Intra Immune nalysis Surface Supplementary Figure 1. Flow cytometry panels used for D Canto () and D Fortessa (). Name Fluorochrome ID F488 PE PerCp-Cy5.5 PC Paclue PE-Cy7 PC-H7 Lympho* 1 CD56 CD8 CD16 CD3 CD45 CD19 CD4 T1* 2 CD4 CD38 HL-DR CD45R CCR7 CD3 CD8 T2 3 CD45 Tim-3 CD8 LG3 CD3 PD-1 CD4 T2 iso 4 CD45 iso CD8 iso CD3 iso CD4 T3 5 CD4 Tim3 CD8 CD45RO CD3 PD-1 CD45R T4 6 CD11a CD69 CD8 CXCR3 CD3 PD-1 CD4 Myelo* 7 CD45 CD66b HL-DR CD33 CD14 CD123 CD16 Tumor* 8 CD45 PD-L2 CD66b PD-L1 CD33 EpCM CD14 Tumor iso* 9 CD45 iso CD66b iso (PD-L1) CD33 EpCM CD14 T1 1 CD45 CTL-4 CD8 FOXP3 CD3 PD-1 CD4 T2 11 CD45 iso CD8 FOXP3 CD3 iso CD4 T3 12 CD45 Tim-3 CD8 FOXP3 CD3 Ki67 CD4 Sorting 1 CD45 CD56 CD8 CD33 EpCM CD4 CD16
% T im -3 + /P D -1 + % T im -3 + /P D -1 + Supplementary Figure 2. PD-1/TIM-3 co-expression by CD8 + T cells () and CD4 + T cells () based on clinical features. C D 8 T IM 3 + /P D 1 + 1 9 8 7 6 *** ** *** *** * 5 4 3 2 1 s m o k e r n e v e r s m o k e r s q u a m o u s a d e n o c a r c in o m a n o r m a l lu n g K R S n e ith e r E G F R T C + T C -/IC + n e g a tiv e C D 4 T IM 3 + /P D 1 + 1 9 8 7 *** ** *** ** * 6 5 4 3 2 1 s m o k e r n e v e r s m o k e r s q u a m o u s a d e n o c a r c in o m a n o r m a l lu n g K R S n e ith e r E G F R T C + T C -/IC + n e g a tiv e
% P D -L 1 (E p C M ) % P D -L 1 in E p C M (flo w ) Supplementary Figure 3. Percent of PD-L1 + epithelial cells (EpCM + ) detected by flow correlates with the percent of PD-L1 in tumor cells by IHC (). oth correlate with hot and cold cluster breakdown (). 1 9 8 7 6 5 4 3 2 1 1 2 3 4 5 6 7 8 9 1 % P D -L 1 T C ( IH C ) r =.5225 p =.5 PD-L1+ (EpCM) 8 ** 6 4 2 h o t c o ld
% P D -1 + % P D -1 + Supplementary Figure 4. Strong correlation between %PD-1 and %TIM-3 expression by both CD8 + T cells () and CD4 + T cells (). 1 CD8 8 6 r =.7969 p <.1 4 2 1 8 6 2 4 6 8 % T IM -3 CD4 r =.5695 p <.1 4 2 1 2 3 4 % T IM -3
n u m b e r o f m u ta tio n s Supplementary Figure 5. Number of mutations detected by OncoPanel sequencing highly correlates with patient reported smoking status in pack-years. 4 3 2 r =.5297 p =.9 1 2 4 6 8 1 p a c k -y e a rs
Supplementary Figure 6. Significantly differentially regulated genes by Nanostring in hot versus cold immnuophenotypic clusters. Log2 fold change Lower confidenc e limit Upper confidenc e limit P-value FDR Gene.sets D 2.8 1.48 2.69 2.93E-7.214 -Cell Functions, T-Cell Functions C4P -4.45-6.14-2.76 2.4E-5.538 Complement GZM 1.57.959 2.17 2.57E-5.538 Cell Functions, Cytotoxicity FOS -2.38-3.31-1.45 2.95E-5.538 TNFSF4 1.41.845 1.97 3.81E-5.556 Chemokines, TNF Superfamily TOLLIP -.569 -.87 -.331 7.1E-5.78 C8-1.74-2.47-1.1 7.49E-5.78 Complement CXCL1 2.46 1.42 3.5 8.48E-5.78 Chemokines, Cytokines, Pathogen Defense, Regulation, T-Cell Functions CDK1 1.63.934 2.32 8.73E-5.78 CXCL9 2.49 1.41 3.57.18.785 Chemokines, Regulation, T-Cell