Advances in the Characterization of Circulating Tumor Cells in Metastatic Breast Cancer: Single Cell Analyses and Interactions, and Patient-Derived Models for Drug Testing

Pancreatic cancer environment: from patient-derived models to single-cell omics

Pancreatic cancer (PC) is a highly malignant cancer characterized by poor prognosis, high heterogeneity, and intricate heterocellular systems. Selecting an appropriate experimental model for studying its progression and treatment is crucial. Patient-derived models provide a more accurate representation of tumor heterogeneity and complexity compared to cell line-derived models. This review initially presents relevant patient-derived models, including patient-derived xenografts (PDXs), patient-derived organoids (PDOs), and patient-derived explants (PDEs), which are essential for studying cell communication and pancreatic cancer progression. We have emphasized the utilization of these models in comprehending intricate intercellular communication, drug responsiveness, mechanisms underlying tumor growth, expediting drug discovery, and enabling personalized medical approaches. Additionally, we have comprehensively summarized single-cell analyses of these models to enhance comprehension of intercellular communication among tumor cells, drug response mechanisms, and individual patient sensitivities.

Patient-derived models: Promising tools for accelerating the clinical translation of breast cancer research findings

Breast cancer has become the highest incidence of cancer in women. It was extensively and deeply studied by biologists and medical workers worldwide. However, the meaningful results in lab researches cannot be realized in clinical, and a part of new drugs in clinical experiments do not obtain as good results as the preclinical researches. It is urgently that promote a kind of breast cancer research models that can get study results closer to the physiological condition of the human body. Patient-derived models (PDMs) originating from clinical tumor, contain primary elements of tumor and maintain key clinical features of tumor. So they are promising research models to facilitate laboratory researches translate to clinical application, and predict the treatment outcome of patients. In this review, we summarize the establishment of PDMs of breast cancer, reviewed the application of PDMs in clinical translational researches and personalized precision medicine with breast cancer as an example, to improve the understanding of PDMs among researchers and clinician, facilitate them to use PDMs on a large scale of breast cancer researches and promote the clinical translation of laboratory research and new drug development.

Deciphering HER2-HER3 Dimerization at the Single CTC Level: A Microfluidic Approach

Simple Summary

Among these different biomarkers, circulating tumor cells have proven to be of high interest for different types of cancer and in particular for breast cancer. Here we focus our attention on a breast cancer subtype referred as HER2-positive breast cancer, this cancer being associated with an amplification of HER2 protein at the plasma membrane of cancer cells. Combined with therapies targeting the HER2 protein, HER2-HER3 dimerization blockade further improves a patient’s outcome. In this work, we propose a new approach to CTC characterization by on-chip integrating proximity ligation assay, so that we can quantify the HER2-HER3 dimerization event at the level of single CTC.

Abstract

Microfluidics has provided clinicians with new technologies to detect and analyze circulating tumor biomarkers in order to further improve their understanding of disease mechanism, as well as to improve patient management. Among these different biomarkers, circulating tumor cells have proven to be of high interest for different types of cancer and in particular for breast cancer. Here we focus our attention on a breast cancer subtype referred as HER2-positive breast cancer, this cancer being associated with an amplification of HER2 protein at the plasma membrane of cancer cells. Combined with therapies targeting the HER2 protein, HER2-HER3 dimerization blockade further improves a patient’s outcome. In this work, we propose a new approach to CTC characterization by on-chip integrating proximity ligation assay, so that we can quantify the HER2-HER3 dimerization event at the level of single CTC. To achieve this, we developed a microfluidic approach combining both CTC capture, identification and HER2-HER3 status quantification by Proximity Ligation Assay (PLA). We first optimized and demonstrated the potential of the on-chip quantification of HER2-HER3 dimerization using cancer cell lines with various levels of HER2 overexpression and validated its clinical potential with a patient’s sample treated or not with HER2-targeted therapy.

Place des biopsies liquides dans le diagnostic et la caractérisation moléculaire des cancers du sein

The tumor biopsy remains essential for breast cancer diagnosis and characterization. Indeed, the treatment is decided according to histological subtype, and according to the presence of targetable molecular alterations. Notably, the presence of hormone receptors, ERBB2 hyperexpression or the existence of PIK3CA or ESR1 mutations are among the alterations commonly investigated. But these biological characteristics are determined only partially by tumor biopsy, due to tumor heterogeneity or tumor plasticity that happens spontaneously or under treatment. Liquid biopsy, and in particular circulating tumor DNA and circulating tumor cells, is a non-invasive method to identify and characterize the presence of cancer in the blood. The aim of this review is to determine the value of liquid biopsy to enhance or replace the data provided by a tumor biopsy.

