Circulating Tumor Cells: The Importance of Single Cell Analysis

Exosomal long non-coding RNAs in cancer: Interplay, modulation, and therapeutic avenues

In the intricate field of cancer biology, researchers are increasingly intrigued by the emerging role of exosomal long non-coding RNAs (lncRNAs) due to their multifaceted interactions, complex modulation mechanisms, and potential therapeutic applications. These exosomal lncRNAs, carried within extracellular vesicles, play a vital partin tumorigenesis and disease progression by facilitating communication networks between tumor cells and their local microenvironment, making them an ideal candidates for use in a liquid biopsy approach. However, exosomal lncRNAs remain an understudied area, especially in cancer biology. Therefore this review aims to comprehensively explore the dynamic interplay between exosomal lncRNAs and various cellular components, including interactions with tumor-stroma, immune modulation, and drug resistance mechanisms. Understanding the regulatory functions of exosomal lncRNAs in these processes can potentially unveil novel diagnostic markers and therapeutic targets for cancer. Additionally, the emergence of RNA-based therapeutics presents exciting opportunities for targeting exosomal lncRNAs, offering innovative strategies to combat cancer progression and improve treatment outcomes. Thus, this review provides insights into the current understanding of exosomal lncRNAs in cancer biology, highlighting their crucial roles, regulatory mechanisms, and the evolving landscape of therapeutic interventions. Furthermore, we have also discussed the advantage of exosomes as therapeutic carriers of lncRNAs for the development of personalized targeted therapy for cancer patients.

Seeding metastases: The role and clinical utility of circulating tumour cells

Peripheral human blood is a readily-accessible source of patient material in which circulating tumour cells (CTCs) can be found. Their isolation and characterization holds the potential to provide prognostic value for various solid cancers. Enumeration of CTCs from blood is becoming a common practice in informing prognosis and may guide therapy decisions. It is further recognized that enumeration alone does not capture perspective on the heterogeneity of tumours and varying functional abilities of the CTCs to interact with the secondary microenvironment. Characterizing the isolated CTCs further, in particular assessing their functional abilities, can track molecular changes in the disease progress. As a step towards identifying a suite of functional features of CTCs that could aid in clinical decisions, developing a CTC isolation technique based on extracellular matrix (ECM) interactions may provide a more solid foundation for isolating the cells of interest. Techniques based on size, charge, density, and single biomarkers are not sufficient as they underutilize other characteristics of cancer cells. The ability of cancer cells to interact with ECM proteins presents an opportunity to utilize their full character in capturing, and also allows assessment of the features that reveal how cells might behave at secondary sites during metastasis. This article will review some common techniques and recent advances in CTC capture technologies. It will further explore the heterogeneity of the CTC population, challenges they experience in their metastatic journey, and the advantages of utilizing an ECM-based platform for CTC capture. Lastly, we will discuss how tailored ECM approaches may present an optimal platform to capture an influential heterogeneous population of CTCs.

Enrichment and detection method for the prognostic value of circulating tumor cells in ovarian cancer: A meta-analysis

OBJECTIVES

Recent studies have revealed that circulating tumor cells (CTCs) might predict bad prognosis, but the results were conflicting. Sampling time, treatment, enrichment method and detection method also varied. We aimed to evaluate whether patients with CTCs in peripheral blood have bad survival outcomes with consideration of the above four aspects.

METHODS

Relevant studies were searched on Pubmed, Embase and the Cochrane Library. Studies of CTCs involving survival data available were identified for a systematic review and meta-analysis. HRs and 95% CIs for PFS and OS were extracted directly or from the Kaplan-Meier survival curves by the Engauge Digitizer v4.1. Subgroup analyses were performed to evaluate the effect of sampling time, treatment, enrichment method and detection method.

RESULTS

Two clinical trials and thirteen retrospective studies with a total of 1285 patients were included. CTCs significantly correlated with OS (HR = 1.77, 95%CI:1.42-2.21, p < 0.00001 and PFS (HR = 1.53, 95%CI:1.26-1.86, p < 0.0001). Subgroup analyses showed that CTCs were significant associated with OS in the "Pre-therapy" subgroup (HR = 1.79, 95%CI:1.43-2.24, p < 0.00001), the "Surgery" group (HR = 1.82, 95%CI:1.42-2.33, p < 0.00001), and the "RT-PCR"subgroup (HR = 2.29, 95%CI:1.53-3.42, p < 0.0001). While for enrichment method, CTCs significantly correlated with OS in the"Physical method" subgroup (HR = 1.94, 95%CI:1.21-3.09, p = 0.006) and the "Immunological method" subgroup (HR = 1.84, 95%CI:1.37-2.48, p < 0.0001).

CONCLUSIONS

The presence of CTCs prior to the treatment indicated worse OS and PFS and CTCs might be predictive biomarker for ovarian cancer patients . CTCs detected using RT-PCR seem to be associated with poorer OS and PFS in patients with ovarian cancer.

