Detection of Urothelial Bladder Carcinoma via Microfluidic Immunoassay and Single-Cell DNA Copy-Number Alteration Analysis of Captured Urinary-Exfoliated Tumor Cells

A novel in vitro prognostic model of bladder cancer based on urine-derived living tumor cells

Bladder cancer (BLCA) remains a difficult malignancy to manage because of its high recurrence, intense follow-up, and invasive diagnostic and treatment techniques. Immune checkpoint inhibitors (ICIs) have forged a new direction for the treatment of BLCA, but it is currently challenging to predict whether an individual patient will be sensitive to ICIs. We collected 43 urine/tumor samples from BLCA patients for primary bladder cancer cells (BCCs) culturing using our previously reported BCC culture platform. We used flow cytometry (FCM) to measure the expression levels of Programmed Death-Ligand 1 (PD-L1) on BCCs before and after interferon-gamma (IFN-γ) treatment and found that PD-L1 expression and the sensitivities to IFN-γ varied among patients. RNA-sequencing, western blotting, and programmed death-1 (PD-1) binding assays confirmed that the BCC FCM-based PD-L1 detection platform (BC-PD-L1) was reliable and was not hindered by the  glycosylation of PD-L1. In the subsequent retrospective study, we found that IFN-γ-stimulated PD-L1 (sPD-L1) expression on BCCs detected by BC-PD-L1 could predict the prognosis of BLCA patients. Importantly, the prognostic value was similar or even better in urine-derived BC-PD-L1 (UBC-PD-L1). Transcriptome analysis showed that BCCs with high sPD-L1 tended to enrich genes associated with the collagen-containing extracellular matrix, cell-cell adhesion, and positive regulation of the immune system. In addition, the UBC-PD-L1 also exhibited predictive value for ICI response in BLCA patients. In conclusion, as a novel personalized urine-detection method, UBC-PD-L1 may provide a rapid, accurate, and non-invasive tool for monitoring tumor progression, predicting therapeutic responses, and helping improve BLCA clinical treatment in future.

Lab-on-a-chip systems for cancer biomarker diagnosis

Lab-on-a-chip (LOC) or micro total analysis system is one of the microfluidic technologies defined as the adaptation, miniaturization, integration, and automation of analytical laboratory procedures into a single instrument or "chip". In this article, we review developments over the past five years in the application of LOC biosensors for the detection of different types of cancer. Microfluidics encompasses chemistry and biotechnology skills and has revolutionized healthcare diagnosis. Superior to traditional cell culture or animal models, microfluidic technology has made it possible to reconstruct functional units of organs on chips to study human diseases such as cancer. LOCs have found numerous biomedical applications over the past five years, including integrated bioassays, cell analysis, metabolomics, drug discovery and delivery systems, tissue and organ physiology and disease modeling, and personalized medicine. This review provides an overview of the latest developments in microfluidic-based cancer research, with pros, cons, and prospects.

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.

Label-free detection of bladder cancer and kidney cancer plasma based on SERS and multivariate statistical algorithm

In this study, we mainly aimed to investigate the diagnostic potential of surface-enhanced Raman spectroscopy for bladder cancer and kidney cancer which are the most common cancers of the urinary system, and evaluate the classification ability of three statistical algorithms: principal component analysis-linear discriminate analysis (PCA-LDA), partial least square-random forest (PLS-RF), and partial least square-support vector machine (PLS-SVM). The plasma of 26 bladder cancer patients, 38 kidney cancer patients and 39 normal subjects was mixed with the same volume of silver nanoparticles, respectively, and then high-quality SERS signal was obtained. The SERS spectra in the range of 400-1800 cm^-1 were compared and analyzed. There were some significant differences in SERS peak intensity, which may reflect the changes in the content of some biomacromolecules in the plasma of cancer patients. Based on the three algorithms of PCA-LDA, PLS-RF and PLS-SVM, the classification accuracy of SERS spectra of plasma from cancer patients and normal subjects was 98.1%, 100% and 100%, respectively. In addition, the classification accuracy of the three diagnostic algorithms to classify the SERS spectra of bladder cancer and kidney cancer was 81.3%, 91.7%, and 98.4%, respectively. This exploratory work demonstrates that SERS combined with PLS-SVM algorithm has superior performance for clinical screening of bladder cancer and kidney cancer through peripheral plasma.

