# XCR1+ and IRF4+ migratory dendritic cells cooperate for the cross-priming of intratumoral CD8+ T cells with a tissue-resident memory phenotype

Nathan Vaudiau, Pierre Bourdely, Agathe Ok, Maria Semitekolou, Louise Gorline, Roberto Savoldelli, Yohan Gerber-Ferder, Fillipe Luiz Rosa Do Carmo, Aurélie Semervil, Mathias Vétillard, et al.

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Nathan Vaudiau, Pierre Bourdely, Agathe Ok, Maria Semitekolou, Louise Gorline, et al., XCR1+ and IRF4+ migratory dendritic cells cooperate for the cross-priming of intratumoral CD8+ T cells with a tissue-resident memory phenotype. 2025. hal-05406969

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Distributed under a Creative Commons Attribution 4.0 International License
# XCR1⁺ and IRF4⁺ migratory dendritic cells cooperate for the cross-priming of intratumoral CD8⁺ T cells with a tissue-resident memory phenotype.

**Nathan Vaudiau**

Institut Pasteur, "Dendritic cells and adaptive immunity" Unit, Immunology Department, Paris, France https://orcid.org/0000-0001-9586-8467

**Pierre Bourdely**

Université Paris Cité, INSERM UMR1149, CNRS EMR8252, Paris, France

**Agathe Ok**

Université Paris Cité, INSERM UMR1149, CNRS EMR8252, Paris, France

**Maria Semitekolou**

Institut Pasteur, "Dendritic cells and adaptive immunity" Unit, Immunology Department, Paris, France

**Louise Gorline**

Institut Pasteur, "Dendritic cells and adaptive immunity" Unit, Immunology Department, Paris, France

**Roberto Savoldelli**

Université Paris Cité, INSERM UMR1149, CNRS EMR8252, Paris, France

**Yohan Gerber-Ferder**

Université Paris Cité, Institut Cochin, INSERM U1016, CNRS UMR 8104, Paris, France

**Fillipe Luiz Rosa do Carmo**

Institut Pasteur, "Dendritic cells and adaptive immunity" Unit, Immunology Department, Paris, France

**Aurélie Semervil**

Institut Pasteur, "Dendritic cells and adaptive immunity" Unit, Immunology Department, Paris, France

**Mathias Vétillard**

Université Paris Cité, INSERM UMR1149, CNRS EMR8252, Paris, France

**Audrey Rood**

Université Paris Cité, INSERM UMR1149, CNRS EMR8252, Paris, France

**Syrine Bouallègue**

Institut Pasteur, "Dendritic cells and adaptive immunity" Unit, Immunology Department, Paris, France

**Konstantina Pamboukas**

Institut Pasteur, "Dendritic cells and adaptive immunity" Unit, Immunology Department, Paris, France

**Jérémie Borneres**

Institut Pasteur, "Dendritic cells and adaptive immunity" Unit, Immunology Department, Paris, France

**Guillaume Darasse-Jèze**

Immunology-Immunopathology-Immunotherapy (i3), UMRS 959, Sorbonne Université, INSERM, Paris, France

**Emmanuel L Gautier**

Sorbonne Université, INSERM UMR-S 1166, 75013 Paris, France

**Marc Dalod**

Aix-Marseille University, CNRS, INSERM, CIML, Centre d'Immunologie de Marseille-Luminy, Turing Center for Living Systems, Marseille, France.

**Eric Tartour**

Université de Paris Cité, PARCC, INSERM U970, 75006 Paris, France.

**Tessa Bergsbaken**

Center for Immunity and Inflammation, Department of Pathology, Immunology, and Laboratory Medicine, New Jersey Medical School, Rutgers-the State University of New Jersey, Newark, NJ, USA.

**Klaas P J M Van Gisbergen**

Champalimaud Research Program, Champalimaud Centre for the Unknown, Lisbon, Portugal

**Kairbaan Hodivala-Dilke**

Barts Cancer Institute, Queen Mary University of London, London, UK

**Loredana Saveanu**

Université Paris Cité, INSERM UMR1149, CNRS EMR8252, Paris, France

**Julie Helft**

Université Paris Cité, Institut Cochin, INSERM U1016, CNRS UMR 8104, Paris, France

**Federica Benvenuti**
Research Article

**Keywords:** CD8+ T lymphocytes, dendritic cells, tissue-resident memory T cells, lung cancer, priming, tumor-draining lymph-node, cross-presentation

