Circulating tumor cell detection and single-cell analysis using an integrated workflow based on ChimeraX® -i120 Platform: A prospective study

Emerging methods and techniques for cancer biomarker discovery

Modern cancer research depends heavily on the identification and validation of biomarkers because they provide important information about the diagnosis, prognosis, and response to treatment of the cancer. This review will provide a comprehensive overview of cancer biomarkers, including their development phases and recent breakthroughs in transcriptomics and computational techniques for detecting these biomarkers. Blood-based biomarkers have great potential for non-invasive tumor dynamics and treatment response monitoring. These include circulating tumor DNA, exosomes, and microRNAs. Comprehensive molecular profiles are provided by multi-omic technologies, which combine proteomics, metabolomics, and genomes to support the identification of biomarkers and the targeting of therapeutic interventions. Genetic changes are detected by next-generation sequencing, and patterns of protein expression are found by protein arrays and mass spectrometry. Tumor heterogeneity and clonal evolution can be understood using metabolic profiling and single-cell studies. It is projected that the use of several biomarkers-genetic, protein, mRNA, microRNA, and DNA profiles, among others-will rise, enabling multi-biomarker analysis and improving individualised treatment plans. Biomarker identification and patient outcome prediction are further improved by developments in AI algorithms and imaging techniques. Robust biomarker validation and reproducibility require cooperation between industry, academia, and doctors. Biomarkers can provide individualized care, meet unmet clinical needs, and enhance patient outcomes despite some obstacles. Precision medicine will continue to take shape as scientific research advances and the integration of biomarkers with cutting-edge technologies continues to offer a more promising future for personalized cancer care.

Liver cancer from the perspective of single-cell sequencing: a review combined with bibliometric analysis

BACKGROUND

Liver cancer (LC) is a prevalent malignancy and a leading cause of cancer-related mortality worldwide. Extensive research has been conducted to enhance patient outcomes and develop effective prevention strategies, ranging from molecular mechanisms to clinical interventions. Single-cell sequencing, as a novel bioanalysis technology, has significantly contributed to the understanding of the global cognition and dynamic changes in liver cancer. However, there is a lack of bibliometric analysis in this specific research area. Therefore, the objective of this study is to provide a comprehensive overview of the knowledge structure and research hotspots in the field of single-cell sequencing in liver cancer research through the use of bibliometrics.

METHOD

Publications related to the application of single-cell sequencing technology to liver cancer research as of December 31, 2023, were searched on the web of science core collection (WoSCC) database. VOSviewers, CiteSpace, and R package "bibliometrix" were used to conduct this bibliometric analysis.

RESULTS

A total of 331 publications from 34 countries, primarily led by China and the United States, were included in this study. The research focuses on the application of single cell sequencing technology to liver cancer, and the number of related publications has been increasing year by year. The main research institutions involved in this field are Fudan University, Sun Yat-Sen University, and the Chinese Academy of Sciences. Frontiers in Immunology and Nature Communications is the most popular journal in this field, while Cell is the most frequently co-cited journal. These publications are authored by 2799 individuals, with Fan Jia and Zhou Jian having the most published papers, and Llovet Jm being the most frequently co-cited author. The use of single cell sequencing to explore the immune microenvironment of liver cancer, as well as its implications in immunotherapy and chemotherapy, remains the central focus of this field. The emerging research hotspots are characterized by keywords such as 'Gene-Expression', 'Prognosis', 'Tumor Heterogeneity', 'Immunoregulation', and 'Tumor Immune Microenvironment'.

CONCLUSION

This is the first bibliometric study that comprehensively summarizes the research trends and developments on the application of single cell sequencing in liver cancer. The study identifies recent research frontiers and hot directions, providing a valuable reference for researchers exploring the landscape of liver cancer, understanding the composition of the immune microenvironment, and utilizing single-cell sequencing technology to guide and enhance the prognosis of liver cancer patients.

Platelet-mediated circulating tumor cell evasion from natural killer cell killing through immune checkpoint CD155-TIGIT

BACKGROUND AND AIMS

Circulating tumor cells (CTCs) are precursors of cancer metastasis. However, how CTCs evade immunosurveillance during hematogenous dissemination remains unclear.

APPROACH AND RESULTS

We identified CTC-platelet adhesions by single-cell RNA sequencing and multiplex immunofluorescence of blood samples from multiple cancer types. Clinically, CTC-platelet aggregates were associated with significantly shorter progression-free survival and overall survival in patients with HCC. In vitro, ex vivo, and in vivo assays demonstrated direct platelet adhesions gifted cancer cells with an evasive ability from NK cell killing by upregulating inhibitory checkpoint CD155 (PVR cell adhesion molecule), therefore facilitating distant metastasis. Mechanistically, CD155 was transcriptionally regulated by the FAK/JNK/c-Jun cascade in a platelet contact-dependent manner. Further competition assays and cytotoxicity experiments revealed that CD155 on CTCs inhibited NK-cell cytotoxicity only by engaging with immune receptor TIGIT, but not CD96 and DNAM1, another 2 receptors for CD155. Interrupting the CD155-TIGIT interactions with a TIGIT antibody restored NK-cell immunosurveillance on CTCs and markedly attenuated tumor metastasis.