Microfluidics-Based Urine Biopsy for Cancer Diagnosis: Recent Advances and Future Trends

Urine biopsy, allowing for the detection, analysis and monitoring of numerous cancer-associated urinary biomarkers to provide insights into cancer occurrence, progression and metastasis, has emerged as an attractive liquid biopsy strategy with enormous advantages over traditional tissue biopsy, such as noninvasiveness, large sample volume, and simple sampling operation. Microfluidics enables precise manipulation of fluids in a tiny chip and exhibits outstanding performance in urine biopsy owing to its minimization, low cost, high integration, high throughput and low sample consumption. Herein, we review recent advances in microfluidic techniques employed in urine biopsy for cancer detection. After briefly summarizing the major urinary biomarkers used for cancer diagnosis, we provide an overview of the typical microfluidic techniques utilized to develop urine biopsy devices. Some prospects along with the major challenges to be addressed for the future of microfluidic-based urine biopsy are also discussed.

Non-invasive diagnosis and surveillance of bladder cancer with driver and passenger DNA methylation in a prospective cohort study

BACKGROUND

State-of-art non-invasive diagnosis processes for bladder cancer (BLCA) harbour shortcomings such as low sensitivity and specificity, unable to distinguish between high- (HG) and low-grade (LG) tumours, as well as inability to differentiate muscle-invasive bladder cancer (MIBC) and non-muscle-invasive bladder cancer (NMIBC). This study investigates a comprehensive characterization of the entire DNA methylation (DNAm) landscape of BLCA to determine the relevant biomarkers for the non-invasive diagnosis of BLCA.

METHODS

A total of 304 samples from 224 donors were enrolled in this multi-centre, prospective cohort study. BLCA-specific DNAm signature discovery was carried out with genome-wide bisulfite sequencing in 32 tumour tissues and 12 normal urine samples. A targeted sequencing assay for BLCA-specific DNAm signatures was developed to categorize tumour tissue against normal urine, or MIBC against NMIBC. Independent validation was performed with targeted sequencing of 259 urine samples in a double-blinded manner to determine the clinical diagnosis and prognosis value of DNAm-based classification models. Functions of genomic region harbouring BLCA-specific DNAm signature were validated with biological assays. Concordances of pathology to urine tumour DNA (circulating tumour DNA [ctDNA]) methylation, genomic mutations or other state-of-the-art diagnosis methods were measured.

RESULTS

Genome-wide DNAm profile could accurately classify LG tumour from HG tumour (LG NMIBC vs. HG NMIBC: p = .038; LG NMIBC vs. HG MIBC, p = .00032; HG NMIBC vs. HG MIBC: p = .82; Student's t-test). Overall, the DNAm profile distinguishes MIBC from NMIBC and normal urine. Targeted-sequencing-based DNAm signature classifiers accurately classify LG NMIBC tissues from HG MIBC and could detect tumours in urine at a limit of detection of less than .5%. In tumour tissues, DNAm accurately classifies pathology, thus outperforming genomic mutation or RNA expression profiles. In the independent validation cohort, pre-surgery urine ctDNA methylation outperforms fluorescence in situ hybridization (FISH) assay to detect HG BLCA (n = 54) with 100% sensitivity (95% CI: 82.5%-100%) and LG BLCA (n = 26) with 62% sensitivity (95% CI: 51.3%-72.7%), both at 100% specificity (non-BLCA: n = 72; 95% CI: 84.1%-100%). Pre-surgery urine ctDNA methylation signature correlates with pathology and predicts recurrence and metastasis. Post-surgery urine ctDNA methylation (n = 61) accurately predicts recurrence-free survival within 180 days, with 100% accuracy.

