Dornieden et al. Supplemental Material

(1)

1

Dornieden et al. Supplemental Material

Table of Contents

Content Page

Supplemental Table 1. Antibodies for phenotypic analysis. 2

Supplemental Table 2. Multimers. 3

Supplemental Table 3. Antibodies for phenotypic analysis of antigen-specific CD8⁺T cells.

3

Supplemental Table 4. Antibodies for functional analysis. 4

Supplemental Table 5. Antibodies for MELC histology. 5

Supplemental Table 6. Used statistics. 6

Supplemental Figure 1 (A+B) 7

Supplemental Figure 2 8

Supplemental Figure 3 (A-C) 9

Supplemental Figure 5 (A+B) 11

Supplemental Figure 8 (A-D) 14

(2)

Molecule Clone Fluorochrome Manufacturer Catalog Number

Panel CD3 SK7 PerCP/Cy5.5 Biolegend, San Diego, USA 344808 1, 2, 3, 4,

5

CD4 SK3 BUV395 BD, Heidelberg, Germany 563550 1, 2, 3,4 ,

5 CD8 SK1 APCeFluor780 Thermo Fisher, Darmstadt,

Germany

47-0087-42 1, 2, 3, 4, 5

CD14 63D3 BV510 Biolegend, San Diego, USA 367123 1, 2, 3, 4,

5

CD19 SJ25C1 BV510 Biolegend, San Diego, USA 363019 1, 2, 3, 4, 5

CD25 BC96 PE/Cy7 Biolegend, San Diego, USA 302612 3

CD28 CD28.2 BV711 Biolegend, San Diego, USA 302947 1

CD38 HIT2 BV605 Biolegend, San Diego, USA 303532 2

CD45RA HI100 BV650 Biolegend, San Diego, USA 304135 1, 3 CD45RO UCHL1 BV650 Biolegend, San Diego, USA 304231 2, 5 CD49a TS2/7 PE/Cy7 Biolegend, San Diego, USA 328311 1, 5

CD56 5.1H11 BV785 Biolegend, San Diego, USA 328311 1, 2, 4

CD62L DREG-56 BV605 BD, Heidelberg, Germany 562719 1, 3

CD69 FN50 Alexa700 Biolegend, San Diego, USA 310922 1, 2

CD69 FN50 BV711 Biolegend, San Diego, USA 310943 3

CD69 FN50 FITC Biolegend, San Diego, USA 310903 4, 5

CD103 Ber-ACT8 BV785 Biolegend, San Diego, USA 350229 5 CD103 Ber-ACT8 PE Biolegend, San Diego, USA 350206 1, 2, 3, 4 CD161 HP-3G10 PE/Dazzle594 Biolegend, San Diego, USA 339940 2, 3, 5 CTLA4 BNI3 BV421 Biolegend, San Diego, USA 369605 3 FoxP3 150D Alexa647 Biolegend, San Diego, USA 320014 3 HLA-DR L243 FITC Biolegend, San Diego, USA 307604 3 HLA-DR L243 PE/Cy7 Biolegend, San Diego, USA 307615 2

Ki67 B56 Alexa700 BD, Heidelberg, Germany 561277 3, 5

L/D - Aqua (BV510) Biolegend, San Diego, USA 423101 1, 2, 3, 4, 5

NKG2D 1D11 BV421 Biolegend, San Diego, USA 320822 1, 2

PD1 EH12.1 BV711 BD, Heidelberg, Germany 564017 2

Tox REA473 APC Miltenyi, Bergisch Gladbach, Germany

130-118-474 4 Vα7.2 3C10 APC Biolegend, San Diego, USA 351708 1, 2 Vα7.2 3C10 BV711 Biolegend, San Diego, USA 351731 5

Supplemental Table 1.Antibodies for phenotypic analysis.

2

(3)

Supplemental Table 2.Multimers.

Supplemental Table 3.Antibodies for phenotypic analysis of antigen-specific CD8⁺T cells.

