides favorable conditions for developing new tumor biomarkers and providing more accurate and individualized targeted tumor therapy. Herein, we review the steps and methods of single-cell sequencing and highlight the application of SCS in tumor diagnosis and clinical treatment.