**Posted Date:** April 16th, 2025

**DOI:** https://doi.org/10.21203/rs.3.rs-6455825/v1

**License:** © Ⓔ This work is licensed under a Creative Commons Attribution 4.0 International License. Read Full License

**Additional Declarations:** The authors declare no competing interests.
Abstract

The composition and diversity of tumor-infiltrating CD8⁺ T cell populations have important consequences on the development of anti-tumor immunity. In a murine model of lung cancer, we have addressed the role of dendritic cell subsets on the generation of various types of tumor-infiltrating CD8⁺ T cells. We show that CD44⁺PD1⁻ effector and PD1⁺TIM3⁺ exhausted, tumor-infiltrating CD8⁺ T cells require XCR1⁺ DCs but not IRF4-dependent DCs. By contrast, CD103⁺CXCR6⁺ T<sub>RM</sub>-like, tumor-infiltrating CD8⁺ T cells require both XCR1⁺ DCs and IRF4-dependent DCs. The same requirement is found in tumor-draining lymph nodes where we identify CD103⁺CXCR6⁺ T<sub>RM</sub>-like precursors that are dependent on both XCR1⁺ DCs and IRF4-dependent migratory DCs. Mechanistically, we evidence that both types of migratory DCs cooperate. Mild TCR triggering by low MHCI-peptide density at the surface of cross-presenting migratory DC2s and low IL-12 support TGFb-dependent T<sub>RM</sub> specification in lymph nodes. High TCR triggering and high MHCI-peptide density at the surface of cross-presenting migratory DC1s and high IL-12 support proliferative expansion and CXCR6 acquisition. Altogether, these findings highlight the induction of intratumoral T<sub>RM</sub>-like cells under the collective aegis of multiple DCs subsets within tumor-draining lymph nodes reconciliating T<sub>RM</sub> phenotype instruction with proliferative expansion.

MAIN

Tumor-infiltrating CD8⁺ T cells (TILs) are critical mediators of anti-tumor immunity. CD8⁺ TILs are characterized by the pervasive expression of exhaustion-associated features initially characterized in chronic infection models, including reduced proliferative response to TCR triggering and reduced polyfunctional cytokine responses. Multiple studies suggest that the qualitative composition of CD8⁺ TILs in solid tumors predicts clinical outcome and response to immunotherapies¹,². In that line, a subset of CD8⁺ TILs with a tissue-resident memory phenotype (T<sub>RM</sub>) has been identified in solid tumors including lung and breast cancer and correlates with improved prognosis and better response to immunotherapies¹,³⁻⁹.

Bona fide T<sub>RM</sub> have first been identified in peripheral tissues after clearance of viral infections¹⁰. Unlike other activated and memory CD8⁺ T cells, T<sub>RM</sub> do not recirculate but persist in tissues where they ensure immunosurveillance. T<sub>RM</sub> are characterized by a specific transcriptional program including the expression of transcription factors Hobit (encoded by *Zfp683*), Runx3 and Blimp-1<sup>4,11,12</sup>. T<sub>RM</sub> express αE integrin/CD103, which associates with integrin β7 to bind E-cadherin stabilizing contacts with epithelial cells, and low levels of S1P receptors ensuring tissue residency¹³. Also, T<sub>RM</sub> stably express the CD69 lectin mediating S1P desensitization, further contributing to tissue residency¹⁴.

Similar to bona fide anti-infectious T<sub>RM</sub>, T<sub>RM</sub>-like TILs harbor canonical features of residency including the concomitant expression of CD103, CD69, Hobit and reduced levels of S1PR1. A recent study in a murine model of E0771 murine breast tumors suggests that CD69<sup>+</sup>CD49a<sup>+</sup>P2Rx7<sup>+</sup> T<sub>RM</sub> phenotype within CD8<sup>+</sup> TILs may not indicate actual residency within tumors<sup>15</sup>. Still, several studies show that CD8<sup>+</sup> T<sub>RM</sub>-like TILs cells can display potent anti-tumor function<sup>16</sup> as they secrete cytokines, exhibit cytotoxic activity<sup>17</sup> and can potentially generate a large repertoire of T cell subsets upon antigenic restimulation<sup>18,19</sup> or after immune checkpoint blockade<sup>20</sup>. T<sub>RM</sub>-like TILs express some features of exhausted T cells but compared to T<sub>EX</sub>-like TILs, T<sub>RM</sub>-like TILs display enhanced cytotoxicity and provide local protection in a murine model of breast cancer<sup>20</sup>. Consistently, numerous studies have identified a strong correlation between CD8<sup>+</sup> TILs with a T<sub>RM</sub> phenotype and favourable outcomes and increased response rates to immune checkpoint inhibition in human lung cancer<sup>1,3,5-7,9</sup>, triple-negative breast cancer and other solid tumors<sup>16,21</sup>. This calls for a better understanding of the mechanisms ensuring the acquisition of the T<sub>RM</sub> program during T cell activation in solid tumors.

In cancer, CD8+ T cells are initially activated in tumor-draining lymph nodes (tdLN) and terminally differentiate within the tumor<sup>22,23</sup>. However, the anatomical location where T<sub>RM</sub>-like fate specification occurs in cancer is unclear (i.e., during priming in tdLN or after infiltration in the TME). In a mouse model of skin vaccination, TGF-β activated by steady-state migratory DCs imprint an epigenetic state rendering naïve T cells poised to differentiate into T<sub>RM</sub><sup>24</sup>. Other studies identify T<sub>RM</sub>-committed circulating progenitors during vaccination or viral infection, arguing in favor of early T<sub>RM</sub> fate decision<sup>25,26</sup>. Anti-infectious T<sub>RM</sub> can also be generated from circulating effector cells receiving T<sub>RM</sub> instruction after tissue infiltration<sup>4,27,28</sup>.