3

Virus Allele Peptide Antigen Catalog Number

CMV HLA-A*0201 NLVPMVATV pp65 WB2132-PE

Influenza HLA-A*0201 GILGFVFFL MP WB2161-PE

BKV HLA-A*0201 LLMWEAVTV VP1 WB2687-PE

EBV HLA-A*0201 GLCTLVAML BMLF1 WB2130-PE

Molecule Clone Fluorochrome Manufacturer Catalog Number

CD3 SK7 PerCP/Cy5.5 Biolegend, San Diego, USA 344808

CD4 SK3 BUV395 BD, Heidelberg, Germany 563550

CD8 SK1 APCeFluor780 Thermo Fisher, Darmstadt, Germany

47-0087-42

CD14 63D3 BV510 Biolegend, San Diego, USA 367123

CD19 SJ25C1 BV510 Biolegend, San Diego, USA 363019

CD45RA HI100 BV650 Biolegend, San Diego, USA 304135 CD62L DREG-56 BV605 BD, Heidelberg, Germany 562719

CD69 FN50 Alexa700 Biolegend, San Diego, USA 310922

CD103 Ber-ACT8 BV785 Biolegend, San Diego, USA 350229 CTLA4 BNI3 BV421 Biolegend, San Diego, USA 369605 HLA-A2 BB7.2 APCCy7 Biolegend, San Diego, USA 343310 HLA-DR L243 PE/Cy7 Biolegend, San Diego, USA 307615

L/D - Aqua (BV510) Biolegend, San Diego, USA 423101

PD1 EH12.1 BV711 BD, Heidelberg, Germany 564017

(4)

Molecule Clone Fluorochrome Manufacturer Catalog Number

CD3 SK7 PerCP/Cy5.5 Biolegend, San Diego, USA 344808

CD4 SK3 BUV395 BD, Heidelberg, Germany 563550

CD8 SK1 APCeFluor780 Thermo Fisher, Darmstadt, Germany

47-0087-42

CD14 63D3 BV510 Biolegend, San Diego, USA 367123

CD19 SJ25C1 BV510 Biolegend, San Diego, USA 363019

CD45RO UCHL1 BV650 Biolegend, San Diego, USA 304231 CD49a TS2/7 PE/Cy7 Biolegend, San Diego, USA 328311

CD69 FN50 BV711 Biolegend, San Diego, USA 310943

CD103 Ber-ACT8 PE Biolegend, San Diego, USA 350206 CD161 HP-3G10 PE/Dazzle594 Biolegend, San Diego, USA 339940 GranzymeB GB11 FITC Biolegend, San Diego, USA 515403 IFN-γ 4S.B3 eFluor450 Thermo Fisher, Darmstadt,

Germany

48-7319-42

IL-2 MQ1-17H12 BV605 Biolegend, San Diego, USA 500332 IL-17 BL168 BV785 Biolegend, San Diego, USA 512338

L/D - Aqua (BV510) Biolegend, San Diego, USA 423101

TNFα MAb11 Alexa700 Biolegend, San Diego, USA 502928

Vα7.2 3C10 APC Biolegend, San Diego, USA 351708

Supplemental Table 4. Antibodies for functional analysis.

4

(5)

Molecule Clone Fluoro- chrome

Manufacturer Catalog Number AQP2 (E-2) PE Santa Cruz Biotechnology, Dallas, USA sc-515770PE CD3 REA613 PE Miltenyi, Bergisch Gladbach, Germany 130-113-139 CD4 VIT4 PE Miltenyi, Bergisch Gladbach, Germany 130-113-776 CD8 BW135/80 PE Miltenyi, Bergisch Gladbach, Germany 130-113-720 CD11c MJ4-27G12 PE Miltenyi, Bergisch Gladbach, Germany 130-114-106 CD14 Tük4 PE Miltenyi, Bergisch Gladbach, Germany 130-113-709 CD16 REA423 PE Miltenyi, Bergisch Gladbach, Germany 130-113-955

