Initiative of clinical single-cell biomedicine in clinical and translational medicine

Single-cell-based research has been developing for decades and has resulted in a new discipline of single-cell biology.^1-3 With rapid development of single-cell technologies, single-cell biology science has shown impact for identification and development of disease-specific biomarkers. The deep understanding of single-cell molecular and morphological phenomes provides new insights for the pathogenesis of human diseases and unites biological and medical science in the discipline of single-cell biomedicine.^4-6 Single-cell systems biomedicine was further advanced by multi-dimensional and molecular explorations of single-cell nuclear elements, signal networks, inter-organelle communication, and metabolism using single-cell multi-omics and trans-omics.^7-10 More recently, human single-cell atlases have the great impact in disease diagnosis and therapy, by discovering new cell subsets, disease-specific biomarkers, and therapeutic targets, monitoring dynamic responses to therapy, and predicting prognosis.¹¹ However, there are urgent needs to clarify the specificities of altered human single cell atlases in clinical phenomes, disease nature, severity, duration, stage, and response to therapy.

The journal of Clinical and Translational Medicine (CTM) launches the first CTM initiative of Clinical Single-Cell Biomedicine (cscBioMed) to promote the discovery and development of single-cell-based biology and medicine, speed the translation from single-cell biology into clinical application, and improve early diagnosis and therapy for human diseases. The cscBioMed has a clear goal to more accurately ensure the quality of human health and life using single-cell technologies. In order to achieve the goal to ensure the quality of human health and life, we organize the resources from single-cell biomedicine and create the new initiative of cscBioMed. The Initiative is targeting at acute and chronic infections and inflammations, cancers, and explosive epidemic diseases as monitoring and therapeutic areas, bus also at evaluation and prediction of health, sub-health, and aging. This is an international call for preclinical and clinical scientists and physicians to present the perspective hypotheses, creative thoughts, and advanced investigations for discovery and development of cscBioMed, to better understand associations between single-cell molecular and clinical phenomes, interactions among genes, proteins, and transcriptional factors, morphologies of spatial organization and remodeling, identities of cell subpopulations, and assemblies of an artificial intelligent cell. These are the important missions for cscBioMed

The cscBioMed initiative is speeding translational processes from circulating single-cell RNA sequencing (scRNA-seq) into routine measures in clinical biochemistry of hematology. There is rapid growing evidence that circulating single cells including leukocytes, red blood cells, and platelets are measured in various physiological and pathological conditions. Circulating scRNA-seq identities of new cell subsets or biology- and disease-specific clusters/subsets demonstrate the comprehensive capacity of systemic immune response during the progression of the disease. Circulating scRNA-seq can be a new measure of clinical biochemistry to monitor dynamical alternations of immune function and hematological hemostasis, although there remain a large number of challenges to overcome.¹² In addition to the general challenge of confirming the accurate cell subset identities, other factors (e.g., hydrodynamics, movements between organs, transit between functional states, and short half-life) may also influence the physiological reference ranges of each subset, and impact the biological and pathological significance of subset number and percentage, and disease-specific alterations. To meet the clinical standard of biochemistry, the settlement of subset reference range will require a large population of healthy participants in each age group, gender, and race categories. For example, scRNA-seq data from 1.27 million peripheral blood mononuclear cells from 982 donors demonstrated that 66% were only identified as cell state–specific effects from the dynamic analysis of expression quantitative trait locus.¹³ In addition to blood samples, cscBioMed will pay special attentions to single-cell phenomes and subsets in other biopsies, e.g., urine, cerebrospinal fluid, sputum, although studies on those aspects remain limited. For example, cell types and subsets as well as interactions in human nasal washing fluid measured by scRNA-Seq were found to represent host and viral transcriptional profiles and epithelial/immune cell responses at infective spatialization to COVID-19 and influenza.¹⁴