CONCLUSION

With the discovery of BLCA-specific DNAm signatures, targeted sequencing of ctDNA methylation outperforms FISH and DNA mutation to detect tumours, predict recurrence and make prognoses.

Single Cell Mass Spectrometry with a Robotic Micromanipulation System for Cell Metabolite Analysis

ObjectiveThe increasing demand for unraveling cellular heterogeneity has boosted single cell metabolomics studies. However, current analytical methods are usually labor-intensive and hampered by lack of accuracy and efficiency.

METHODS

we developed a first-ever automated single cell mass spectrometry system (named SCMS) that facilitated the metabolic profiling of single cells. In particular, extremely small droplets of sub nano-liter were generated to extract the single cells, and the underlying mechanism was verified theoretically and experimentally. This was crucial to minimize the dilution of the trace cellular contents and enhance the analytical sensitivity. Based on the precise 3D positioning of the pipette tip, we established a visual servoing robotic micromanipulation platform on which single cells were sequentially extracted, aspirated, and ionized, followed by the mass spectrometry analyses.

RESULTS

With the SCMS system, inter-operator variability was eliminated and working efficiency was improved. The performance of the SCMS system was validated by the experiments on bladder cancer cells. MS and MS2 analyses of single cells enable us to identify several cellular metabolites and the underlying inter-cell heterogeneity.

CONCLUSION

In contrast to traditional methods, the SCMS system functions without human intervention and realizes a robust single cell metabolic analysis.

SIGNIFICANCE

the SCMS system upgrades the way how single cell metabolites were analyzed, and has the potential to be a powerful tool for single cell metabolomics studies.

Microfluidic Assaying of Circulating Tumor Cells and Its Application in Risk Stratification of Urothelial Bladder Cancer

Bladder cancer is characterized by its frequent recurrence and progression. Effective treatment strategies need to be based on an accurate risk stratification, in which muscle invasiveness and tumor grade represent the two most important factors. Traditional imaging techniques provide preliminary information about muscle invasiveness but are lacking in terms of accuracy. Although as the gold standard, pathological biopsy is only available after the surgery and cannot be performed longitudinally for long-term surveillance. In this work, we developed a microfluidic approach that interrogates circulating tumor cells (CTCs) in the peripheral blood of bladder cancer patients to reflect the risk stratification of the disease. In a cohort of 48 bladder cancer patients comprising 33 non-muscle invasive bladder cancer (NMIBC) cases and 15 muscle invasive bladder cancer (MIBC) cases, the CTC count was found to be considerably higher in the MIBC group compared with the NMIBC group (4.67 vs. 1.88 CTCs/3 mL, P=0.019), and was significantly higher in high-grade bladder cancer patients verses low-grade bladder cancer patients (3.69 vs. 1.18 CTCs/3mL, P=0.024). This microfluidic assay of CTCs is believed to be a promising complementary tool for the risk stratification of bladder cancer.

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.

Microtechnology-enabled filtration-based liquid biopsy: challenges and practical considerations

Liquid biopsy, an important enabling technology for early diagnosis and dynamic monitoring of cancer, has drawn extensive attention in the past decade. With the rapid developments of microtechnology, it has been possible to manipulate cells at the single-cell level, which dramatically improves the liquid biopsy capability. As the microtechnology-enabled liquid biopsy matures from proof-of-concept demonstrations towards practical applications, a main challenge it is facing now is to process clinical samples which are usually of a large volume while containing very rare targeted cells in complex backgrounds. Therefore, a high-throughput liquid biopsy which is capable of processing liquid samples with a large volume in a reasonable time along with a high recovery rate of rare targeted cells from complex clinical liquids is in high demand. Moreover, the purity, viability and release feasibility of recovered targeted cells are the other three key impact factors requiring careful considerations. To date, among the developed techniques, micropore-type filtration has been acknowledged as the most promising solution to address the aforementioned challenges in practical applications. However, the presently reported studies about micropore-type filtration are mostly based on trial and error for device designs aiming at different cancer types, which requires lots of efforts. Therefore, there is an urgent need to investigate and elaborate the fundamental theories of micropore-type filtration and key features that influence the working performances in the liquid biopsy of real clinical samples to promote the application efficacy in practical applications. In this review, the state of the art of microtechnology-enabled filtration is systematically and comprehensively summarized. Four key features of the filtration, including throughput, purity, viability and release feasibility of the captured targeted cells, are elaborated to provide the guidelines for filter designs. The recent progress in the filtration mode modulation and sample standardization to improve the filtration performance of real clinical samples is also discussed. Finally, this review concludes with prospective views for future developments of filtration-based liquid biopsy to promote its application efficacy in clinical practice.