CD31 9G11 PE R&D Systems, Minneapolis, USA FAB3567P

CD45RA REA562 PE Miltenyi, Bergisch Gladbach, Germany 130-098-184 CD45RO UCHL1 PE DRFZ, Berlin, Germany

CD49a TS2/7 PE Biolegend, San Diego, USA 328303

CD56 AF12-7H3 PE Miltenyi, Bergisch Gladbach, Germany 130-098-137 CD69 REA824 PE Miltenyi, Bergisch Gladbach, Germany 130-112-613 CD103 Ber-ACT8 PE Miltenyi, Bergisch Gladbach, Germany 130-103-709 CD161 191B8 PE Miltenyi, Bergisch Gladbach, Germany 130-114-119

CD163 RM3/1 PE Biolegend, San Diego, USA 326505

DAPI Thermo Fisher, Darmstadt, Germany D1306

HLA-DR REA332 PE Miltenyi, Bergisch Gladbach, Germany 130-120-784

Ki67 MIB1 FITC Dako, Glostrup, Denmark F7268

TCRVα7.2 3C10 PE Biolegend, San Diego, USA 351705

Supplemental Table 5. Antibodies for MELC histology.

5

(6)

Supplemental Table 6. Used statistics.

6

Figure Statistic test

1 B-D two-tailed paired T test / Wilcoxon Signed Ranks test 2 B two-tailed Wilcoxon Signed Ranks test

3 B-C One-way ANOVA(with multiple comparison corrected by the Tukey’s method) / Friedman test (with multiple comparison corrected by the Dunn’s method) 3 D Spearman’s rank-order coefficients

3 E Ordinary One-way ANOVA (with multiple comparison corrected by the Tukey’s method) /

Kruskal-Wallis test (with multiple comparison corrected by the Dunn’s method) Spearman’s rank-order coefficients

4 A two-tailed Wilcoxon Signed Ranks test

5B, F two-tailed paired T test / Wilcoxon Signed Ranks test 6 A, B, D two-tailed paired T test / Wilcoxon Signed Ranks test 7 B, C two-tailed paired T test / Wilcoxon Signed Ranks test 7 D two-tailed unpaired T test / Mann-Whitney test

8 B Kruskal-Wallis test (with multiple comparison corrected by the Dunn’s method) 8 C-D One-way ANOVA(with multiple comparison corrected by the Tukey’s method)

Friedman test (with multiple comparison corrected by the Dunn’s method) Suppl. 3 A, B two-tailed paired T test / Wilcoxon Signed Ranks test

Suppl. 5 A, B two-tailed paired T test / Wilcoxon Signed Ranks test Suppl. 6 B two-tailed paired T test / Wilcoxon Signed Ranks test Suppl. 7 A, B, C two-tailed paired T test / Wilcoxon Signed Ranks test Suppl. 8A two-tailed unpaired T test / Mann-Whitney test Suppl. 8 B, C, D Spearman’s rank-order coefficients

Suppl. 14 two-tailed paired T test

(7)

Supplemental Figure 1

A.

CD8

CD4

SSC-A

CD69

0 0 0 0

38.3 61.7 59.5 40.5

direct CD69 surface staining

CD69 staining before and analysis after 6h stimulation

0 0

38.4 61.6

0 0

56.5 43.5

CD4⁺ CD8⁺

B.

Supplemental Figure 1: (A) Gating Strategy. Cells were detected by after gating on single, live CD14^-CD19^- (“DUMP” negative) lymphocytes. Conventional CD4⁺ and CD8⁺ T cells and CD8⁺/CD8^-CD4^-(“DN”) CD161⁺Vα7.2⁺ MAIT cells were identified within the CD3⁺ population.

