Single-cell sequencing reveals antitumor characteristics of intratumoral immune cells in old mice

Abstract

BackgroundAging has long been thought to be a major risk factor for various types of cancers. However, accumulating evidence indicates increased resistance of old animals to tumor growth. An in-depth understanding of how old individuals defend against tumor invasion requires further investigations.MethodsWe revealed age-associated alterations in tumor-infiltrating immune cells between young and old mice using single-cell RNA and coupled T cell receptor (TCR) sequencing analysis. Multiple bioinformatics methods were adopted to analyze the characteristics of the transcriptome between two groups. To explore the impacts of young and old CD8+ T cells on tumor growth, mice were treated with anti-CD8 antibody every 3 days starting 7 days after tumor inoculation. Flow cytometry was used to validate the differences indicated by sequencing analysis between young and old mice.ResultsWe found a higher proportion of cytotoxic CD8+ T cells, naturally occurring Tregs, conventional dendritic cell (DC), and M1-like macrophages in tumors of old mice compared with a higher percentage of exhausted CD8+ T cells, induced Tregs, plasmacytoid DC, and M2-like macrophages in young mice. Importantly, TCR diversity analysis showed that top 10 TCR clones consisted primarily of exhausted CD8+ T cells in young mice whereas top clones were predominantly cytotoxic CD8+ T cells in old mice. Old mice had more CD8+ T cells with a ‘progenitor’ and less ‘terminally’ exhausted phenotypes than young mice. Consistently, trajectory inference demonstrated that CD8+ T cells preferentially differentiated into cytotoxic cells in old mice in contrast to exhausted cells in young mice. Importantly, elimination of CD8+ T cells in old mice during tumor growth significantly accelerated tumor development. Moreover, senescent features were demonstrated in exhausted but not cytotoxic CD8+ T cells regardless of young and old mice.ConclusionsOur data revealed that a significantly higher proportion of effector immune cells in old mice defends against tumor progression, providing insights into understanding the altered kinetics of cancer development and the differential response to immunotherapeutic modulation in elderly patients.

Therapy-induced senescence drives immunotherapy resistance by inducing an immunosuppressive tumor microenvironment

“…Note that tumor growth was delayed in mice previously exposed to TIS compared to control mice (see Fig. 1B and 2B), a phenotype also observed by others and possibly mediated by a modulation of the immunosuppressive TME composition [28,29]. Tumor growth delay in TBI mice was not changed by treatments with GCV alone.…”

Construction of a cross-species cell landscape at single-cell level

“…Therefore, all available cell type clusters in mapping pipelines were generated from single-cell studies, and the cell landscapes with a wide range of life stages as well as single tissue datasets would allow for more precise annotation of cell types with temporal correlation, providing tissue and age information. By using our updated scMCA, we could easy classify conventional dendritic cells (cDCs), plasmacytoid dendritic cells (pDCs), natural killer (NK) cells, neutrophils, T cells, macrophages and monocytes in isolated tumors of young (6–8 weeks) and old (20–22 months) mice ( 75 ) (Figure 4C ). These cells from tumors were highly correlated with adult (6–8 weeks) and aging (18 and 24 months) mice, rather than newborn and juvenile mice.…”

Combination of oral STING agonist MSA-2 and anti-TGF-β/PD-L1 bispecific antibody YM101: a novel immune cocktail therapy for non-inflamed tumors

“…The rest of subcluster was assigned as memory-like T cells ( Il7r + Icos + Gzmb − Gzmk − ) (Fig. 7 f–h) [ 36 ]. Relative to other T cell subclusters, CD8 + effector had multiple significantly enriched metabolism pathways, including arginine, proline, histidine, glutathione, glycine, serine, threonine, phenylalanine, taurine, and hypotaurine (Fig.…”

“…Then, to validate the annotations of SingleR, we calculated the levels of immune cell-specific markers based on previous studies [ 34 , 35 ]. The annotations of T cell subclusters were based on previously identified markers [ 36 , 37 ]. The annotations of NK cell subclusters were according to Itgam and Cd27 levels [ 38 ].…”