CONCLUSIONS

Our results demonstrated CTC evasion from NK-cell-mediated innate immunosurveillance mainly through immune checkpoint CD155-TIGIT, potentially offering an immunotherapeutic strategy for eradicating CTCs.

Hypoxia-induced circ-CDYL-EEF1A2 transcriptional complex drives lung metastasis of cancer stem cells from hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is often associated with poor outcomes due to lung metastasis. ICAM-1+ circulating tumor cells, termed circulating cancer stem cells (CCSCs), possess stem cell-like characteristics. However, it is still unexplored how their presence indicates lung metastasis tendency, and particularly, what mechanism drives their lung metastasis. Here, we demonstrated that a preoperative CCSC count in 5 mL of blood (CCSC5) of >3 was a risk factor for lung metastasis in clinical HCC patients. The CSCs overexpressed with circ-CDYL entered the bloodstream and developed lung metastases in mice. Mechanistically, circ-CDYL promoted COL14A1 expression and thus ERK signaling to facilitate epithelial-mesenchymal transition. Furthermore, we uncovered that an RNA-binding protein, EEF1A2, acted as a novel transcriptional (co-) factor to cooperate with circ-CDYL and initiate COL14A1 transcription. A high circ-CDYL level is caused by HIF-1⍺-mediated transcriptional upregulation of its parental gene CDYL and splicing factor EIF4A3 under a hypoxia microenvironment. Hence, the hypoxia microenvironment enables the high-tendency lung metastasis of ICAM-1+ CCSCs through the HIF-1⍺/circ-CDYL-EEF1A2/COL14A1 axis, potentially allowing clinicians to preoperatively detect ICAM-1+ CCSCs as a real-time biomarker for precisely deciding HCC treatment strategies.

Nanotechnology and machine learning enable circulating tumor cells as a reliable biomarker for radiotherapy responses of gastrointestinal cancer patients

A highly sensitive, circulating tumor cell (CTC)-based liquid biopsy was used to monitor gastrointestinal cancer patients during treatment to determine if CTC abundance was predictive of disease recurrence. The approach used a combination of biomimetic cell rolling on recombinant E-selectin and dendrimer-mediated multivalent immunocapture at the nanoscale to purify CTCs from peripheral blood mononuclear cells. Due to the exceptionally high numbers of CTCs captured, a machine learning algorithm approach was developed to efficiently and reliably quantify abundance of immunocytochemically-labeled cells. A convolutional neural network and logistic regression model achieved 82.9% true-positive identification of CTCs with a false positive rate below 0.1% on a validation set. The approach was then used to quantify CTC abundance in peripheral blood samples from 27 subjects before, during, and following treatments. Samples drawn from the patients either prior to receiving radiotherapy or early in chemotherapy had a median 50 CTC ml-1 whole blood (range 0.6-541.6). We found that the CTC counts drawn 3 months post treatment were predictive of disease progression (p = .045). This approach to quantifying CTC abundance may be a clinically impactful in the timely determination of gastrointestinal cancer progression or response to treatment.

Detection and Characterization of Circulating Tumor Cells Using Imaging Flow Cytometry—A Perspective Study

Simple Summary

Liquid biopsy is non-invasive approach used to prognose and monitor tumor progression based on the detection and examination of metastasis-related events found in the patients’ blood (such as circulating tumor cells (CTCs), extracellular vesicles, and circulating nucleic acids). Different ultrasensitive techniques are applied to study those events and the biology of tumor dissemination, which in the future might complement standard diagnostics. Here, we suggest that CTCs analysis could be improved by the usage of imaging flow cytometry, combining advantages of both standard flow cytometry (high-scale analysis) and microscopy (high resolution) to investigate detailed features of those cells. From this perspective, we discuss the potential of this technology in the CTC field and present representative images of CTCs from breast and prostate cancer patients analyzed with this method.

Abstract

Tumor dissemination is one of the most-investigated steps of tumor progression, which in recent decades led to the rapid development of liquid biopsy aiming to analyze circulating tumor cells (CTCs), extracellular vesicles (EVs), and circulating nucleic acids in order to precisely diagnose and monitor cancer patients. Flow cytometry was considered as a method to detect CTCs; however, due to the lack of verification of the investigated cells’ identity, this method failed to reach clinical utility. Meanwhile, imaging flow cytometry combining the sensitivity and high throughput of flow cytometry and image-based detailed analysis through a high-resolution microscope might open a new avenue in CTC technologies and provide an open-platform system alternative to CellSearch^®, which is still the only gold standard in this field. Hereby, we shortly review the studies on the usage of flow cytometry in CTC identification and present our own representative images of CTCs envisioned by imaging flow cytometry providing rationale that this novel technology might be a good tool for studying tumor dissemination, and, if combined with a high CTC yield enrichment method, could upgrade CTC-based diagnostics.