Artificial intelligence to improve cytology performances in bladder carcinoma detection: results of the VisioCyt test

OBJECTIVE

To explore the utility of artificial intelligence (AI) using the VisioCyt® test (VitaDX International, Rennes, France) to improve diagnosis of bladder carcinoma using voided urine cytology.

PATIENTS AND METHODS

A national prospective multicentre trial (14 centres) was conducted on 1360 patients, divided in two groups. The first group included bladder carcinoma diagnosis with different histological grades and stages, and the second group included control patients based on negative cystoscopy and cytology results. The first step of this VISIOCYT1 trial focussed on algorithm development and the second step on validating this algorithm. A total of 598 patients were included in this first step, 449 patients with bladder tumours (219 high-grade and 230 low-grade) and 149 as negative controls. The VisioCyt test was compared to voided urine cytology performed by experienced uro-pathologists from each centre.

RESULTS

Overall sensitivity was highly improved by the VisioCyt test compared to cytology (84.9% vs 43%). For high-grade tumours the VisioCyt test sensitivity was 92.6% vs 61.1% for the uro-pathologists. Regarding low-grade tumours, VisioCyt test sensitivity was 77% vs 26.3% for the uro-pathologists.

CONCLUSION

In comparison to routine cytology, the results of the first phase of the VISIOCYT1 trial show very clear progress in terms of sensitivity, which is particularly visible and interesting for low-grade tumours. If the validation cohort confirms these results, it could lead to the VisioCyt test being considered as a very useful aid for pathologists. Moreover, as this test is in fact software based on AI, it should become more and more efficient as more data are collected.

Biomarkers for Precision Urothelial Carcinoma Diagnosis: Current Approaches and the Application of Single-Cell Technologies

Simple Summary

Urothelial carcinoma (UC) is the most frequently diagnosed cancer of the urinary tract and is ranked the sixth most diagnosed cancer in men worldwide. About 70–75% of newly diagnosed UCs are non-invasive or low grade. Different tests such as urine cytology and cystoscopy are used to detect UC. If abnormal tissue is found during cystoscopy, then a biopsy will be performed. Cytology has low sensitivity for low-grade cancer while cystoscopy is invasive and costly. Detecting UC early improves the chances of treatment success. Therefore, many researchers have painstakingly identified urine biological markers for non-invasive UC diagnosis. In this review, we summarize some of the latest and most promising biological markers (including FDA-approved and investigational markers). We also discuss some new technologies that can aid research efforts in biological marker discovery for early UC detection.

Abstract

Urothelial carcinoma (UC) is the most frequent malignancy of the urinary system and is ranked the sixth most diagnosed cancer in men worldwide. Around 70–75% of newly diagnosed UC manifests as the non-muscle invasive bladder cancer (NMIBC) subtype, which can be treated by a transurethral resection of the tumor. However, patients require life-long monitoring due to its high rate of recurrence. The current gold standard for UC diagnosis, prognosis, and disease surveillance relies on a combination of cytology and cystoscopy, which is invasive, costly, and associated with comorbidities. Hence, there is considerable interest in the development of highly specific and sensitive urinary biomarkers for the non-invasive early detection of UC. In this review, we assess the performance of current diagnostic assays for UC and highlight some of the most promising biomarkers investigated to date. We also highlight some of the recent advances in single-cell technologies that may offer a paradigm shift in the field of UC biomarker discovery and precision diagnostics.