CD56 dim or bright NK cells were identified within the CD3^- subset. Tissue resident cells were subsequently detected by single- or co-expression of CD69 and CD103, respectively. Exemplary dot plots for intracellular markers (CTLA4, Ki67) and cytokines (granzyme B (GrB), IFNγ, IL-2, IL-17, TNFα) (B) Ex vivo staining of CD69 prior to stimulation. PBMCs were stained with anti-CD69 before culture, thereby preventing its stimulus-dependent increase by PMA/Ionomycin. Plots demonstrate stable staining after 6h activation as compared to theex vivocontrol. ₇

CD8

DUMP

SSC-A

FSC-A

FSC-H

FSC-W CD3 CD4

SSC-A

CD56

Tissue resident cells

NK cells dim bright

CD8⁺

CD4⁺ DN

CD3⁺ CD3^-

Lymphocytes

Single Cells

CD8⁺DN MAIT

Vα7.2

CD161

CD103

CD69

DP

SSC-A

GrB IFNγ IL2 IL17 TNFα

unstimulated

stimulated

CTLA4

Ki67

(8)

peri-tumor

tumor

Supplemental Figure 2:Panel overview of a 19 marker MELC run in human kidneys show different degree of T cell infiltration. 2 exemplary different data-sets are shown: 1 peri- tumor samples (A) and 1 tumor samples (B). Each image shows the same field of view, sequentially stained with the depicted fluorescence-labelled antibodies. Images contain 2024 x 2024 pixels and are generated using an inverted wide-field fluorescence microscope with a 20x objective, a lateral resolution of 325 nm and an axial resolution above 5 µm.

Scale bar: 100 µm. ⁸

(9)

Supplemental Figure 3: (A) Quantification of PBMC- and tissue-derived T cell subsets.

Frequencies of CD8⁺CD4^-, CD8⁺CD4⁺, CD8^-CD4⁺and CD8^-CD4^- T cells within the CD3⁺ cell population isolated from paired blood and peri-tumor kidney samples (n=29) were analyzed by FACS. (B) Ex vivo proliferation of CD8⁺ and CD4⁺ T cells.Proliferation as reflected by Ki67 expression of CD8⁺ (n=8) and CD4⁺ (n=9) T cells derived from paired blood and peri-tumor kidney samples. Statistically significant differences were tested with two-tailed paired T or two- tailed Wilcoxon Signed Ranks test and presented as mean values ± SD. (C) Exemplary dot plots for blood and peri-tumor kidney-derived CD8⁺ and CD4⁺ T cell subsets according to their CD62L and CD45RA expression.

A.

0 20 40 60 80

CD8⁺CD4^- p=0.0047

% of CD3+

0 5 10 15 20

kidney blood p<0.0001

CD8⁺CD4⁺ ⁰ 20 40 60 80 100

CD8^-CD4⁺ p=0.0037

0 10 20 30 40 50

CD8^-CD4^-

B.

0 1 2 3 4

Ki67⁺

% of CD3+CD8+

Ki67⁺ 0

2 4 6

% of CD3+CD4+ kidney

blood

n.s.

n.s. n.s.

blood kidney

CD45RA

CD62L blood

kidney

CD8⁺ CD4⁺

18.7 5.88

59.5 3.45

22.1 37.8

13.8 10.7

2.73 12.8

38.7 17.1

0.11 42.7

6.08 28.0

C.

9

(10)

tSNE2

tSNE1 CD8⁺

kidney blood

tSNE2

tSNE1 CD4⁺

tSNE2

tSNE1 CD8⁺

kidney blood

tSNE2

tSNE1 CD4⁺

tSNE2

tSNE1 CD8⁺

tSNE2

tSNE1 CD4⁺ kidney blood

CD45RA^-CD62L^-69^-103⁺28^-49a⁺Va7.2^intNKG2D⁺ CD45RA^-CD62L^-69⁺103⁺28^-49a⁺Va7.2^-NKG2D^-

CD45RA⁺CD62L⁺69⁺103⁺28⁺49a⁺Va7.2^-NKG2D^- CD45RA^-CD62L^-69^-103^-28^-49a^-Va7.2^-NKG2D^-

CD45RA⁺CD62L^-69⁺103^-28^int49a⁺Va7.2^-NKG2D^-

CD45RA^-CD62L^-69^-103⁺28^-49a⁺Va7.2întNKG2Dînt CD45RA^-CD62L^-69înt103^-28^-49a^-Va7.2^-NKG2D^- CD45RA^-CD62L^-69^-103^-28^-49a^-Va7.2^-NKG2D^-