Uncovering the Heterogeneity and Clinical Relevance of Circulating Tumor-Initiating Cells in Hepatocellular Carcinoma Using an Integrated Immunomagnetic-Microfluidic Platform

Circulating tumor-initiating cells (CTICs) with stem cell-like properties play pivotal roles in tumor metastasis and recurrence. However, little is known about the biology and clinical relevance of CTICs in hepatocellular carcinoma (HCC). Here, we investigated the molecular heterogeneity and clinical relevance of CTICs in HCC using a novel integrated immunomagnetic-microfluidic platform (iMAC). We constructed the iMAC and evaluated its ability to detect CTICs using a series of spiked cell experiments. A four-channel microfluidic chip was applied to investigate the composition of CTICs in patients with primary and recurrent HCC utilizing microbeads labeled with one of four stem-related markers: epithelial cell adhesion molecule (EpCAM), CD133, CD90, and CD24. The dynamic changes of these four CTIC subsets were serially monitored during treatment courses. Finally, single-cell RNA profiling was used to reveal the molecular characteristics of the four CTIC subsets. The iMAC platform detected significantly more EpCAM⁺ CTICs in the blood samples from 33 HCC patients than the FDA-approved CellSearch system (0.92 ± 0.94 vs 0.23 ± 0.36, P < 0.001). The number of EpCAM⁺ CTICs (≥0.75/mL) detected by iMAC was a predictor of early recurrence (P = 0.007). The distinct stem-related markers' expression of CTICs could distinguish primary HCC, recurrent HCC, and TACE-resistant HCC. Single-cell transcriptional profiling proved the heterogeneity among individual CTICs and separated the four CTIC subsets into distinct phenotypes. Dissecting the heterogeneity of CTICs using the iMAC represents a novel and informative method for accurate CTIC detection and characterization. This innovative technology will enable more indepth cancer biology research and clinical cancer management than is currently available.

Single-Cell Sequencing and Its Applications in Liver Cancer

As one of the most lethal cancers, primary liver cancer (PLC) has high tumor heterogeneity, including the heterogeneity between cancer cells. Traditional methods which have been used to identify tumor heterogeneity for a long time are based on large mixed cell samples, and the research results usually show average level of the cell population, ignoring the heterogeneity between cancer cells. In recent years, single-cell sequencing has been increasingly applied to the studies of PLCs. It can detect the heterogeneity between cancer cells, distinguish each cell subgroup in the tumor microenvironment (TME), and also reveal the clonal characteristics of cancer cells, contributing to understand the evolution of tumor. Here, we introduce the process of single-cell sequencing, review the applications of single-cell sequencing in the heterogeneity of cancer cells, TMEs, oncogenesis, and metastatic mechanisms of liver cancer, and discuss some of the current challenges in the field.

Applications of single-cell sequencing in cancer research: progress and perspectives

Single-cell sequencing, including genomics, transcriptomics, epigenomics, proteomics and metabolomics sequencing, is a powerful tool to decipher the cellular and molecular landscape at a single-cell resolution, unlike bulk sequencing, which provides averaged data. The use of single-cell sequencing in cancer research has revolutionized our understanding of the biological characteristics and dynamics within cancer lesions. In this review, we summarize emerging single-cell sequencing technologies and recent cancer research progress obtained by single-cell sequencing, including information related to the landscapes of malignant cells and immune cells, tumor heterogeneity, circulating tumor cells and the underlying mechanisms of tumor biological behaviors. Overall, the prospects of single-cell sequencing in facilitating diagnosis, targeted therapy and prognostic prediction among a spectrum of tumors are bright. In the near future, advances in single-cell sequencing will undoubtedly improve our understanding of the biological characteristics of tumors and highlight potential precise therapeutic targets for patients.

miR-637 Prevents Glioblastoma Progression by Interrupting ZEB2/WNT/β-catenin Cascades

Glioblastomas (GBMs) are the most frequent primary malignancies in the central nervous system. Aberrant activation of WNT/β-catenin signaling pathways is critical for GBM malignancy. However, the regulation of WNT/β-catenin signaling cascades remains unclear. Presently, we observed the increased expression of ZEB2 and the decreased expression of miR-637 in GBM. The expression of miR-637 was negatively correlated with ZEB2 expression. miR-637 overexpression overcame the ZEB2-enhanced cell proliferation and G1/S phase transition. Besides, miR-637 suppressed the canonical WNT/β-catenin pathways by targeting WNT7A directly. Gain- and loss-of-function experiments with U251 mice demonstrated that miR-637 inhibited cell proliferation and arrested the G1/S phase transition, leading to tumor growth suppression. The collective findings suggest that ZEB2 and WNT/β-catenin cascades merge at miR-637, and the ectopic expression of miR-637 disturbs ZEB2/WNT/β-catenin-mediated GBM growth. The findings provide new clues for improving β-catenin-targeted therapy against GBM.