Cancer is a highly heterogeneous disease that has high levels of phenotypic diversity due to molecular aberrations that occur at the genetic, epigenetic, transcriptomic, and protein levels in cells. Tumors are composed of various cell types that interact on several levels, presenting several challenges for treatment by contributing to metastasis and drug resistance. Sometimes, genetic variations that contribute to the diversity found in tumor cells affect only a small number of cells and can be difficult to detect. If researchers are to successfully find ways to treat tumors, they must first characterize this heterogeneity within tumors to understand the mechanisms of cancer pathogenesis and to develop effective treatment programs. As tumor research progresses, one powerful tool that is increasing in popularity is single-cell sequencing technology which has several important applications including studying tumor heterogeneity. This tool has also been used to provide further information on the genetic identity of the cells in a tumor which can help to discover the specific function of the cell groups, characterize the tumor immune microenvironment, and be used to examine drug-resistant metastasis [1, 2].
To respond to the growing needs of scientists involved in tumor research, Novogene offers a one-stop solution for investigating tumor single-cell characteristics from sample preparation to personalized analysis. Novogene provides a single-cell sequencing solution that takes care of all the details, from the preparation of single-cell suspensions right through to library sequencing and analysis. Novogene uses copy number variations (CNV) and single nucleotide polymorphisms (SNP) analysis to help to distinguish malignant and non-malignant tumor cells, as well as offering several other types of analysis including subsequent differential analysis and cell-to-cell relationship analysis to provide you with the perfect package to help answer all your research questions.
To ensure that Novogene reaches your research goals, sample preparation is tailored to meet researchers’ needs and takes into account the type of sample and research purpose. Novogene’s technology is based on the Tumor Dissociation Kit (human), which has been developed for the dissociation of primary human tumors and xenografts and is optimized for a wide range of tumor types, including melanoma, ovarian cancer, colon cancer, renal tumors, lung tumors, prostate cancer, breast cancer, and pancreatic cancer as well as head and neck squamous cell (HNSCC) tumors and hypopharyngeal tumors.
Tumor characteristic analysis content
CNV and SNP Analysis
Single-cell sequencing technology enables tumors to be classified and can assess the degree of malignancy of the cells or cell group. This technology enables us to understand which cells or cell groups are malignant or non-malignant and provides a good base from which further research can be done to understand how tumors progress [ 3, 4].
CNV analysis enables us to assess genomic alterations that result in an abnormal number of copies of a gene or multiple genes. These alterations are usually genomic rearrangements such as deletions, duplications, inversions, and translocations. Next-generation sequencing (NGS) is increasingly being used for CNV analysis because it has greater coverage than traditional methods. When combined with SNP analysis, it can be used to identify tumor cells and to examine tumor heterogeneity. Also, by examining the chromosomal pattern of single cells it might be possible to highlight the mutations that are driving both disease progression and the response to therapy [2, 5].
Ligand & Receptor Analysis
Tumors are composed of multiple cell types, including cancer cells and many non-malignant cell types such as immune, endothelial, and stromal cells. These cells form a cellular network and communicate by ligand-receptor interactions. Understanding the communication between cells via ligand and receptors is important to understand how cell type within the tumor cooperate to facilitate growth and spread, which has applications in understanding not only tumorigenesis but also development and drug resistance. Single-cell receptor-ligand analysis can be used to study cell-cell interactions and how this varies within a tumor. Understanding which cell populations play an important role in tumor growth and development can highlight which cell interactions should be targeted by therapy and where research should focus on [6, 7].
Single-cell technology has revolutionized cancer research, providing the means to detect rare cancer cells and has advanced the analysis of intra-tumor heterogeneity as well as tumor epigenetics. This technology has the potential to help guide treatment strategies by identifying the cells and/or cell interactions that are driving tumor progression. Novogene will be rolling out a one-stop solution for investigating tumor single-cell characteristics which will take you right from sample preparation to personalized analysis and help meet all your research needs.
 Fan, Jean, Kamil Slowikowski, and Fan Zhang. “Single-cell transcriptomics in cancer: Computational challenges and opportunities.” Experimental & Molecular Medicine 52.9 (2020): 1452-1465.
 Cariati, Federica, et al. “Dissecting Intra-Tumor Heterogeneity by the Analysis of Copy Number Variations in Single Cells: The Neuroblastoma Case Study.” International journal of molecular sciences 20.4 (2019): 893.
 Puram, Sidharth V., et al. “Single-cell transcriptomic analysis of primary and metastatic tumor ecosystems in head and neck cancer.” Cell 171.7 (2017): 1611-1624.
 Izar, B. et al. Dissecting the multicellular ecosystem of metastatic melanoma by single-cell RNA-sequencing.Cancer Research 76, 4380-4380, doi:10.1158/1538-7445.AM2016-4380 (2016).
 Petti, A. A. et al. A general approach for detecting expressed mutations in AML cells using single cell RNA-sequencing. Nat Commun 10, 3660, doi:10.1038/s41467-019-11591-1 (2019).
 Kumar, Manu P., et al. “Analysis of single-cell RNA-seq identifies cell-cell communication associated with tumor characteristics.” Cell reports 25.6 (2018): 1458-1468.
 Xiong, X. et al. Landscape of Intercellular Crosstalk in Healthy and NASH Liver Revealed by Single-Cell Secretome Gene Analysis. Mol Cell 75, 644-660 e645, doi:10.1016/j.molcel.2019.07.028 (2019).
To get more information about Novogene services, please visit our website: https://en.novogene.com/services/research-services/transcriptome-sequencing/single-cell-sequencing/