The Ratio of Exhausted to Resident Infiltrating Lymphocytes Is Prognostic for Colorectal Cancer Patient Outcome.
Momeneh ForoutanRamyar MolaniaAline PfefferleCorina C BehrenbruchSebastian ScheerAxel KalliesTerence P SpeedJoseph CursonsNicholas D HuntingtonPublished in: Cancer immunology research (2021)
Immunotherapy success in colorectal cancer is mainly limited to patients whose tumors exhibit high microsatellite instability (MSI). However, there is variability in treatment outcomes within this group, which is in part driven by the frequency and characteristics of tumor-infiltrating immune cells. Indeed, the presence of specific infiltrating immune-cell subsets has been shown to correlate with immunotherapy response and is in many cases prognostic of treatment outcome. Tumor-infiltrating lymphocytes (TIL) can undergo distinct differentiation programs, acquiring features of tissue-residency or exhaustion, a process during which T cells upregulate inhibitory receptors, such as PD-1, and lose functionality. Although residency and exhaustion programs of CD8+ T cells are relatively well studied, these programs have only recently been appreciated in CD4+ T cells and remain largely unknown in tumor-infiltrating natural killer (NK) cells. In this study, we used single-cell RNA sequencing (RNA-seq) data to identify signatures of residency and exhaustion in colorectal cancer-infiltrating lymphocytes, including CD8+, CD4+, and NK cells. We then tested these signatures in independent single-cell data from tumor and normal tissue-infiltrating immune cells. Furthermore, we used versions of these signatures designed for bulk RNA-seq data to explore tumor-intrinsic mutations associated with residency and exhaustion from TCGA data. Finally, using two independent transcriptomic datasets from patients with colon adenocarcinoma, we showed that combinations of these signatures, in particular combinations of NK-cell activity signatures, together with tumor-associated signatures, such as TGFβ signaling, were associated with distinct survival outcomes in patients with colon adenocarcinoma.
Keyphrases
- rna seq
- single cell
- nk cells
- genome wide
- electronic health record
- high throughput
- peripheral blood
- big data
- public health
- end stage renal disease
- squamous cell carcinoma
- chronic kidney disease
- newly diagnosed
- ejection fraction
- locally advanced
- epithelial mesenchymal transition
- deep learning
- radiation therapy
- artificial intelligence
- quality improvement
- signaling pathway
- machine learning
- rectal cancer