Dendritic cells (DCs) are the sentinel cells of the immune system ensuring T cell activation and differentiation. Classical DCs are diverse and composed of 2 main families expressing and relying on IRF8 or IRF4 transcription factors. There is wide evidence that IRF8+, BATF3-dependent XCR1+ DC1s control the activation of effector CD8+ T cell responses in the context of immunogenic tumors<sup>29-31</sup> and maintain the fitness of CD8+ T cell effector compartment by expanding TCF1+ T cells in tdLN<sup>32</sup>. Efficient phagocytosis of tumor-derived cell debris and efficient cross presentation of cell-associated antigens by MHCI<sup>33-35</sup> and MHCII presentation to helper T cells<sup>36</sup> all support the paramount importance of XCR1+ DC1s in shaping effector CD8+ T cell responses. By contrast, the nature of antigen presenting DC subtypes controlling T<sub>RM</sub> activation during T cell priming and infiltration is less clear and has mostly been investigated in the context of vaccination or infections. Skin XCR1+ Batf3-dependent DC1s are essential for the efficient activation of skin T<sub>RM</sub> after vaccination<sup>37</sup>. IRF4-dependent DC2s are essential for the priming of influenza-specific T<sub>RM</sub> in
lungs³⁸ and the maintenance of CXCR3⁺ T<sub>RM</sub> against HSV cervical infection²⁷. Also, human IRF4⁺ CD163⁺CD1c⁺ DCs are the most potent antigen-presenting cells for T<sub>RM</sub> specification *in vitro* or in humanized mice³⁹,⁴⁰.

Despite numerous evidence of a role for CD8⁺ T<sub>RM</sub>-like TILs in non-small cell lung cancer (NSCLC) immunosurveillance<sup>1,3,5-7,9,21</sup>, little is known on i) the anatomical location where the T<sub>RM</sub>-like phenotype is specified and ii) if and how migratory DCs subsets participate to the induction of T<sub>RM</sub>-like CD8⁺ T cells within tumor-draining lymph nodes.

In this study, we delineate the activation of tumor-infiltrating T<sub>RM</sub>-like cells in the KP (*Kras*<sup>G12D</sup>, *p53<sup>-/-</sup>*) model of lung adenocarcinoma. We identify an unexpected contribution of IRF4-dependent migratory DCs in activating pre-T<sub>RM</sub> precursors in tdLNs to give rise to tumor-infiltrating T<sub>RM</sub>-like TILs. In addition, we show that the low density of MHCI-peptide complexes evoking a mild TCR triggering promote specification into T<sub>RM</sub>-like phenotype.

RESULTS

CD8<sup>+</sup> T cells with a T<sub>RM</sub>-like phenotype infiltrate lung tumors.

To determine the extent of T<sub>RM</sub>-like cells infiltrating the lungs after engraftment of tumor cells, we employ a cell line derived from *Kras*<sup>G12D</sup> *p53<sup>-/-</sup>* mice<sup>32,41,42</sup> (Fig.S1A). We found that a large proportion of CD8<sup>+</sup> TILs stained positive for both CD69 and CD103 expression (27.3%, Fig. 1A) which is a classical gating for T<sub>RM</sub> phenotype. CD8<sup>+</sup> TILs also stained positive for PD1 and TIM3 (21.7%, Fig. 1B), a feature of exhausted T cells. In line with other studies highlighting the expression of exhaustion markers on T<sub>RM</sub>-like TILs<sup>3,20</sup>, we found that these two subsets were largely overlapping (Fig. 1C and S1B). This led us to investigate the correspondence between cell surface phenotype and transcriptional profile in unbiased settings using a single-cell RNA-sequencing (scRNA-seq) combined with CITE-Seq approach (Fig. 1D and S1C). scRNA-seq identified 5 clusters of Cd44<sup>+</sup>Sell<sup>-</sup> cells (clusters 1, 4, 7, 8, 9) (Fig. 1D-E and S1D). Clusters 4 and 7 expressed Tcf7 and intermediate levels of Pdcd1, aligning them to a T<sub>PEXh</sub> phenotype. Clusters 1, 8 and 9 shared the expression of multiple exhaustion molecules (Pdcd1, Lag3, Havcr2, Tigit, Tox) and scored high for an exhaustion signature (Fig. 1E-F). Among these exhausted clusters, cluster 1 expressed core T<sub>RM</sub>-associated genes (such as Itgae/CD103, Itga1/CD49a and Cxcr6) and scored high for a residency signature. Using CITE-Seq antibodies, we identified T<sub>RM</sub>-like TILs (CD44<sup>+</sup>CD62L<sup>-</sup>CD103<sup>+</sup>CD69<sup>+</sup>) and found that they overlapped mostly with cluster 1 (Fig. 1G and S1E). By contrast, CD44<sup>+</sup>CD62L<sup>-</sup>PD1<sup>+</sup> activated cells distinct from CD103<sup>+</sup>CD69<sup>+</sup> comprised a variety of transcriptional phenotypes including cycling and Tox<sup>+</sup> exhausted clusters (clusters 8 and 9).

