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Uncovering Potential Therapeutic Targets for drug development through single cell Sequencing Techniques

In recent years, single cell sequencing techniques have emerged as powerful tools in the field of drug development. These techniques allow researchers to study individual cells, providing unprecedented insights into cellular behavior and function. By uncovering potential therapeutic targets for drug development, single cell sequencing techniques have the potential to revolutionize medical research. When compared to Traditional sequencing, Single cell RNA sequencing (scRNA-seq) technology is a more valuable tool for identifying new potential targets because they show changes in gene expression of cells in response to different types of conditions.

Table 1. The limitation of traditional bulk sequencing and the advantages of Single Cell Sequencing

Traditional bulk Sequencing Single Cell Sequencing
Analyzes mixtures of cells Can analyze individual cells
Difficult to distinguish between different cell types Can identify cell types and subtypes
Provides a limited view of gene expression for a whole tissue or cell population Generates a comprehensive profile of gene expression for individual cells
May miss rare mutations or gene expression changes in subpopulations of cells Can detect rare mutations or gene expression changes in subpopulations of cells
Limited ability to identify therapeutic targets Can identify potential therapeutic targets based on cell type-specific gene expression
Limited ability to study cellular heterogeneity Can study cellular heterogeneity and identify subpopulations of cells involved in disease pathology

Identify TNBC immunotherapy target

In pursuit of new tumor immunotherapy targets for triple negative breast cancer (TNBC), Ji et al. applied Novogene’s bulk RNA-seq and scRNA-seq strategy to identify Lgals2, gene encoding galectin-2, as a potential target.[1] Following in vivo CRISPR screens targeting disease-related immune genes in TNBC mouse models, Ji et al. employed transcriptomic analysis to identify candidate genes, and chose Lgals2 for further inquiry. Notably, increased Lgals2 expression levels in vivo—but not in vitro—correlated with enhanced tumor cell proliferation. scRNA-seq further revealed multiple transcriptional clusters of immune cells altered in Lgals2-overexpressing mice. In particular, the scRNA-seq data pointed to macrophage compartment remodeling induced by tumor cell overexpression of Lgals2. Subsequent experiments showed that anti-LGALS2 antibody treatment slowed tumor growth and decreased macrophage proliferation, thus demonstrating the value of transcriptomics in identifying potential therapeutic targets.

Reveal potential prognostic marker

Because the tumor microenvironment (TME) influences factors such as tumor progression, treatment resistance, and metastasis,[2] understanding the TME is also important for considering prognostic factors and therapeutic targets. Luo et al. employed Novogene’s single-cell transcriptomic sequencing capabilities to comprehensively profile the commonalities, heterogeneities, and plasticity of cancer-associated fibroblasts (CAFs) which are the predominant component of the TME.[2] Luo et al. developed a single-cell transcriptional atlas for common solid cancer types from public and in-house scRNA-seq data to systematically characterize CAFs across cancers. Notably, they found that CAFs had multiple states of differentiation, each with specific biofunctions. In particular, the most de-differentiated state predicted worse immunotherapy outcomes, suggesting that evaluating a patient’s CAF differentiation state may be prognostic for immunotherapy decisions.

Uncover potential therapeutic targets

Single-cell transcriptome sequencing technologies have considerable applicability beyond cancer. For example, Liu et al. used single-cell transcriptional profiling of bone marrow (BM) hematopoietic stem cells (HSPCs) to investigate potential contributions of hematopoietic differentiation to ITP (immune thrombocytopenia) pathogenesis.[3] Analyses of their single-cell transcriptomic atlas of HSPCs in ITP BM versus healthy controls revealed multiple transcriptome alterations in hematopoiesis during ITP, including activation of immune states during most phases. In another example, Tang et al. used single-cell multi-omics technology to investigate MAIT (mucosal-associated invariant T) cell dysfunction in HIV-1 infected individuals, a phenomenon which contributes to vulnerability to bacterial infection.[4] Using a combination of Abseq (oligo-conjugated antibodies) and scRNA-seq, they developed transcriptomic and proteomic expression profiles. Analyzing those profiles revealed that MAIT cells in HIV-1-infected patients were characterized by immune activation, suggesting a role for IFN-I activation. Additional experiments showed that MAIT cells’ antibacterial response could be restored in vitro by blocking IFNAR or IL-10R. Together, these studies illustrate how transcriptome profiling strategies, and in particular single-cell transcriptional profiling, can elucidate characteristics of cell types within very different diseases that can then be used to identify potential therapeutic targets or pathways.

In conclusion, single cell sequencing techniques have the potential to revolutionize drug development by uncovering potential therapeutic targets and improving patient outcomes. By providing unprecedented insights into cellular behavior and function, these techniques can help identify rare cell populations, genetic mutations, and treatment response predictors that may be missed by traditional sequencing methods. As technology continues to advance, single cell sequencing is likely to become an increasingly important tool in the fight against diseases.


[1]. Ji P et al. In vivo multidimensional CRISPR screens identify Lgals2 as an immunotherapy target in triple-negative breast cancer. Sci Adv. 2022;8;eabl8247.

[2]. Luo H et al. Pan-cancer single-cell analysis reveals the heterogeneity and plasticity of cancer-associated fibroblasts in the tumor microenvironment. Nat Commun. 2022;13;6619.

[3]. Liu Y et al. Deciphering transcriptome alterations in bone marrow hematopoiesis at single-cell resolution in immune thrombocytopenia. Signal Transduct Target Ther. 2022;7.

[4]. Tang X et al. Sustained IFN-I stimulation impairs MAIT cell responses to bacteria by inducing IL-10 during chronic HIV-1 infection. Sci Adv. 2020;6;eaaz0374.