Ball-lens assisted sensitivity improvement of fluorescence immunoassay in microchannels

A contactless and ball-lens assisted sensitivity improvement method was present for the fluorescence or luminescence immunoassay in microchannel.

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

Bladder cancer (BC) is among the most common tumors with a high recurrence rate, necessitating noninvasive and sensitive diagnostic methods. Accurate detection of exfoliated tumor cells (ETCs) in urine is crucial for noninvasive BC diagnosis but suffers from limited sensitivity when ETCs are rare and confounded by reactive, regenerative, or reparative cells. Single-cell sequencing (SCS) enables accurate detection of ETCs by surveying oncogenic driver mutations or genome-wide copy number alternations. To overcome the low-throughput limitation of SCS, we report a SCS-validated cellular marker, hexokinase 2 (HK2), for high-throughput screening cells in urine and detecting ETCs engaging elevated glycolysis. In the SCS-based training set, a total of 385 cells from urine samples of eight urothelial carcinoma (UC) patients were sequenced to establish a HK2 threshold that achieved >90% specificity for ETC detection. This urine-based HK2 assay was tested with a blinded patient group (n = 384) including UC and benign genitourinary disorders as a validation cohort for prospectively evaluating diagnostic accuracy. The sensitivity, specificity, positive predictive value, and negative predictive value of the assay were 90, 88, 83, and 93%, respectively, which were superior to urinary cytology. For investigating the potential to be a screening test, the HK2 assay was tested with a group of healthy individuals (n = 846) and a 6-month follow-up. The specificity was 98.4% in this health group. Three participants were found to have >5 putative ETCs that were sequenced to exhibit recurrent copy number alternations characteristic of malignant cells, demonstrating early BC detection before current clinical methods.

Cytologically targeted next-generation sequencing: a synergy for diagnosing urothelial carcinoma

INTRODUCTION

Cytology and cystoscopy are used to detect urothelial carcinoma (UC), but together they still fail to detect some UC cases and are not suitable for screening asymptomatic individuals. Mutations are present in more than 98% of UC, mutations have therapeutic significance, and they can be detected by next generation sequencing (NGS) in urine samples. We review the role of NGS in UC detection.

MATERIALS AND METHODS

Comprehensive literature review on UC genetics, economics of NGS, and previous reports of UC detection by NGS.

RESULTS

The raw costs of NGS have decreased to about 14,000 base pairs per penny, making it appear economically feasible to use NGS widely. Reported NGS assays fall short of predicted sensitivity. Decreased sensitivity is attributed to a low frequency of mutant alleles in many urine samples. Attempts to increase the percentage of mutant alleles, by using cell-free urinary DNA, or by using cell sorting and microfluidics, have been unsuccessful or remain unproven. However, cytologic examination can immediately enable NGS: Urine cytologies with sufficient proportions of abnormal cells could be directly triaged to NGS with high sensitivity for UC detection. For cases with a low proportion of abnormal cells, cytologically targeted microdissection of cells for NGS should maintain sensitivity and decrease sequencing costs. Cytologically targeted urothelial cells for NGS could allow a screening test for low grade UC.

CONCLUSIONS

Cytology is immediately poised to allow NGS to improve the diagnosis of UC, allowing NGS to be an ancillary test for atypical cytologies, and potentially allowing a screening test for low-grade UC.

Noninvasive Detection of Urothelial Carcinoma by Cost-effective Low-coverage Whole-genome Sequencing from Urine-Exfoliated Cell DNA

PURPOSE

Urothelial carcinoma is a malignant cancer with frequent chromosomal aberrations. Here, we investigated the application of a cost-effective, low-coverage whole-genome sequencing technology in detecting all chromosomal aberrations.

EXPERIMENTAL DESIGN

Patients with urothelial carcinomas and nontumor controls were prospectively recruited in clinical trial NCT03998371. Urine-exfoliated cell DNA was analyzed by Illumina HiSeq XTen, followed by genotyping with a customized bioinformatics workflow named Urine Exfoliated Cells Copy Number Aberration Detector (UroCAD).