To further confirm these results, we designed a gating strategy enabling the prospective isolation of TILs populations identified above. As already shown previously, CD69<sup>+</sup>CD103<sup>+</sup> T<sub>RM</sub>-like TILs were largely enriched in an exhausted phenotype PD1<sup>+</sup>TIM3<sup>+</sup> (68.0%, termed here as TIM3<sup>+</sup> T<sub>RM</sub>) but also contained a population of PD1<sup>+</sup>TIM3<sup>-</sup> (29.2%, termed here as TIM3<sup>-</sup> T<sub>RM</sub>) and a minor fraction of PD1<sup>-</sup>TIM3<sup>-</sup> cells (Fig. 1H-I). Conversely, we also identified PD1<sup>+</sup>TIM3<sup>+</sup> (37.0%, termed here as TIM3<sup>+</sup> T<sub>Exh</sub>) and PD1<sup>+</sup>TIM3<sup>-</sup> (42.9%, termed here as TIM3<sup>-</sup> T<sub>PEXh</sub>) distinct from CD69<sup>+</sup>CD103<sup>+</sup>. PD1-negative CD8<sup>+</sup> T cells also comprised CD62<sup>-</sup>CD44<sup>+</sup> activated effector T cells (20.4%, termed here as PD1<sup>-</sup> T<sub>Eff</sub>). Similar populations were found in the autochtonous KP cancer model which recapitulates the human physiopathology from hyperplasia to adenocarcinoma and the onset of T cell dysfunction<sup>32,41,42</sup> (Fig. S1F-I).

Bulk RNA-seq profiling further validated the correspondence between the T<sub>RM</sub>-like gate and the enrichment in T<sub>RM</sub>-associated genes and signatures (*Itgae*, *Itga1*, *Rgs1*, *Cxcr6* e.g.) and gene ontology pathways "regulation of cell migration", "TGF-β signalling pathway", "R-SMAD binding" (Fig. 1J-K and S1J-M). By contrast, T<sub>RM</sub> expressed lower levels of effector-associated genes (*Eomes*, *Gzmk*, e.g.) and of genes ensuring recirculation (*Klf2* and *S1pr1*, e.g.)<sup>4,11</sup>. Finally, we confirmed by FACS that T<sub>RM</sub>-associated proteins (Hobit in Hobit reporter mice<sup>18</sup> and CD49a encoded by *Itga1*) were expressed at higher levels in TIM3<sup>+</sup> T<sub>RM</sub> while they express low levels of EOMES and KLRG1 (Fig. 1L-M). Also, we found that the human T<sub>RM</sub> signature was enriched in TIM3<sup>+</sup> T<sub>RM</sub> as compared to TIM3<sup>+</sup> T<sub>Exh</sub> (Fig.S1N), thereby validating their physiological relevance. Unlike other T cell subsets, T<sub>RM</sub>-like TILs (CD69<sup>+</sup>CD103<sup>+</sup>TIM3<sup>+/-</sup>) were not stained after intravenous injection of anti-CD45.2-PE antibodies labelling the vascular compartment. This demonstrates their localization in the lung parenchyma (Fig. 1N).

We next focused our analysis on tumor antigen-specific cells after engraftment of a KP cell line expressing the ovalbumin protein (KP-OVA, Fig. 1O-P). Tumor-antigen specific tetramer-OVA⁺ cells encompassed similar subsets but displayed a significant enrichment in TIM3-expressing cells including TIM3⁺ T<sub>EXH</sub> and TIM3⁺ T<sub>RM</sub>, unlike PD1⁻T<sub>EFF</sub> that were mostly found in the tetramer-OVA⁻ fraction (Fig. 1Q). Functionally, we found that both TIM3⁺ T<sub>RM</sub> (15.5%) and TIM3⁺ T<sub>EXH</sub> (11.9%) were able to produce pro-inflammatory cytokines IFNg and TNFa after *ex vivo* antigen-specific restimulation with the OVA<sub>257-264</sub> peptide (Fig. 1R). Of note, TIM3⁻ T<sub>RM</sub> (5.7%) but not TIM3⁻ T<sub>PEXH</sub> (1.3%) displayed some levels of polyfunctionality.
Altogether, we conclude that the transplanted KP model recapitulates some features of human NSCLC in terms of dysfunctionality and T<sub>RM</sub>-like phenotype<sup>1,3,7,9,43</sup>. Our results define T<sub>RM</sub>-like TILs as a specific, separable subset within a larger population of CD8<sup>+</sup> TILs expressing co-inhibitory receptors. Therefore, this model is suitable to investigate how the T<sub>RM</sub>-like phenotype is instructed in comparison to other PD1<sup>+</sup> TILs.