The cscBioMed initiative promotes the development of single-cell pathology for detection of single cell morphological phenomes, identities, and spatialization. Tissue morphological characteristics can be re-constructed by labelled tissue single cells with corresponding transcriptomic identities and profiles from scRNA-seq, although the accuracy of cell spatial specificities and variabilities remains to be improved, especially in the brain that is characterized by rich and complex intercellular connections and communication.¹⁵ Studies on human tissue scRNA-seq demonstrate immune cell clusters and interactions in the tumor microenvironment and define new identities of cancer cells and new categories of cancer subtypes. As the part of spatiotemporal molecular image and medicine, tissue scRNA-seq paired with spatial transcriptomics can provide comprehensive information on histological stratification, pathological phenomes, and molecular changes, even though the approaches still require optimization and standardization.^16-18 The Initiative will extend the concept of “single-cell pathology” into “single-cell image”, including images from computed tomography, nuclear magnetic resonance, and ultrasound. Clinical images can be enriched with histological stratifications, cell types and subsets, and transcriptomic profiles by integrating image, pathology, scRNAseq, and spatial transcriptome.^{18, 17} The combination of image mass cytometry with defined target biomarkers can demonstrate pathological spatial phenomes, distributions, heterogeneity, and stratification of tumor and stromal single cells to characterize intercellular connections and spatial patterns in the microenvironment, and uncover new subtypes of cancer and correlations with clinical outcomes.¹⁹ This particular method is suitable for validation of the biomarker panels discovered from scRNA-seq integrated with spatial transcriptomics or multi-/trans-omics, for translating comprehensive and spatiotemporal single-cell phenomes into pathological measures and for developing clinical diagnostics of single-cell pathology in a large scale clinical applications. Single-cell pathology may provide the direct information to identify new histological phenomes, subtypes, and categories of disease, severity, and response to drugs. Integrating single-cell multi-omics with pathological spatialization and temporalization makes it possible to create the artificial intelligence-based “whole cell model³” from single-cell biology into clinical values.

The cscBioMed initiative is accelerating the process from discovery and development of disease-specific diagnostic biomarkers and therapeutic targets on the basis of single-cell multi-omics/trans-omics into clinical diagnostics and target drugs.

Different from bulk multi/trans-omics, the single-cell multi/trans-omics provides multi-dimensional and comprehensive insights for locating more precise cell types of target molecules, defining the roles in intercellular functions, and clarifying the specificity of intercellular and interorganellar target-dominated signals. More recent studies demonstrating the value and impact of single-cell multi-omics in detecting various alternations of microenvironmental cardiac cell status, spatialization, interactions with other cells have highlighted the multi-layer molecular networks, and cell type or phenome-based remodeling in cardiac disease.²⁰ Different from scRNA-seq, single-cell multi/trans-omics presents a stereoscopic regulatory networks and functional view of target-oriented molecular panels, illustrates intercellular heterogeneities and interactions, and uncovers the relationship between target spatialization and temporalization, disease nature and phenomes, and patient outcomes. The Initiative will explore the special impact of single-cell transcriptomic profiles in DNA mutations, modifications, and regulations, in target-based individualized therapy, and in immunotherapy. Thus, the validation of scRNA-seq-based discoveries is critically important goal for translational medicine and science, with current emphasis on defining the specificity of single-cell molecular phenomes and functions and correlating with clinical phenomes and response to therapies.

The cscBioMed initiative is gathering international single-cell experts and working to translate discovery and development of clinical challenges-oriented and based single-cell knowledge, diagnoses, and therapies, in partnership with scientific communities, universities, hospitals, and organizations. The initiative strives to better understand and solve practical challenges during implementation, e.g., how to make the expensive testing costs acceptable, complex measures applicable, required equipments certifiable, comprehensive processes standardizable, massive-scale data analyses efficient, clinical explanations accurate and reliable, quality controls accessible, and clinical physicians understandable. It is also necessary to have specific regulations and protocols to apply scRNA-seq in clinical practice. To meet those challenges, cscBioMed Initiative will accelerate the translational process to ensure that the measures of clinical scRNA-seq and single-cell pathology are accurate, efficient, repeatable, unexpensive, user friendly, and accessible. This will provide new opportunities to identify new cell types and subsets, generate comprehensive information on immune function evaluation, define disease- or therapy-specific heterogeneity and cell-cell interaction, and develop biomarkers and targets specific to disease nature, severity, and outcome. We expect that cscBioMed will benefit the human health by establishing a clinical single-cell dynamic monitoring and early predicting system and by improving diagnosis and treatment.

CONFLICT OF INTEREST

The authors declare no conflict of interest.