Progress and Clinical Application of Single-Cell Transcriptional Sequencing Technology in Cancer Research

Cancer has been a daunting challenge for human beings because of its clonal heterogeneity and compositional complexity. Tumors are composed of cancer cells and a variety of non-cancer cells, which together with the extracellular matrix form the tumor microenvironment. These cancer-related cells and components and immune mechanisms can affect the development and progression of cancer and are associated with patient diagnosis, treatment and prognosis. As the first choice for the study of complex biological systems, single-cell transcriptional sequencing (scRNA-seq) has been widely used in cancer research. ScRNA-seq has made breakthrough discoveries in tumor heterogeneity, tumor evolution, metastasis and spread, development of chemoresistance, and the relationship between the tumor microenvironment and the immune system. These results will guide clinical cancer treatment and promote personalized and highly accurate cancer treatment. In this paper, we summarize the latest research progress of scRNA-seq and its guiding significance for clinical treatment.

The combination of artificial intelligence and systems biology for intelligent vaccine design

INTRODUCTION

A new body of evidence depicts the applications of artificial intelligence and systems biology in vaccine design and development. The combination of both approaches shall revolutionize healthcare, accelerating clinical trial processes and reducing the costs and time involved in drug research and development.

AREAS COVERED

This review explores the basics of artificial intelligence and systems biology approaches in the vaccine development pipeline. The topics include a detailed description of epitope prediction tools for designing epitope-based vaccines and agent-based models for immune system response prediction, along with a focus on their potentiality to facilitate clinical trial phases.

EXPERT OPINION

Artificial intelligence and systems biology offer the opportunity to avoid the inefficiencies and failures that arise in the classical vaccine development pipeline. One promising solution is the combination of both methodologies in a multiscale perspective through an accurate pipeline. We are entering an 'in silico era' in which scientific partnerships, including a more and more increasing creation of an 'ecosystem' of collaboration and multidisciplinary approach, are relevant for addressing the long and risky road of vaccine discovery and development. In this context, regulatory guidance should be developed to qualify the in silico trials as evidence for intelligent vaccine development.

Preclinical development of a novel BCR-ABL T315I inhibitor against chronic myeloid leukemia

Chronic Myeloid Leukemia (CML) is a myeloproliferative neoplasm primarily due to the presence of the BCR-ABL fusion gene that produces the constitutively active protein, BCR-ABL. Imatinib, a BCR-ABL-targeted drug, is a first-line drug for the treatment of CML. Resistance to imatinib occurs as a result of mutations in the BCR-ABL kinase domains. In this study, we evaluated S116836, a novel BCR-ABL inhibitor, for its anti-cancer efficacy in the wild-type (WT) and T315I mutant BCR-ABL. S116836 was efficacious in BaF3 cells with WT or T315I mutated BCR-ABL genotypes. S116836 inhibits the phosphorylation of BCR-ABL and its downstream signaling in BaF3/WT and BaF3/T315I cells. Mechanistically, S116836 arrests the cells in the G0/G1 phase of cell cycle, induces apoptosis, increases ROS production, and decreases GSH production in BaF3/WT and BaF3/T315I cells. Moreover, in mouse tumor xenografts, S116836 significantly inhibits the growth and volume of tumors expressing the WT or T315I mutant BCR-ABL without causing significant cardiotoxicity. Overall, our results indicate that S116836 significantly inhibits the imatinib-resistant T315I BCR-ABL mutation and could be a novel drug candidate for treating imatinib-resistant CML patients.

Role of Exosomes in Photodynamic Anticancer Therapy

Photodynamic Therapy (PDT) is a promising alternative treatment for malignancies based on photochemical reaction induced by Photosensitizers (PS) under light irradiation. Recent studies show that PDT caused the abundant release of exosomes from tumor tissues. It is well-known that exosomes as carriers play an important role in cell-cell communication through transporting many kinds of bioactive molecules (e.g. lipids, proteins, mRNA, miRNA and lncRNA). Therefore, to explore the role of exosomes in photodynamic anticancer therapy has been attracting significant attention. In the present paper, we will briefly introduce the basic principle of PDT and exosomes, and focus on discussing the role of exosomes in photodynamic anticancer therapy, to further enrich and boost the development of PDT.

Circulating Tumor Cell Detection in Lung Cancer: But to What End?

The understanding of the natural history and biology of lung cancer has been enhanced by studies into circulating tumor cells (CTCs). Fundamental and translational research, as well as clinical trials in the characterization and behavior of these cells, have constantly contributed to improving understanding within the domain of thoracic oncology. However, the use of these CTCs as prognostic and predictive biomarkers has not been adopted to the same extent as circulating free DNA (cf-DNA) in plasma, in the daily practice of thoracic oncologists. However, recent technological advances have firmly put the detection and characterization of CTCs in thoracic oncology back on the agenda, and have opened up perspectives for their routine clinical use. This review discusses the major advances of using CTCs in the domain of thoracic oncology, as well as the envisaged short- and long-term prospects.

Circulating Tumor Cell-Derived Pre-Clinical Models for Personalized Medicine

The main cause of death from cancer is associated with the development of metastases, resulting from the inability of current therapies to cure patients at metastatic stages. Generating preclinical models to better characterize the evolution of the disease is thus of utmost importance, in order to implement effective new cancer biomarkers and therapies. Circulating Tumor Cells (CTCs) are good candidates for generating preclinical models, making it possible to follow up the spatial and temporal heterogeneity of tumor tissues. This method is a non-invasive liquid biopsy that can be obtained at any stage of the disease. It partially summarizes the molecular heterogeneity of the corresponding tumors at a given time. Here, we discuss the CTC-derived models that have been generated so far, from simplified 2D cultures to the most complex CTC-derived explants (CDX models). We highlight the challenges and strengths of these preclinical tools, as well as some of the recent studies published using these models.