Tumor-draining lymph nodes contain a fraction of CD103<sup>+</sup> activated CD8<sup>+</sup> T cells poised to generate T<sub>RM</sub>-like TILs.

The anatomical localization where T<sub>RM</sub> specification occurs is still a matter of debate. Therefore, we wondered whether CD8<sup>+</sup> T<sub>RM</sub>-like TILs require egress from tumor-draining mediastinal lymph nodes (tdLN) or differentiate *in situ* from a T cell pool pre-existing tumor development. To address this, we inhibited lymph node egress using S1PR1 blockade with fingolimod (FTY720) and analysed T<sub>RM</sub>-like TILs at day 14 post-tumor engraftment (Fig. 2A). We found that FTY720 administration from day 1 to 14 or from day 7 to 14 blocked T<sub>RM</sub> infiltration in the lungs (Fig. 2B). We conclude that tdLNs represent an obligate site during the development of CD8<sup>+</sup> T<sub>RM</sub>-like TILs.

Having established a role for tdLN in T<sub>RM</sub> infiltration, we next sought to characterize tdLN CD8<sup>+</sup> T cells after KP tumor engraftment. We found that KP tumor development induced the expansion of CD62L<sup>-</sup>CD44<sup>+</sup> activated CD8<sup>+</sup> T cells ("T<sub>Act</sub>") (Fig. 2C). Because CD103 expression has been widely used as a marker of T<sub>RM</sub> biased T cells in other settings<sup>24</sup>, we analysed CD103 expression and found that 41.3% of T<sub>Act</sub> expressed CD103 (Fig. 2C and S2A). CD103<sup>+</sup>T<sub>Act</sub> population was similarly observed in OVA-specific T<sub>Act</sub> after KP-OVA engraftment (15.0%) (Fig. 2D-F). Bulk RNA-sequencing analysis showed that CD103<sup>+</sup> T<sub>Act</sub> were enriched in T<sub>RM</sub> core genes such as *Cxcr6*, *Fgl2*, *Itga1* and *Innp4b* (Fig. 2G and S2B-D). On the contrary, CD103<sup>-</sup> T<sub>Act</sub> expressed more T<sub>effector</sub> (*Eomes*, *Gzmk*) and proliferation-associated genes (*Mki67*). Consistently, GSEA analysis revealed that lymphocyte residency signatures were enriched in CD103<sup>+</sup> T<sub>Act</sub> while signature of genes associated to circulating lymphocytes were enriched in CD103<sup>-</sup> T<sub>Act</sub><sup>4,11</sup> (Fig. 2H and S2E). CD103<sup>+</sup> T<sub>Act</sub> were also enriched for genes associated to KP-bearing lung TIM3<sup>+</sup> T<sub>RM</sub> while CD103<sup>-</sup> T<sub>Act</sub> were enriched for genes associated to KP bearing-lung TIM3<sup>+</sup> T<sub>Exh</sub> (Fig. 2I). At the protein level, CD103<sup>+</sup> T<sub>Act</sub> expressed lower levels of effector-associated markers (T-BET, EOMES, KLRG1 and CX3CR1) (Fig. 2J and S2F) but higher T<sub>RM</sub>-enriched markers such as CD49a, Hobit, CTLA4 and CXCR6 (Fig. 2K). We therefore hypothesized that CD103<sup>+</sup> T<sub>Act</sub> are biased to give rise to lung T<sub>RM</sub>-like TILs. To assess the relationship between CD103<sup>+</sup> T cells in tdLN and lung T<sub>RM</sub>-like TILs, we took advantage of the CD103-cre<sup>ERT2</sup>-ROSA<sup>LSL-tdTomato</sup> reporter mouse<sup>44</sup> (hereafter referred as CD103-tdTomato). Tamoxifen induction 8 days after KP injection efficiently labelled CD103<sup>+</sup> T<sub>Act</sub> (45.6%) but not CD103<sup>-</sup> T<sub>Act</sub> (1.5%) in tdLNs from CD103-tdTomato donor mice (Fig.S2G). We thus transferred whole tdLN containing genetically labelled CD103<sup>+</sup> T cells in KP tumor-bearing CD45.1<sup>+</sup> WT recipient mice (Fig. 2L). We assessed T<sub>RM</sub> phenotype in the progeny of tdTomato<sup>-</sup> or tdTomato<sup>+</sup> transferred tdLN CD8<sup>+</sup> T cells in the lungs as controlled in endogenous CD8<sup>+</sup> T cells from the host mice (Fig.S2G). We found that tdTomato<sup>+</sup> transferred T cells exclusively gave rise to T<sub>RM</sub>-like but not other CD44<sup>+</sup>CD62L<sup>-</sup> CD8<sup>+</sup> TILs (100.0%, Fig. 2M). By contrast, only a small fraction of tdTomato<sup>-</sup> transferred CD8<sup>+</sup> T cells differentiated into T<sub>RM</sub>-like TILs (8.5% of CD44<sup>+</sup>CD62L<sup>-</sup> CD8<sup>+</sup> TILs).