Functions VEGFC 1.54.855 2.23.153.977 CREP -.859-1.24 -.475.161.977 CXCL13 2.72 1.48 3.97.213.115 Chemokines ITG5 1.7.915 2.48.228.115 dhesion CTSH -1.71-2.5 -.915.247.115 IRC5 1.51.85 2.21.261.115 Cell Cycle FOXJ1-3.43-5.5-1.82.282.115 STT1 1.36.723 2.1.284.115 Chemokines, Regulation CCL17-2.37-3.5-1.24.318.122 Chemokines EGR1-1.87-2.78 -.951.444.156 Senescence, T-Cell Functions TNFSF15-1.48-2.2 -.753.45.156 Chemokines, TNF Superfamily PL2G1-3.13-4.68-1.58.482.16 Regulation PRKCE -.759-1.14 -.381.519.165 Macrophage Functions IL6R -1.11-1.66 -.553.55.167 Cytokines VCM1 2.5.999 3.1.75.26 dhesion, Regulation TTK 1.37.656 2.8.828.232 SIGIRR -.984-1.5 -.464.951.257 CD1C -1.55-2.38 -.723.14.271 T-Cell Functions CCL8 1.51.72 2.32.18.272 Chemokines, Regulation PK 1.32.611 2.4.113.276 ICM4-2.71-4.18-1.25.118.279 dhesion, Regulation STT6-1.7-1.65 -.488.125.28 Chemokines, Regulation, T-Cell Functions CCND3-1.3-2.1 -.593.127.28 Cell Cycle C6-2 -3.9 -.899.137.281 Complement NUP17.621.279.962.138.281 Cell Cycle RORC -2.32-3.6-1.5.138.281 Cell Functions FCER1-1.98-3.8 -.884.149.294 IL18 1.2.451 1.59.157.31 Interleukins, T-Cell Functions PRG2-1.16-1.82 -.497.196.367 Pathogen Defense FCGR3 1.27.538 2.1.213.389 Regulation CCL23-1.4-2.21 -.584.231.41 Chemokines, Regulation COL31 3.23 1.34 5.12.236.41 Regulation RRD -2-3.17 -.82.255.433 Cell Functions REPS1.567.23.94.275.456 Cell Functions
T L TLS S s score c o re TLS score C D 1 9 e x p r e s s io n ( n a n o s t r in g ) S P s c o r e ( IH C ) SP CD3 medium large medium large large small small large Supplementary Figure 7. TLS size was accessed for quantification (). Percent of CD19 + cells defined by flow correlates with the Nanostring counts for CD19 gene expression () and cell count by IHC (C). TLS score highly correlates with abundance of cells quantified by flow (D) but not with hot or cold immunophenotype (E). Scale bars measuring TLS size to the tenth of a μm are overlayed onto image. 1 8 C 6 r =.6612 p =.8 6 4 4 2 r =.6598 P<.1 2 1 2 3 4 C D 1 9 + c e lls in t o t a l liv e (f lo w ) 5 1 1 5 2 C D 1 9 + c e lls in t o t a l liv e (f lo w ) D 6 r =.5689 p =.57 E 6 4 4 2 2 5 1 1 5 2 % C %CD19+ D 1 9 + ccells e lls (of(liv live e cells) c e lls ) hot cold
Supplementary Figure 8. No significant differences between Ig light chains between tumor cells and normal lung cells or between IL-1 + cells and IL-1 - cells. bsolute counts Relative contribution
Supplementary Figure 9. Immune parameters used for clustering in Figure 4. immune parameter 1 %EpCM+ cells (live cells) 2 %CD45+ cells (live cells) 3 %CD3+ T cells (CD45+) 4 %CD19+ T cells (CD45+) 5 %CD56+ NK cells (CD45+) 6 %CD33+ monocytes (CD45+) 7 %CD66b+ granulocytes (CD45+) 8 %CD16+ NK cells 9 %CD8+ T cells (CD3+) 1 CD8/CD4 T cell ratio 11 %TIM-3+ (CD4+ T cells) 12 %PD-1+ (CD4+ T cells) 13 %TIM-3+ (CD8+ T cells) 14 %PD-1+ (CD8+ T cells) 15 %CD4+ T cells (CD3+)