RESULTS

In the discovery phase, urine samples from 126 patients with urothelial carcinomas and 64 nontumor disease samples were analyzed. Frequent chromosome copy-number changes were found in patients with tumor as compared with nontumor controls. A novel diagnosis model, UroCAD, was built by incorporating all the autosomal chromosomal changes. The model reached performance of AUC = 0.92 (95% confidence interval, 89.4%-97.3%). At the optimal cutoff, |Z| ≥ 3.21, the sensitivity, specificity, and accuracy were 82.5%, 96.9%, and 89.0%, respectively. The prediction positivity was found correlated with tumor grade (P = 0.01). In the external validation cohort of 95 participants, the UroCAD assay identified urothelial carcinomas with an overall sensitivity of 80.4%, specificity of 94.9%, and AUC of 0.91. Meanwhile, UroCAD assay outperformed cytology tests with significantly improved sensitivity (80.4% vs. 33.9%; P < 0.001) and comparable specificity (94.9% vs. 100%; P = 0.49).

CONCLUSIONS

UroCAD could be a robust urothelial carcinoma diagnostic method with improved sensitivity and similar specificity as compared with cytology tests. It may be used as a noninvasive approach for diagnosis and recurrence surveillance in urothelial carcinoma prior to the use of cystoscopy, which would largely reduce the burden on patients.

Single-Cell Sequencing in Genitourinary Malignancies

Single-cell sequencing (SCS) is a powerful new tool that applies Next Generation Sequencing at the cellular level. SCS has revolutionized our understanding of tumor heterogeneity and the tumor microenvironment, immune infiltration, cancer stem cells (CSCs), circulating tumor cells (CTCs), and clonal evolution. The following chapter highlights the current literature on SCS in genitourinary (GU) malignancies and discusses future applications of SCS technology. The renal cell carcinoma (RCC) section highlights the use of SCS in characterizing the initial cells driving tumorigenesis, the intercellular mutational landscape of RCC, intratumoral heterogeneity (ITH) between primary and metastatic lesions, and genes driving RCC cancer stem cells (CSCs). The bladder cancer section will also illustrate molecular drivers of bladder cancer stem cells (BCSCs), SCS use in reconstructing tumor developmental history and underlying subclones, and understanding the effect of cisplatin on intratumoral heterogeneity in vitro and potential mechanisms behind platinum resistance. The final section featuring prostate cancer will discuss how SCS can be used to identify the cellular origins of benign prostatic hyperplasia and prostate cancer, the plasticity and heterogeneity of prostate cancer cells with regard to androgen dependence, and the use of SCS in CTCs to understand chemotherapy resistance and gene expression changes after androgen deprivation therapy (ADT). The studies listed in this chapter illustrate many translational applications of SCS in GU malignancies, including diagnostic, prognostic, and treatment-related approaches. The ability of SCS to resolve intratumor heterogeneity and better define the genomic landscape of tumors and CTCs will be fundamental in the new era of precision-based care.

Phenotypic Analysis of Urothelial Exfoliated Cells in Bladder Cancer via Microfluidic Immunoassays: Sialyl-Tn as a Novel Biomarker in Liquid Biopsies

Bladder cancer is the most common malignancy of the urinary tract, having one of the highest recurrence rates and progression from non-muscle to muscle invasive bladder cancer that commonly leads to metastasis. Cystoscopy and urine cytology are the standard procedures for its detection but have limited clinical sensitivity and specificity. Herein, a microfluidic device, the UriChip, was developed for the enrichment of urothelial exfoliated cells from fresh and frozen urine, based on deformability and size, and the cancer-associated glycan Sialyl-Tn explored as a putative bladder cancer urinary biomarker. Spiking experiments with bladder cancer cell lines showed an isolation efficiency of 53%, while clinical sample analyses revealed retention of cells with various morphologies and sizes. in situ immunoassays demonstrated significantly higher number of Sialyl-Tn-positive cells in fresh and frozen voided urine from bladder cancer patients, compared to healthy individuals. Of note, urothelial exfoliated cells from cryopreserved urine sediments were also successfully isolated by the UriChip, and found to express significantly high levels of Sialyl-Tn. Remarkably, Sialyl-Tn expression is correlated with tumor stage and grade. Overall, our findings demonstrate the potential of UriChip and Sialyl-Tn to detect urothelial bladder cancer cells in follow-up and long-term retrospective studies.