These results demonstrate that T<sub>RM</sub> specification is initiated in tdLNs where CD103<sup>+</sup> T cells are pre-committed to differentiate into T<sub>RM</sub>-like TILs
after seeding tumor-bearing lungs.

Both XCR1+ and IRF4-dependent DCs contribute to the differentiation of CD103+T<sub>Act</sub> in tdLN

Because DCs are the main tumor antigen-presenting cells in the LN, we assessed their requirements for the generation of CD103<sup>+</sup> T<sub>Act</sub> in tdLN. We
found that KP tumor development triggered a massive increase of both resident and migratory XCR1<sup>+</sup> DC1s and CD11b<sup>+</sup> DC2s compared to
mediastinal LN from naïve mouse (Fig. 3A-B). To better characterise DC populations in tdLN, we performed scRNA-Seq of CD11c<sup>+</sup>MHCII<sup>+</sup> cells 14
days after KP tumor engraftment (Fig. 3C and S3A). We identified 2 clusters of XCR1<sup>+</sup> resident DC1 (clusters 7, 14) and 3 clusters of SIRPa<sup>+</sup> resident
DC2 (clusters 3, 9, 17). Within the clusters expressing high levels of maturation markers (Ccr7, Cd80, Cd86, Cd200, Cd274, Pdcd1lg2 e.g.) (clusters
2, 5, 8), CITE-Seq protein expression of XCR1 and SIRPa enabled to discriminate migratory DC1 (cluster 2) from migratory DC2 (cluster 8), although
cluster 5 was composed of a mix of migratory DC1 and DC2 as reported earlier<sup>45</sup> (Fig. 3D-E). To assess the contribution of DC subsets in T<sub>RM</sub>
differentiation, we engrafted KP tumors in Xcr1<sup>cre</sup>X Rosa<sup>LSL-DTA</sup> (Xcr1<sup>DTA</sup>,<sup>46</sup>) or Cd11c<sup>cre</sup>Xlrf4fl/fl (Cd11c<sup>lrf4,47</sup>) mice. Xcr1<sup>DTA</sup> mice were deficient in
XCR1<sup>+</sup> DCs while Cd11c<sup>lrf4</sup> mice had reduced numbers of migratory but not resident DC2s (Fig. 3F and S3B-C). By performing scRNA-Seq in
Cd11c<sup>lrf4</sup> mice, we confirmed that migratory DC2 cluster 2 was reduced as compared to WT mice, while most clusters including resident DC2
clusters 3, 9 and 17 were left unaffected (Fig. 3G-H). Consistent with a well-established role of DC1s in activating CD8<sup>+</sup> T cell responses<sup>29,30,48,49</sup>, we
found that tetramer-OVA<sup>+</sup> T<sub>Act</sub> were severely reduced in Xcr1<sup>DTA</sup> mice bearing KP-OVA tumors (Fig.S3D), including CD103<sup>+</sup> T<sub>Act</sub> (Fig. 3I). Conversely,
depletion of IRF4-dependent DCs in Cd11c<sup>lrf4</sup> did not impact tetramer-OVA<sup>+</sup> CD8<sup>+</sup> T cell activation (Fig.S3D) but led to a selective decrease in
tetramer-OVA<sup>+</sup>CD103<sup>+</sup> T<sub>Act</sub> numbers (Fig. 3I). Similar results were found after adoptive transfer of OVA-specific OT1 T cells prior to tumor engraftment (Fig.S3E). Analysis of OT1 in tdLN at day 9 revealed impaired CD103 expression in both Xcr7<sup>DTA</sup> and Cd11c<sup>Irf4</sup> mice (Fig. 3J).

Altogether, these results show that both XCR1<sup>+</sup> DC1s and IRF4-dependent DC2s are required for the crosspriming of tumor-specific CD103<sup>+</sup> T<sub>Act</sub> in
tdLN that are poised to generate T<sub>RM</sub>-like TILs.

CD103<sup>+</sup> activated T cells in tdLN contain a rare population of CXCR6<sup>+</sup>T<sub>RM</sub>-like cells.

