Cancers are a group of heterogeneous diseases characterized by the acquisition of functional capabilities during the transition from a normal to a neoplastic state. Powerful experimental and computational tools can be applied to elucidate the mechanisms of occurrence, progression, metastasis, and drug resistance; however, challenges remain. Bulk RNA sequencing techniques only reflect the average gene expression in a sample, making it difficult to understand tumor heterogeneity and the tumor microenvironment. The emergence and development of single-cell RNA sequencing (scRNA-seq) technologies have provided opportunities to understand subtle changes in tumor biology by identifying distinct cell subpopulations, dissecting the tumor microenvironment, and characterizing cellular genomic mutations. Recently, scRNA-seq technology has been increasingly used in cancer studies to explore tumor heterogeneity and the tumor microenvironment, which has increased the understanding of tumorigenesis and evolution. This review summarizes the basic processes and development of scRNA-seq technologies and their increasing applications in cancer research and clinical practice. 

Advances in single-cell RNA sequencing and its applications in cancer research

Background & AimsHepatitis B surface antigen (HBsAg) secretion may impact the immune response in chronic hepatitis B virus (HBV) infection. Therapeutic approaches to suppress HBsAg production are being investigated. Our study aims to examine the immunomodulatory effects of high and low levels of circulating HBsAg by analyzing single-cell RNA sequencing data (scRNAseq) from blood and liver fine-needle aspirates (FNA). This will help to better understand anti-HBV immunity.MethodsAn optimized 10X Genomics scRNAseq-workflow was applied to blood and FNA samples from 18 patients undergoing tenofovir or entecavir treatment (NUC) for chronic HBV infection. They were categorized based on their HBsAg levels: high (920-12447 IU/mL) or low (1-100 IU/mL). Cluster frequencies, differential gene expression, and phenotypes were analyzed.ResultsIn blood of HBV patients on NUC, the proportion of KLRC2+ “adaptive” NK cells were significantly lower in the HBsAg high group and, remarkably, both the KLRC2+ NK- and KLRG1+ CD8 T cells display enrichment of lymphocyte activation-associated gene sets in the HBsAg low group. High levels of HBsAg were associated with mild immune activation in the liver. However, no suppression, of liver-resident CXCR6+ NCAM1+ NK- and CXCR6+ CD69+ CD8 T cells were detected, while memory B cells showed signs of activation in both blood and liver.ConclusionsAmong NUC-treated HBV patients, we observed a minimal impact of HBsAg on leukocyte populations in the blood and liver. However, here we show for the first time that HBsAg has distinct effects in blood and liver restricted to NK-, CD8 T-, and memory B cell subsets. Our findings are highly relevant for current clinical studies evaluating treatment strategies aimed at suppressing HBsAg production and reinvigorating immunity to HBV. 

Association of HBsAg levels with differential gene expression in NK, CD8 T, and memory B cells in treated patients with chronic HBV

The impact of nucleos(t)ide analogues on intrahepatic viral burden and immune microenvironment in patients with chronic hepatitis B (CHB) is not clear. 

Effects of tenofovir disoproxil fumarate on intrahepatic viral burden and liver immune microenvironment in patients with chronic hepatitis B

PURPOSE OF REVIEW
The future of medicine is aimed to equip the physician with tools to assess the individual health of the patient for the uniqueness of the disease that separates it from the rest. The integration of omics technologies into clinical practice, reviewed here, would open new avenues for addressing the spatial and temporal heterogeneity of cancer. The rising cancer burden patiently awaits the advent of such an approach to personalized medicine for routine clinical settings.


RECENT FINDINGS
To weigh the translational potential, multiple technologies were categorized based on the extractable information from the different types of samples used, to the various omic-levels of molecular information that each technology has been able to advance over the last 2 years. This review uses a multifaceted classification that helps to assess translational potential in a meaningful way toward clinical adaptation.


SUMMARY
The importance of distinguishing technologies based on the flow of information from exploration to actuation puts forth a framework that allows the clinicians to better adapt a chosen technology or use them in combination to enhance their goals toward personalized medicine.

Explore & actuate: the future of personalized medicine in oncology through emerging technologies.

Background & Aims Suppression of HBV DNA, inhibition of HBsAg production and therapeutic vaccination to reverse HBV-specific T-cell exhaustion in chronic HBV patients are likely required to achieve functional cure. In the AAV-HBV mouse model, therapeutic vaccination can be effective in clearing HBsAg when hepatitis B surface (HBsAg) levels are low. The factor(s) required for mounting an effective immune control of HBV infection are unclear. Using a single-cell approach, we investigated the liver immune environment in the context of different levels of HBsAg as well as upon sustained HBsAg loss through treatment with an HBV specific GalNAc-siRNA followed by therapeutic vaccination. Methods C57BL/6 mice were transduced with a range of rAAV-HBV DNA to express different HBsAg levels. Mice were treated with GalNAc-siRNA targeting HBV transcripts to lower the HBsAg levels and then vaccinated 4 times with a DNA vaccine encoding HBV Core, Pol and Surface. We used single-cell RNA-sequencing on homogenised liver resident cells, paired with single-cell V(D)J receptor sequencing to understand the changes in the liver immune microenvironment. Results Treatment with GalNAc-HBV siRNA followed by therapeutic vaccination, achieved a sustained HBsAg loss in all mice. This was accompanied by an induction of CD4 follicular helper T-cell responses, polyclonal activation of CD8 T-cells in the liver and clonal expansion of plasma cells that were responsible for antibody production. Conclusions This study provides novel insight into the immune changes in the liver at the single-cell level, highlighting the correlation between the induced reduction in HBsAg levels and the clonal expansion of CD4 follicular helper T-cells, CD8 cytotoxic T-cells, plasma cells, and ISG-producing neutrophils in the liver upon HBV siRNA and subsequent therapeutic vaccine treatment. Lay Summary Chronic hepatitis B infection is characterized by a complex interplay between immune responses and viral replication in the liver. To achieve functional cure a combination of different treatments is likely required. In this study single-cell approach was used to understand the liver microenvironment in the context of different HBsAg levels followed by therapeutic vaccination in AAV-HBV mouse model and to identify key factors required to achieve functional cure. Graphical abstract Highlights AAV-HBV transduced mice sequentially treated with GalNAc-siRNA and therapeutic vaccine showed sustained HBsAg loss. The sustained HBsAg loss correlates with increased proportion and clonal expansion of CD4 follicular helper T-cells, CD8 cytotoxic T-cells, plasma cells, and ISG producing neutrophils in the liver. Baseline levels of HBsAg are important to determine outcome of therapeutic vaccination in mice.

Sustained liver HBsAg loss and clonal T and B cell expansion upon therapeutic DNA vaccination require low HBsAg levels

Single-cell RNA sequencing of liver fine-needle aspirates captures immune diversity in the blood and liver in chronic hepatitis B patients.

Profiling Transcriptional Heterogeneity with Seq-Well S3: A Low-Cost, Portable, High-Fidelity Platform for Massively Parallel Single-Cell RNA-Seq.

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Single-cell RNA sequencing of liver fine-needle aspirates captures immune diversity in the blood and liver in chronic hepatitis B patients.

Profiling Transcriptional Heterogeneity with Seq-Well S3: A Low-Cost, Portable, High-Fidelity Platform for Massively Parallel Single-Cell RNA-Seq.