ALICE: a hybrid AI paradigm with enhanced connectivity and cybersecurity for a serendipitous encounter with circulating hybrid cells

A fully automated and accurate assay of rare cell phenotypes in densely-packed fluorescently-labeled liquid biopsy images remains elusive. Methods: Employing a hybrid artificial intelligence (AI) paradigm that combines traditional rule-based morphological manipulations with modern statistical machine learning, we deployed a next generation software, ALICE (Automated Liquid Biopsy Cell Enumerator) to identify and enumerate minute amounts of tumor cell phenotypes bestrewed in massive populations of leukocytes. As a code designed for futurity, ALICE is armed with internet of things (IOT) connectivity to promote pedagogy and continuing education and also, an advanced cybersecurity system to safeguard against digital attacks from malicious data tampering. Results: By combining robust principal component analysis, random forest classifier and cubic support vector machine, ALICE was able to detect synthetic, anomalous and tampered input images with an average recall and precision of 0.840 and 0.752, respectively. In terms of phenotyping enumeration, ALICE was able to enumerate various circulating tumor cell (CTC) phenotypes with a reliability ranging from 0.725 (substantial agreement) to 0.961 (almost perfect) as compared to human analysts. Further, two subpopulations of circulating hybrid cells (CHCs) were serendipitously discovered and labeled as CHC-1 (DAPI+/CD45+/E-cadherin+/vimentin-) and CHC-2 (DAPI+ /CD45+/E-cadherin+/vimentin+) in the peripheral blood of pancreatic cancer patients. CHC-1 was found to correlate with nodal staging and was able to classify lymph node metastasis with a sensitivity of 0.615 (95% CI: 0.374-0.898) and specificity of 1.000 (95% CI: 1.000-1.000). Conclusion: This study presented a machine-learning-augmented rule-based hybrid AI algorithm with enhanced cybersecurity and connectivity for the automatic and flexibly-adapting enumeration of cellular liquid biopsies. ALICE has the potential to be used in a clinical setting for an accurate and reliable enumeration of CTC phenotypes.

A Microfluidic Detection System for Bladder Cancer Tumor Cells

The clinical characteristics of excreted tumor cells can be found in the urine of bladder cancer patients, meaning the identification of tumor cells in urine can assist in bladder cancer diagnosis. The presence of white blood cells and epithelial cells in the urine interferes with the recognition of tumor cells. In this paper, a technique for detecting cancer cells in urine based on microfluidics provides a novel approach to bladder cancer diagnosis. The bladder cancer cell line (T24) and MeT-5A were used as positive bladder tumor cells and non-tumor cells, respectively. The practicality of the tumor cell detection system based on microfluidic cell chip detection technology is discussed. The tumor cell (T24) concentration was around 1 × 10⁴ to 300 × 10⁴ cells/mL. When phosphate buffer saline (PBS) was the diluted solution, the tumor cell detected rate was 63–71% and the detection of tumor cell number stability (coefficient of variation, CV%) was 6.7–4.1%, while when urine was the diluted solution, the tumor cell detected rate was 64–72% and the detection of tumor cell number stability (CV%) was 6.3–3.9%. In addition, both PBS and urine are tumor cell dilution fluid solutions. The sample was analyzed at a speed of 750 microns per hour. Based on the above experiments, a system for detecting bladder cancer cells in urine by microfluidic analysis chip technology was reported. The rate of recognizing bladder cancer cells reached 68.4%, and the speed reached 2 mL/h.

