Tumor Cell Heterogeneity and Plasticity Analysis

Tumor cells possess a remarkable ability to adapt and transition between different phenotypic states, a phenomenon known as cellular plasticity. At Alfa Cytology, we offer cutting-edge analysis services to explore the intricacies of tumor cell heterogeneity and plasticity, empowering researchers to uncover the key drivers of cancer evolution.

Introduction

Tumor heterogeneity, which includes genetic heterogeneity, epigenetic heterogeneity, phenotypic and functional heterogeneity, plays a crucial role in tumor progression. The origin of tumor heterogeneity has been the focus of academic research. For example, theories of cancer stem cells, clonal evolution and cellular plasticity have been proposed to explain the origin of heterogeneity. Previously, high-throughput sequencing technologies have been used in cancer research to classify molecular subtypes, monitor treatment response, identify new therapeutic targets, and explore tumor heterogeneity.

Cancer cell plasticity refers to the dynamic migration of some cancer cells between different cellular states, which leads to increased tumor heterogeneity and promotes tumor progression. For example, during primary tumorigenesis, progression and metastasis, cancer cells require cellular identity and plasticity during transitions such as epithelial-mesenchymal transition (EMT) and mesenchymal-epithelial transition (MET). The functional roles of EMT, MET and partial states (called pEMT) may vary depending on tumor type, diffusion status and degree of metastatic colonization. However, the molecular mechanisms that regulate cellular plasticity remain elusive.

Our Services

Recent studies on cellular heterogeneity and plasticity have shown their great potential in tumors, greatly enriching our understanding of tumors, providing new perspectives to explore the mechanisms of tumor cell genesis and development, and laying the foundation for subsequent research in tumor treatment and prevention. For example, recent studies have suggested that drug resistance in tumor cells may be due to non-genetic adaptive mechanisms such as tumor cell plasticity, rather than genetic mutations that cause cellular plasticity properties, resulting in reversible switching between drug-tolerant and drug-sensitive phenotypes or states, thus escaping drug attack and surviving. Alfa Cytology has developed several technologies to provide solutions for the study of tumor cell heterogeneity and plasticity, thus providing guidance for new targets and strategies for tumor drug resistance.

Key Technologies

Single-cell technologies show great advantages in profiling cell composition and their molecular signatures, offering the opportunity to reveal the mixed state of individual cells. Single-cell RNA sequencing has identified a variety of mixed states of cancer cells in human cancers, such as mixed EMT cells and cancer / immune cells. In addition, single-cell technology has a powerful ability to identify rare cell populations. Finally, single-cell technologies can distinguish between tumor and non-tumor cell components and also infer the interactions within or between these cell components. Thus, it can easily understand the heterogeneity between tumor cells and the plasticity of dynamic migration.

Spatial transcriptomics (ST) is also a very good choice because it can also restore the spatial structure of tumor tissues, allowing studies to be more realistic and easier to understand the heterogeneity and plasticity of tumor cells.

Alfa Cytology is committed to supporting scientists in making breakthrough scientific discoveries and developing new applications to accelerate new drug discovery and scientific diagnosis and treatment. Our high-performance scientific instruments and high-value solutions enable scientists to explore the mysteries of life at the tumor microenvironment level. Please tell us your project requirements, and we will provide you with a full service from solution to report. If you have any questions, please feel free to contact us.

For research use only.