HLA-DR^-CD45RO^-69^-103^-PD1^-161^-Va7.2^-NKG2D^- HLA-DR⁺CD45RO⁺69^-103⁺PD1^int161⁺Va7.2⁺NKG2D⁺ HLA-DR⁺CD45RO⁺69⁺103⁺PD1⁺161^-Va7.2^-NKG2D^int

HLA-DR⁺CD45RO⁺69⁺103^-PD1⁺161^intVa7.2^intNKG2D⁺ HLA-DR⁺CD45RO⁺69⁺103⁺PD1⁺161^-Va7.2^-NKG2D⁺ HLA-DR^-CD45RO^-69^-103^-PD1^-161^-Va7.2^-NKG2D^-

CD45RA^-CD62L^-69⁺103^-HLA-DR⁺CTLA-4^- 161^-FoxP3^-Ki67^intCD25^-

CD45RA^-CD62L^-69^-103^-HLA-DR^-CTLA-4^- 161^-FoxP3^-Ki67^-CD25^-

CD45RA^-CD62L^-69⁺103^-HLA-DR⁺CTLA-4^- 161⁺FoxP3^-Ki67⁺CD25^-

CD45RA^-CD62L^-69⁺103^-HLA-DR⁺CTLA-4^- 161^-FoxP3întKi67întCD25înt

CD45RA^-CD62L^-69⁺103⁺HLA-DR⁺CTLA-4^- 161^-FoxP3^intKi67⁺CD25^int

CD45RA^-CD62L^-69⁺103^-HLA-DR^-CTLA-4^- 161^-FoxP3^-Ki67^-CD25^-

Supplemental Figure 4: viSNE and FlowSOM analysis of FACS data. viSNE plots of flow cytometric analysis of viable CD8⁺ and CD4⁺ T cells illustrate the separate clustering of kidney and blood. FlowSOM analysis clusters cells into cell subsets based on their marker expression patterns used in the corresponding FACS panels. Only metaclusters identified in kidney but not present in blood are annotated. Markers used for dimensional reduction were identical to those in Figure 1A for the respective panels. [Panel 1: CD103, CD28, CD45RA, CD49a, CD62L, CD69, NKG2D, Va7.2 HLA-DR/PD-1; Panel 2: CD103, CD161, CD45RO, CD69, HLA-DR, NKG2D, PD1, Va7.2; Panel 3: CD103, CD161, CD25, CD45RA, CD62L, CD69, CTLA-4, FoxP3, HLA- DR, Ki67].

10

Panel 1Panel 2Panel 3

(11)

11

A.

% of CD3+CD8+

0 20 40 60 80

100 p<0.0001

CD49a⁺ p<0.0001

% of CD3+CD4+

CD49a⁺ 0

20 40 60

SSC-A

CD49a CD8⁺

CD4⁺

0 0

63.5 36.5

0 0

88.4 11.6

0 0

79.8 20.2

0 0

87.4 12.6

kidney blood

B.

p=0.0001 p=0.0038 p=0.0011 p=0.0004 p=0.0096 CD49a⁺

CD49a^-

0 20 40 60 80

GrB⁺ IFNγ⁺ IL2⁺ IL17⁺ TNFα⁺

n.s. n.s.

% of CD3+CD8+

n.s.

0 20 40 60 80

GrB⁺ IFNγ⁺ IL2⁺ IL17⁺ TNFα⁺

% of CD3+CD4+

p=0.0102 p=0.0002

Supplemental Figure 5:(A,B) CD49a expression and related cytokine profiles. Exemplary dot plots showing frequencies of CD49a expressing CD8⁺and CD4⁺T cells in peri-tumor tissue and blood (n=17) (A) and the associated effector molecule profile (Granzyme B, IFNγ, IL-2, IL-17, TNFα) within kidney (n=17) (B). Statistically significant differences were tested with two-tailed paired T or two-tailed Wilcoxon Signed Ranks test and presented as mean values ± SD.

