Single-Cell Transcriptomics in Cancer Immunobiology: The Future of Precision Oncology

Abstract

Cancer is a heterogeneous and complex disease. Tumors are formed by cancer cells and a myriad of non-cancerous cell types that together with the extracellular matrix form the tumor microenvironment. These cancer-associated cells and components contribute to shape the progression of cancer and are deeply involved in patient outcome. The immune system is an essential part of the tumor microenvironment, and induction of cancer immunotolerance is a necessary step involved in tumor formation and growth. Immune mechanisms are intimately associated with cancer progression, invasion, and metastasis; as well as to tumor dormancy and modulation of sensitivity to drug therapy. Transcriptome analyses have been extensively used to understand the heterogeneity of tumors, classifying tumors into molecular subtypes and establishing signatures that predict response to therapy and patient outcomes. However, the classification of the tumor cell diversity and specially the identification of rare populations has been limited in these transcriptomic analyses of bulk tumor cell populations. Massively-parallel single-cell RNAseq analysis has emerged as a powerful method to unravel heterogeneity and to study rare cell populations in cancer, through unsupervised sampling and modeling of transcriptional states in single cells. In this context, the study of the role of the immune system in cancer would benefit from single cell approaches, as it will enable the characterization and/or discovery of the cell types and pathways involved in cancer immunotolerance otherwise missed in bulk transcriptomic information. Thus, the analysis of gene expression patterns at single cell resolution holds the potential to provide key information to develop precise and personalized cancer treatment including immunotherapy. This review is focused on the latest single-cell RNAseq methodologies able to agnostically study thousands of tumor cells as well as targeted single-cell RNAseq to study rare populations within tumors. In particular, we will discuss methods to study the immune system in cancer. We will also discuss the current challenges to the study of cancer at the single cell level and the potential solutions to the current approaches.

The inflammasome of circulatory collapse: single cell analysis of survival on extracorporeal life support

“…This technology holds the promise to uncover new information about the pathophysiology of complex disease states in high detail. Initial efforts in this direction with human material have focused on cancer (4,(19)(20)(21), although examples in other diseases are emerging (22,23) including one example of identification of a PBMC repertoire associated tuberculosis progression (2) and a second related to survival in acute infectious disease based on analysis of ~100 cells from 2 patients (3).…”

“…Single cell transcriptomic approaches continue to modify and expand our understanding of the function and classification of PBMC subsets (2,3). The degree to which these sophisticated approaches will lead to clinically actionable information remains to be established (4). To that end, we here took an integrated approach combining plasma cytokine quantification, flow cytometry, and single cell transcriptomics to address the challenging question of why some patients survive on VA-ECLS while many do not.…”

Single-cell RNA-sequencing of peripheral neuroblastic tumors reveals an aggressive transitional cell state at the junction of an adrenergic-mesenchymal transdifferentiation trajectory

“…Among non-malignant cells, we found that non-neuroblastoma samples have a higher proportion of infiltrating immune cells compared with neuroblastoma samples, especially cytotoxic T-cells. Cytotoxic T-cells are a key player in tumor surveillance and inhibition of tumor growth by secreting cytokines as well as perforin or Fas-mediated cytotoxic response 47 . Therefore, it is an important target of immunotherapy and considered as an important prognostic indicator in many cancers, including neuroblastoma 29,48 .…”

Single cell transcriptomics reveals involution mimicry during the specification of the basal breast cancer subtype

“…We have previously demonstrated that tumour infiltrated myeloid-derived suppressor cells (MDSCs) are involved in the formation of lung metastasis in PyMT/ELF5 alveolar tumours 15 . As tumour infiltrated myeloid cells constitute a low abundance population 51 we kept it as a unique cell cluster, however, our scRNAseq analysis was able to map the cellular mechanism for MDSC expansion, recruitment and malignant activation previously described in these alveolar tumours 52 , identifying the cell of origin of well-known signalling pathways involved in this process (Fig. 7D).…”