Advances in diagnostic microfluidics

Microfluidics is an emerging field in diagnostics that allows for extremely precise fluid control and manipulation, enabling rapid and high-throughput sample processing in integrated micro-scale medical systems. These platforms are well-suited for both standard clinical settings and point-of-care applications. The unique features of microfluidics-based platforms make them attractive for early disease diagnosis and real-time monitoring of the disease and therapeutic efficacy. In this chapter, we will first provide a background on microfluidic fundamentals, microfluidic fabrication technologies, microfluidic reactors, and microfluidic total-analysis-systems. Next, we will move into a discussion on the clinical applications of existing and emerging microfluidic platforms for blood analysis, and for diagnosis and monitoring of cancer and infectious disease. Together, this chapter should elucidate the potential that microfluidic systems have in the development of effective diagnostic technologies through a review of existing technologies and promising directions.

Detection of Clinical Mesenchymal Cancer Cells from Bladder Wash Urine for Real-Time Detection and Prognosis

Bladder cancer (BC) is a disease that requires lifelong surveillance due to its high recurrence rate. An efficient method for the non-invasive rapid monitoring of patient prognosis and downstream phenotype characterization is warranted. Here, we develop an integrated procedure to detect aggressive mesenchymal exfoliated bladder cancer cells (EBCCs) from patients in a label-free manner. Using a combination of filtration and inertial focusing principles, the procedure allowed the focusing of EBCCs in a single stream-line for high-throughput separation from other urine components such as large squamous cells and blood cells using a microfluidic sorting device. Characterization of enriched cells can be completed within hours, suggesting a potential utility for real-time detection. We also demonstrate high efficiency of cancer cell recovery (93.3 ± 4.8%) and specific retrieval of various epithelial to mesenchymal transition (EMT) phenotype cell fractions from respective outlets of the microfluidic device. EMT is closely associated with metastasis, drug resistance and tumor-initiating potential. This procedure is validated with clinical samples, and further demonstrate the efficacy of bladder wash procedure to reduce EBCCs counts over time. Overall, the uniqueness of a rapid and non-invasive method permitting the separation of different EMT phenotypes shows high potential for clinical utility. We expect this approach will better facilitate the routine screening procedure in BC and greatly enhance personalized treatment.

CTC phenotyping for a preoperative assessment of tumor metastasis and overall survival of pancreatic ductal adenocarcinoma patients

BACKGROUND

The evaluation for surgical resectability of pancreatic ductal adenocarcinoma (PDAC) patients is not only imaging-based but highly subjective. An objective method is urgently needed. We report on the clinical value of a phenotypic circulating tumor cell (CTC)-based blood test for a preoperative prognostic assessment of tumor metastasis and overall survival (OS) of PDAC patients.

METHODS

Venous blood samples from 46 pathologically confirmed PDAC patients were collected prospectively before surgery and immunoassayed using a specially designed TU-chip™. Captured CTCs were differentiated into epithelial (E), mesenchymal and hybrid (H) phenotypes. A further 45 non-neoplastic healthy donors provided blood for cell line validation study and CTC false positive quantification.

FINDINGS

A validated multivariable model consisting of disjunctively combined CTC phenotypes: "H-CTC≥15.0 CTCs/2ml OR E-CTC≥11.0 CTCs/2ml" generated an optimal prediction of metastasis with a sensitivity of 1.000 (95% CI 0.889-1.000) and specificity of 0.886 (95% CI 0.765-0.972). The adjusted Kaplan-Meier median OS constructed using Cox proportional-hazard models and stratified for E-CTC < 11.0 CTCs/2 ml was 16.5 months and for E-CTC ≥ 11.0 CTCs/2 ml was 5.5 months (HR = 0.050, 95% CI 0.004-0.578, P = .016). These OS results were consistent with the outcome of the metastatic analysis.

INTERPRETATION

Our work suggested that H-CTC is a better predictor of metastasis and E-CTC is a significant independent predictor of OS. The CTC phenotyping model has the potential to be developed into a reliable and accurate blood test for metastatic and OS assessments of PDAC patients. FUND: National Natural Science Foundation of China; Zhejiang Province Science and Technology Program; China Scholarship Council.