(12)

B.

A.

CD103

KLRG1 blood kidney

CD8⁺ CD4⁺

5.52 3.03

15.6 75.8

0.68 0.37

12.3 86.8

0.65 0.31

49.5 49.6

0.81 0.059

76.7 23.6

0 10 20 30 40 50

KLRG1^-CD103⁺ p=0.0058

% of CD3+CD8+

0 5 10 15

20 p=0.0289

KLRG1⁺CD103⁺

0 20 40 60 80

100 p=0.0091

KLRG1⁺CD103^-

kidney blood

0 1 2 3

4 p=0.0409

% of CD3+CD4+

0.0 0.5 1.0

1.5 p=0.0078

0 20 40

60 p=0.0078

Supplemental Figure 6: (A,B) KLRG1 and CD103 expression of CD8⁺ and CD4⁺ T cells.

Exemplary dot plots and frequencies for blood and peri-tumor kidney tissue derived CD8⁺and CD4⁺ T cell subsets according to their KLRG1 and CD103 expression (n=8). Statistical analysis was performed using two-tailed paired T or two-tailed Wilcoxon Signed Ranks test.

(C) Exemplary dot plots for blood and peri-tumor kidney-derived CD8⁺ and CD4⁺ T cell subsets expressing CD103 and CD69.

12 blood

kidney

CD103

CD69 blood kidney

CD8⁺ CD4⁺

5.78 27.4

29.0 37.8

0.38 0.016

93.3 6.34

1.09 4.81

34.3 59.8

1.79 0.10

93.4 4.74

C.

(13)

Supplemental Figure 7: (A) Ex vivo proliferation of CD8⁺ and CD4⁺ T_RM cell subsets.

Proliferation status as reflected by Ki67 expression of CD8⁺ and CD4⁺ CD69⁺CD103⁺ and CD69⁺CD103^-T cells derived from renal peri-tumor tissue (n=8) was analyzed by FACS.

Statistical analysis was performed using two-tailed paired T or two-tailed Wilcoxon Signed Ranks test. (B) Memory subsets within CD8⁺ and CD4⁺ T_RM T cell subsets. Frequencies of CD45RA^-CD62L⁺ central memory (T_CM), CD45RA⁺CD62L^- terminally differentiated effector (T_EMRA), CD45RA^-CD62L^- effector memory (T_EM) and CD45RA⁺CD62L⁺ naïve cells within CD8⁺ and CD4⁺ T_RM peri-tumor kidney T cell subsets CD69⁺CD103⁺ and CD69⁺CD103^- (n=16). Statistically significant differences were tested with two-tailed paired T or two-tailed Wilcoxon Signed Ranks test. (C) CD49a expression on renal-derived CD69⁺CD103⁺ and CD69⁺CD103^- CD8⁺ T cells (n=19). Statistically significant differences were tested with the Wilcoxon Signed Ranks test and presented as mean values ± SD.

0 2 4 6 8 10

Ki67⁺ p=0.0015

% of CD3+CD4+

0 1 2 3 4 5

Ki67⁺

% of CD3+CD8+

A.

CD69⁺CD103⁺ CD69⁺CD103^- n.s.

13

% of CD3+CD8+

p<0.0001 p=0.0063 p=0.0027

% of CD3+CD4+

B.

0 20 40 60 80

0 20 40 60 80 100

0 5 10

0 5 10 15 20

0 10 20 30

0 50 100 150

0 1 2 3 4 5

CD69⁺CD103⁺ CD69⁺CD103^- n.s.

n.s. n.s. n.s. n.s.

0 20 40 60 80 100

CD45RA^- CD62L⁺

CD45RA⁺ CD62L^-

CD45RA^- CD62L^-

CD45RA⁺ CD62L⁺

0 50 100

p<0.0001

% of CD3+CD8+

C.

