Zhenget al.,Science 374 , eabe6474 (2021) 17 December 2021 2 of 11
Fig. 1. Pan-cancer T cell profile at the single-cell resolution.
(A) Schematics of pan-cancer single-cell transcriptome and TCR profiling of
T cells. (B) UMAP visualization of CD8+T cell metaclusters. Selective
metaclusters are highlighted by using their functional annotation: Tex,
exhausted T cells; ISG, interferon-stimulated genes; Temra, terminally
differentiated effector memory or effector; Tem, effector memory T cells; Trm,
tissue-resident memory T cells; Tn, naïve T cells; and KIR, killer cell
immunoglobulin-like receptors. (C) The same plot as in (B) applied to CD4+
T cells. (D) Bar plots showing the CD8+T cell compositions in the blood
(n= 46 patients), normal (n= 82 patients), and tumor (n= 197 patients) from
treatment-naïve patients (mean ± SD). Average diversity measured with the
Shannon equitability index for each tissue is shown. A high index indicated
similar frequencies across different metaclusters. (E) The same plots as in
(D) applied to CD4+T cells from blood (n= 15 patients), normal (n= 51 patients),
and tumor (n= 163 patients). (F) Heatmap showing the ORs of metaclusters
occurring in each tissue. OR > 1.5 indicates that the metacluster is preferred
to distribute in the corresponding tissue. Hierarchical clustering based on
cosine distance is applied for rows. The naming, numbering, and colors of the
metaclusters are in accordance with (B) and (C). (G) Scatter plot showing
the expansion index and the proliferation index of metaclusters in the tumor.
Metaclusters of high expansion (expansion index > 0.1,P< 0.01) are highlighted
in blue, and tumor-enriched metaclusters with significant expansion (P< 0.01)
and proliferation (index > 0.05) are highlighted in red. Size indicates the
number of cells (in log10 scale).RESEARCH | RESEARCH ARTICLE