Investigating Mechanisms of Response or Resistance to Immune Checkpoint Inhibitors by Analyzing Cell-Cell Communications in Tumors Before and After Programmed Cell Death-1 (PD-1) Targeted Therapy: An Integrative Analysis Using Single-cell RNA and Bulk-RNA Sequencing Data

Abstract

Currently, a significant proportion of cancer patients do not benefit from programmed cell death-1 (PD-1)-targeted therapy. Overcoming drug resistance remains a challenge. In this study, single-cell RNA sequencing and bulk RNA sequencing data from samples collected before and after anti-PD-1 therapy were analyzed. Cell-cell interaction analyses were performed to determine the differences between pretreatment responders and nonresponders and the relative differences in changes from pretreatment to posttreatment status between responders and nonresponders to ultimately investigate the specific mechanisms underlying response and resistance to anti-PD-1 therapy. Bulk-RNA sequencing data were used to validate our results. Furthermore, we analyzed the evolutionary trajectory of ligands/receptors in specific cell types in responders and nonresponders. Based on pretreatment data from responders and nonresponders, we identified several different cell-cell interactions, like WNT5A-PTPRK, EGFR-AREG, AXL-GAS6 and ACKR3-CXCL12. Furthermore, relative differences in the changes from pretreatment to posttreatment status between responders and nonresponders existed in SELE-PSGL-1, CXCR3-CCL19, CCL4-SLC7A1, CXCL12-CXCR3, EGFR-AREG, THBS1-a3b1 complex, TNF-TNFRSF1A, TNF-FAS and TNFSF10-TNFRSF10D interactions. In trajectory analyses of tumor-specific exhausted CD8 T cells using ligand/receptor genes, we identified a cluster of T cells that presented a distinct pattern of ligand/receptor expression. They highly expressed suppressive genes like HAVCR2 and KLRC1, cytotoxic genes like GZMB and FASLG and the tissue-residence-related gene CCL5. These cells had increased expression of survival-related and tissue-residence-related genes, like heat shock protein genes and the interleukin-7 receptor (IL-7R), CACYBP and IFITM3 genes, after anti-PD-1 therapy. These results reveal the mechanisms underlying anti-PD-1 therapy response and offer abundant clues for potential strategies to improve immunotherapy.

Keywords: Single-cell rna sequencing; cell-cell interaction; immune checkpoint blockade; immunotherapy; programmed cell death-1.

Figure 1.

Study overview, analysis of the tumor microenvironment in patients before and after anti-PD-1 treatment with scRNA-seq, and marker ligands/receptors in specific cell types

Figure 2.

Comparison of pretreatment responders and nonresponders

Figure 3.

Relative differences in changes from pretreatment to posttreatment status between responders and nonresponders

Figure 4.

Relative differences in changes in specific ligand-receptor pairs between responders and nonresponders with “Relative Ratio” >2 or <0.5 (overlapping with DEGs from the Riaz et al. study)

Figure 5.

Relative differences in changes in specific ligand-receptor pairs between responders and nonresponders with “Relative Ratio” >2 or <0.5 (overlapping with DEGs identified in the Riaz et al. study)

Figure 6.

“Ligand-receptors Pairs Related to Response On Treatment” with significant relative differences in changes between responders and nonresponders in our study

Figure 7.

Trajectory Analyses of All Cell Types and Tumor-Specific CD8 T cells Using Ligand/Receptor-Related Genes

Figure 8.

Validation of the “Ligand-receptor Pairs Related to Response Before Treatment” and the “Ligand-receptor Pairs Related to Response On Treatment) with additional immunotherapy datasets