CD49a⁺

CD69⁺CD103⁺ CD69⁺CD103^-

(14)

B.

C.

40 60 80

40 60 80 100 120

% ofCD3+CD8+CD69+CD103+ CD28-

p=0.3406

age in years R²=0.07002

40 60 80

0 50 100 150

% ofCD3+CD8+CD69+CD103- CD28-

p=0.6372 R²=0.01763

age in years

40 60 80

0 20 40 60

80 p=0.1800

R²=0.09254

% of CD3+CD8+DN MAIT CD69+CD103+ % ofCD3+CD56+dim CD69+CD103+

40 60 80

0 5 10 15

20 p=0.3194

R²=0.08997

% ofCD3+CD56+bright CD69+CD103+

40 60 80

0 10 20 30

40 p=0.3723

R²=0.2723

age in years age in years

D.

Supplemental Figure 8. (A) Patients were divided into two groups according to the calculated mean age of 63 years (n=35). Group I included patients ≤ 63 years (n=13), whereas Group II included patients > 63 years (n=22). CD69⁺CD103⁺ and CD69⁺CD103^- CD8⁺ and CD4⁺ T cell frequencies in peri-tumor tissue were compared between the two groups. Statistically significant differences were tested with two-tailed unpaired T or the Mann-Whitney test and presented as mean values ± SD. (B-D) Correlation of T_RM cell subsets and age. Correlation analysis of (A) CD4⁺CD69⁺CD103⁺ T cells (n=35), (B) CD8⁺CD69⁺CD103⁺CD28^- and CD8⁺CD69⁺CD103^-CD28^- (n=18), and (C) CD69⁺CD103⁺ TCRVα7.2⁺CD161⁺ MAIT (n=27), CD56^dim and CD56^bright NK cells (n=18) frequencies with patient age. Linear regression analysis was performed and Spearman’s rank-order coefficients were calculated.

% ofCD3+CD4+CD69+CD103+

p=0.9697 R²=0.000064

age in years

40 60 80

0 2 4 6 8 10

14 p=0.0456

CD69⁺CD103⁺

% of CD3+CD8+

CD69⁺CD103^- p=0.0135

% of CD3+CD4+

CD69⁺CD103⁺ CD69⁺CD103^- 0

20 40 60

0 20 40 60 80

0 2 4 6 8 10

0 20 40 60

n.s. 80 n.s.

≤ 63 years

> 63 years

A.

(15)

15

Supplementary Figure 9.Cluster analysis of MELC data from pooled tumor and patient-matched peri-tumor samples (n=4). (A) t-SNE maps showing the analysis of 16 measured markers allowing the identification of the following clusters: vessels, activated monocytes/macrophages, CD69⁺CD103⁺ tissue-resident cells, CD69⁺CD103^-CD8⁺ T_RM cells, and CD69⁺CD103^-CD4⁺ T_RM cells in a color-coded fashion and, (B) a color-code for the individual samples measured, allowing the relation of the cluster to the sample origin.

A.

B.

(16)

16

Supplementary Figure 10. Both, CD69⁺CD103^- CD4⁺ and CD69⁺CD103^- CD8⁺ T cells form clusters, while and CD69⁺CD103⁺ tissue-resident (TR) populations tend to be rather scattered across the tumor tissue. Especially CD69⁺CD103^- CD4⁺ T cells could be identified in close proximity to monocyte/macrophages.Exemplary overlays of MELC fluorescent images depicting endothelial cells (CD31 in white, left panel) and monocyte/macrophages (CD14 in cyan, CD16 in magenta and CD163 in yellow, right panel) together with color-coded dots that represent the centroid spatial coordinates of the three tissue-resident cells clusters identified in (Fig. 6A). The images depict the spatial distribution of the CD69⁺CD103^-CD4⁺T cell cluster (light blue dots), the CD69⁺CD103^-CD8⁺ T cell cluster (purple dots) and the CD69⁺CD103⁺TR cluster (red dots) in each tumor sample and the patient-matched peri-tumor sample analyzed. Figures are representative for n=4 peri-tumor/tumor matched patient samples.