To better characterize the heterogeneity of tdLN activated CD103<sup>+</sup>CD8<sup>+</sup>T cells giving rise to lung T<sub>RM</sub>-like TILs in unbiased settings, we performed single-cell RNA-sequencing of a mixture of 80% of T<sub>Act</sub> and 20% of T<sub>Naive</sub> and T<sub>CM</sub> (Fig. 4A and S4A). We identified 4 clusters of activated Cd44<sup>+</sup>Sell<sup>-</sup> CD8<sup>+</sup> T cells (clusters 0, 3, 5 and 8)(Fig. 4B). Cluster 5 was highly proliferating (<i>Mki67</i><sup>high</sup>). Among the remaining activated clusters, Itgae expression was restricted to clusters 0 and 8. Strikingly, cluster 8 expressed high levels of *Cxcr6* and scored high for residency but low for circulating signatures or stemness-associated genes (*Slamf6*, *Tcf7*) (Fig. 4B-C and S4B). Consistently, this cluster scored the highest for genes associated to KP-bearing lung TIM3<sup>+</sup> T<sub>RM</sub> (Fig.S4B). CITE-Seq gating also showed that CD103 was most highly expressed by cluster 8 (Fig.S3C). However, the majority of CD103<sup>+</sup> TAct cells were found in cluster 0 since cluster 8 contains very few cells (Fig. 3D). To further compare single-cell RNA-seq clusters obtained in both lung and tdLN locations, we projected lung clusters on the tdLN dataset. We found that T<sub>RM</sub> cluster 1 from the lung was almost exclusively projected on *Cxcr6*<sup>+</sup> cluster 8 from the tdLN (84.25%, Fig. 4E), thereby validating their transcriptional alignment. Taking advantage of this information, we refined our FACS gating strategy to separate previously gated CD103<sup>+</sup> T<sub>Act</sub> into CD103<sup>+</sup>CXCR6<sup>-</sup> and CD103<sup>+</sup>CXCR6<sup>+</sup> T<sub>Act</sub> (Fig. 4F). We found that CD103<sup>+</sup>CXCR6<sup>+</sup> T<sub>Act</sub> expressed low levels of SLAMF6 but higher levels of PD1 and Hobit than CD103<sup>-</sup> or CD103<sup>+</sup>CXCR6<sup>-</sup> T<sub>Act</sub> (Fig. 3G and S4D). CD103<sup>+</sup>CXCR6<sup>+</sup> T<sub>Act</sub> were found highly enriched within tumor antigen-specific tetramer-OVA<sup>+</sup> T<sub>Act</sub> from KP-OVA bearing mice (2.1% of tetramer-OVA<sup>-</sup> T<sub>Act</sub> vs 15.2% of tetramer-OVA<sup>+</sup> T<sub>Act</sub>) unlike CD103<sup>+</sup>CXCR6<sup>-</sup> that were almost exclusively tetramer-OVA<sup>-</sup> (31.5% of tetramer-OVA<sup>-</sup> T<sub>Act</sub> vs 0.9% of tetramer-OVA<sup>+</sup> T<sub>Act</sub>) (Fig. 4H-I). CD103<sup>-</sup> T<sub>Act</sub> encompassed both tetramer-OVA<sup>+</sup> and tetramer-OVA<sup>-</sup> cells. Phenotyping tetramer-OVA<sup>+</sup> T<sub>Act</sub> led to similar results compared to endogenous T<sub>Act</sub> as CD103<sup>+</sup>CXCR6<sup>+</sup> T<sub>Act</sub> expressed high levels of T<sub>RM</sub> marker CD49a but low levels of SLAMF6 (Fig.S4E-F). In order to identify conserved T<sub>RM</sub> markers across anatomical locations, we combined our different datasets and found that 38 genes overlapped between lung T<sub>RM</sub> cluster 1, tdLN *Cxcr6*<sup>+</sup> cluster 8 and genes associated to lung TIM3<sup>+</sup> T<sub>RM</sub> as compared to TIM3<sup>+</sup> T<sub>Exh</sub> (Fig.S4G). We validated at the level of protein expression that JAML, DNAM (encoded by *Cd226*) and CD49a were indeed expressed at higher levels by lung T<sub>RM</sub> and tdLN CD103<sup>+</sup>CXCR6<sup>+</sup> T<sub>Act</sub> as compared to other T cell populations (Fig.S4H). These results demonstrate the existence of a rare population of CD103<sup>+</sup>CXCR6<sup>+</sup> T<sub>RM</sub>-like cells in tdLN. We thus wondered whether this population would be similarly affected by lack of DC populations in *Xcr1*<sup>DTA</sup> and *Cd11c*<sup>Irf4</sup> mice bearing KP tumors. Consistent with previous results obtained in antigen-specific assays (Fig. 3I-J), we found that all T<sub>Act</sub> populations including CD103<sup>+</sup>CXCR6<sup>+</sup> T<sub>Act</sub> were severely reduced in *Xcr7*<sup>DTA</sup> mice (Fig. 4J-L). By contrast, total T<sub>Act</sub> numbers were similar in *Cd11c*<sup>Irf4</sup> mice but both CD103<sup>+</sup>CXCR6<sup>-</sup> and CD103<sup>+</sup>CXCR6<sup>+</sup> T<sub>Act</sub> were reduced.

Altogether, these results demonstrate that CD103<sup>+</sup> T<sub>Act</sub> contain a rare population of CXCR6<sup>+</sup> T<sub>RM</sub>-like cells and that both XCR1<sup>+</sup> and IRF4-dependent migratory DCs are required for the differentiation of CD103<sup>+</sup>CXCR6<sup>+</sup> T<sub>RM</sub>-like cells in tdLN.

Efficient generation of T<sub>RM</sub>-like TILs involves both XCR1<sup>+</sup> and IRF4-dependent DCs at the level of tdLN.

We next sought to address the consequences of impaired T<sub>RM</sub> specification at the level of tdLN on the generation of lung T<sub>RM</sub>-like TILs.

