With advances in sequencing and instrument technology, bioinformatics analysis is being applied to batches of massive cells at single-cell resolution. High-throughput single-cell sequencing can be utilized for multi-omics characterization of tumor cells, stromal cells or infiltrated immune cells to evaluate tumor progression, responses to environmental perturbations, heterogeneous composition of the tumor microenvironment, and complex intercellular interactions between these factors. Particularly, single-cell sequencing of T cell receptors, alone or in combination with single-cell RNA sequencing, is useful in the fields of tumor immunology and immunotherapy. Clinical insights obtained from single-cell analysis are critically important for exploring the biomarkers of disease progression or antitumor treatment, as well as for guiding precise clinical decision-making for patients with malignant tumors. In this review, we summarize the clinical applications of single-cell sequencing in the fields of tumor cell evolution, tumor immunology, and tumor immunotherapy. Additionally, we analyze the tumor cell response to antitumor treatment, heterogeneity of the tumor microenvironment, and response or resistance to immune checkpoint immunotherapy. The limitations of single-cell analysis in cancer research are also discussed.

Background: Chromothripsis caused massive, clustered genomic rearrangements is prevalent in cancer and is considered a new paradigm for tumorigenesis and progression. In this study, we investigated the association among chromothripsis, anti-tumor immune responses, and responsiveness to immune checkpoint blockade (ICB). Methods: Quantification of immune cell infiltration and functional enrichment of immune-related signaling pathways were performed in the discovery set (n = 9403) and the validation set (n = 1140). we investigated the association between chromothripsis and anti-tumor immune responses. In the immunotherapy cohort, copy number alteration-based chromothripsis scores (CPSs) were introduced to assess the extent of chromothripsis to evaluate its association with responsiveness to ICB. Results: In the discovery set and the validation set, the ratios of CD8 + T cells to Tregs, TAMs, and MDSCs were significantly lower in tumors with chromothripsis (P = 1.5 × 10 − 13 , P = 5.4 × 10 − 8 , and P = 1.2 × 10 − 4 , respectively, TCGA; P = 1.0 × 10 − 13 , P = 3.6 × 10 − 15 , and P = 3.3 × 10 − 3 , respectively, PCAWG). The relevant pathways underlying the antitumor immune effect were significantly enriched in tumors without chromothripsis. Chromothripsis can be used as an independent predictor, and patients with low-CPSs experienced longer overall survival (OS) after immunotherapy [HR, 1.90; 95% confidence interval, 1.10−3.28; P = 0.019]. Conclusions: Our findings highlight the reduced cytotoxic immune infiltration in tumors with chromothripsis and enhanced immunosuppression in the tumor microenvironment. Chromothripsis can thus be used as a potential indicator to help identify patients who will respond to ICB, which could complement established biomarkers.

Immune checkpoint inhibitor (ICI) responses vary, and biomarkers for predicting responders are urgently needed. Growing evidence points to the association between programmed cell death protein ligand 2 (PDL2) and ICI benefits, while clinical evidences were lacking. Thus, we consolidated five public ICI-treated cohorts to investigate the association between PDL2 expression and ICI treatment prognosis. Immune cell signatures and IFN-γ signatures are investigated in The Cancer Genome Atlas (TCGA) dataset and later in ICI-treated cohorts to explore the association between PDL2 and antitumor immunity in the tumor microenvironment (TME). We found that immune cell signatures and IFN-γ signatures were enriched in the PDL2-high group in TCGA pooled cohorts and most cancers. Consistently, in ICI-treated cohorts, patients with high PDL2 expression experienced longer overall survival time (OS) and were more likely responsive to ICIs than patients with low PDL2 expression. Immune cell scores of the high PDL2 expression patients were significantly higher ( P < 0.05 ) than those of the low PDL2 expression patients in ICI-treated cohorts. In conclusion, our findings suggest that PDL2 is a potential predictive biomarker for ICIs.