(17)

17

Supplementary Figure 11.Overlays of MELC fluorescent images depicting endothelial cells (CD31 in white, left panel) and monocyte/macrophages (CD14 in cyan, CD16 in magenta and CD163 in yellow, right panel) together with color-coded dots that represent the centroid spatial coordinates of the three tissue-resident cells clusters identified in (Fig. 5A) for n=3 peri-tumor/tumor matched patient samples.

(18)

18 tumor

peri-tumor

CD103

CD69 tumor peri-tumor

CD56^+dim CD56^+bright

Supplemental Figure 12: Tissue-residency of NK cells in peri-tumor and tumor kidney tissue. Exemplary dot plots of CD69 and CD103 expression of CD56^+dimand CD56^+bright cells isolated from peri-tumor and tumor tissue.

(19)

19 peri-tumor

tumor

tSNE2

tSNE1 CD8⁺

tSNE2

tSNE1 CD4⁺

HLA-DR^-CD45RO^-69^-103^-PD1^-161^-Va7.2^-NKG2D^- HLA-DR^-CD45ROînt69^-103întPD1înt161⁺Va7.2^-NKG2D⁺ HLA-DR^-CD45RO⁺69înt103^-PD1înt161^-Va7.2⁺NKG2Dînt HLA-DR⁺CD45RO⁺69⁺103întPD1⁺161⁺Va7.2⁺NKG2D⁺ HLA-DRîntCD45RO⁺69⁺103⁺PD1⁺161⁺Va7.2întNKG2D⁺ HLA-DR^-CD45ROînt69^-103^-PD1^-161^-Va7.2întNKG2Dînt HLA-DRîntCD45RO⁺69înt103^-PD1⁺161^-Va7.2⁺NKG2D⁺ HLA-DR⁺CD45RO⁺69⁺103⁺PD1⁺161⁺Va7.2întNKG2D⁺ HLA-DRîntCD45RO^-69înt103întPD1^-161⁺Va7.2întNKG2D^- HLA-DR^-CD45RO⁺69^-103^-PD1^-161^-Va7.2^-NKG2Dînt HLA-DR⁺CD45RO⁺69⁺103^-PD1⁺161^-Va7.2întNKG2D⁺ HLA-DR^-CD45RO^-69^-103^-PD1înt161^-Va7.2^-NKG2D^- HLA-DR^-CD45ROînt69^-103⁺PD1înt161întVa7.2^-NKG2D^- HLA-DRîntCD45RO^-69⁺103^-PD1^-161^-Va7.2⁺NKG2Dînt HLA-DR^-CD45RO^-69^-103^-PD1^-161^-Va7.2^-NKG2D^-

peri-tumor tumor

Supplemental Figure 13: viSNE and FlowSOM analysis of FACS data for peri-tumor and tumor samples. viSNE plots of flow cytometric analysis of viable CD8⁺ and CD4⁺ T cells does not illustrate a separate clustering between peri-tumor and tumor. Main cell clusters identified by FlowSOM analysis are annotated. The markerset from Panel 2 used for dimensional reduction was identical to that in Figure 1A (CD103, CD161, CD45RO, CD56, CD69, HLA-DR, NKG2D, PD-1, Va7.2).

Panel 2

(20)

Supplemental Figure 14: CD49a expression of CD8⁺ T_RM T cell subsets. Frequencies of CD49a expression of CD8⁺ CD69⁺CD103⁺ and CD69⁺CD103^- T_RM T cells isolated from peri-tumor and tumor tissue (n=11). Statistical analysis was performed using two-tailed paired T test.

0 50 100

% of CD3+CD8+ CD69+CD103+

CD49a⁺ n.s.

0 50 100

% of CD3+CD8+ CD69+CD103-

CD49a⁺ n.s.

peri-tumor tumor

20