Bridging the Gaps between Circulating Tumor Cells and DNA Methylation in Prostate Cancer

Prostate cancer is the second most common male malignancy, with a highly variable clinical presentation and outcome. Therefore, diagnosis, prognostication, and management remain a challenge, as available clinical, imaging, and pathological parameters provide limited risk assessment. Thus, many biomarkers are under study to fill this critical gap, some of them based on epigenetic aberrations that might be detected in liquid biopsies. Herein, we provide a critical review of published data on the usefulness of DNA methylation and circulating tumor cells in diagnosis and treatment decisions in cases of prostate cancer, underlining key aspects and discussing the importance of these advances to the improvement of the management of prostate cancer patients. Using minimally invasive blood tests, the detection of highly specific biomarkers might be crucial for making therapeutic decisions, determining response to specific treatments, and allowing early diagnosis.

RNA-Based CTC Analysis Provides Prognostic Information in Metastatic Breast Cancer

In metastatic breast cancer (MBC) the molecular characterization of circulating tumor cells (CTCs) provides a unique tool to understand metastasis-biology and therapy-resistance. We evaluated the prognostic significance of gene expression in EpCAM⁽⁺⁾ CTCs in 46 MBC patients based on a long follow-up. We selected a panel consisting of stem cell markers (CD24, CD44, ALDH1), the mesenchymal marker TWIST1, receptors (ESR1, PGR, HER2, EGFR) and the epithelial marker CK-19. Singleplex RT-qPCR was used for TWIST1 and CK-19 and multiplex RT-qPCR for stem cell markers and receptors. A group of 19 healthy donors (HD) was used as control. Univariate (p = 0.001) and multivariate analysis (p = 0.002) revealed the prognostic value of combined gene expression of CK-19(+), CD44^high/CD24^low, ALDH1^high/CD24^low and HER2 over-expression for overall survival (OS). The Kaplan–Meier estimates of OS were significantly different in patients positive for CK-19 (p = 0.028), CD44^high/CD24^low (p = 0.002), ALDH1^high/CD24^low (p = 0.007) and HER2-positive (p = 0.022). Our results indicate that combined gene expression analysis in EpCAM⁽⁺⁾ CTCs provides prognostic information in MBC.

Single-cell RNA sequencing in breast cancer: Understanding tumor heterogeneity and paving roads to individualized therapy

Single‐cell RNA sequencing (scRNA‐seq) is a novel technology that allows transcriptomic analyses of individual cells. During the past decade, scRNA‐seq sensitivity, accuracy, and efficiency have improved due to innovations including more sensitive, automated, and cost‐effective single‐cell isolation methods with higher throughput as well as ongoing technological development of scRNA‐seq protocols. Among the variety of current approaches with distinct features, researchers can choose the most suitable method to carry out their research. By profiling single cells in a complex population mix, scRNA‐seq presents great advantages over traditional sequencing methods in dissecting heterogeneity in cell populations hidden in bulk analysis and exploring rare cell types associated with tumorigenesis and metastasis. scRNA‐seq studies in recent years in the field of breast cancer research have clustered breast cancer cell populations with different molecular subtypes to identify distinct populations that may correlate with poor prognosis and drug resistance. The technology has also been used to explain tumor microenvironment heterogeneity by identifying distinct immune cell subsets that may be associated with immunosurveillance and are potential immunotherapy targets. Moreover, scRNA‐seq has diverse applications in breast cancer research besides exploring heterogeneity, including the analysis of cell‐cell communications, regulatory single‐cell states, immune cell distributions, and more. scRNA‐seq is also a promising tool that can facilitate individualized therapy due to its ability to define cell subsets with potential treatment targets. Although scRNA‐seq studies of therapeutic selection in breast cancer are currently limited, the application of this technology in this field is prospective. Joint efforts and original ideas are needed to better implement scRNA‐seq technologies in breast cancer research to pave the way for individualized treatment management. This review provides a brief introduction on the currently available scRNA‐seq approaches along with their corresponding strengths and weaknesses and may act as a reference for the selection of suitable methods for research. We also discuss the current applications of scRNA‐seq in breast cancer research for tumor heterogeneity analysis, individualized therapy, and the other research directions mentioned above by reviewing corresponding published studies. Finally, we discuss the limitations of current scRNA‐seq technologies and technical problems that remain to be overcome.