In a first approach, we engrafted KP tumors in WT, *Flt3L*<sup>-/-</sup> deficient in all classical DC subsets, and *Ccr2*<sup>-/-</sup> mice deficient in inflammatory monocytes and assessed CD8<sup>+</sup> T<sub>RM</sub>-like content. In accordance with a non-redundant role of classical DCs in CD8<sup>+</sup> T cell immunity<sup>29,50</sup>, we found that CD8<sup>+</sup> T<sub>RM</sub>-like infiltration was deeply inhibited in DC-deficient *Flt3L*<sup>-/-</sup> mice (Fig.S5A-B). However, T<sub>RM</sub>-like TILs accrual was not modified in *Ccr2*<sup>-/-</sup> mice, excluding a role for monocyte-derived/inflammatory phagocytes in T<sub>RM</sub> generation. To further define the role of XCR1 and IRF4-dependent DCs, we analysed the differentiation of polyclonal CD8<sup>+</sup>T cells in *Xcr1*<sup>DTA</sup> and *Cd11c*<sup>Irf4</sup> mice engrafted with KP tumors. In *Xcr1*<sup>DTA</sup> mice, a major defect in the infiltration of all CD8<sup>+</sup> T cells subsets was observed (Fig. 5A-B). These results highlight general defects in CD8<sup>+</sup> T cell activation in DC1-lacking mice<sup>29,32,49</sup> and correlate with the deep impairment in T cell activation observed in tdLN (Fig. 4J-L). By contrast, *Cd11c*<sup>Irf4</sup> mice only had a partial and selective defect in both TIM3<sup>-</sup> and TIM3<sup>+</sup> T<sub>RM</sub> populations while other populations of CD8<sup>+</sup> TILs were left unaffected.

Next, we intended to address the role of DC subsets on CD8+ T cell populations in tumor antigen-specific settings using KP-OVA tumors engrafted in WT, Xcr7DTA and Cd11cIrF4 mice. We found that after 14 days, tetramer+ OVA-specific lung CD8+T cells were severely reduced in Xcr7DTA but not in Cd11cIrF4 mice (Fig. 5C-D and S5C-D). However, tetramer+ OVA-specific CD8+ T<sub>RM</sub>-like TILs were reduced in Cd11cIrF4 mice and they represented the most impacted population of activated CD8+ T cells. Of note, PD1- effector CD8+T cells were not impacted in Cd11cIrF4, evidencing a differential regulation compared to T<sub>RM</sub> in antigen-specific context as well.
We have shown above that both migratory DC subsets promote pre-T<sub>RM</sub> generation in tdLN (Fig. 4J-L). To assess the contribution of this tdLN-localized phenomenon on lung T<sub>RM</sub> accrual, we adoptively transferred total cell suspensions obtained from tdLN of WT, *Xcr1<sup>DTA</sup>* or *Cd11c<sup>Irf4</sup>* mice to KP-bearing WT host mice (Fig. 5E). This setting allowed us to normalise the lung tumor-microenvironment in recipient mice as controlled by similar responses in endogenous CD45.2<sup>+</sup> CD8<sup>+</sup> T cells (Fig. S5E-F). As anticipated, total donor CD8<sup>+</sup>T cells from *Xcr1<sup>DTA</sup>* but not *Cd11c<sup>Irf4</sup>* tdLNs were decreased in host lungs 7 days post-transfer (Fig. 5F-G). However, the generation of T<sub>RM</sub>-like TILs was impaired when tdLN progenitors originated from *Xcr1<sup>DTA</sup>* or *Cd11c<sup>Irf4</sup>* tdLNs.

These results demonstrate that T<sub>RM</sub>-like TILs activation necessitate the presence of both migratory XCR1<sup>+</sup> DC1s and IRF4<sup>+</sup> CD11b<sup>+</sup> migratory DC2s in tdLN. By contrast, the generation of non-T<sub>RM</sub>, exhausted CD8<sup>+</sup> T cells or PD1<sup>-</sup> CD8<sup>+</sup> T cell effector populations is more selectively dependent on DC1s and less impacted by DC2 deficiency.

### Low TCR triggering by migratory crosspriming DC2s favors CD103 expression while migratory DC1-derived IL-12 supports CXCR6 expression.

Because both types of migratory DCs were required for T<sub>RM</sub>-specification in the LN, we wondered which could be the mechanism accounting for their respective contribution. We first analysed the ability of both types of migratory DCs to uptake tumor antigens. To do so, we engrafted mice with KP tumors expressing the lysosomal-stable ZsGreen fluorescent protein. We found that both XCR1<sup>+</sup> and IRF4-dependent CD11b<sup>+</sup> migratory but not resident DCs had some levels of antigen uptake, although XCR1<sup>+</sup> migratory DCs were more able to transport tumor antigens to the LN (52.3% ZsGreen<sup>+</sup> MigDC1s vs 13.4% ZsGreen<sup>+</sup> MigDC2s) (Fig. 6A). We next wondered if migratory DCs had acquired an immunogenic phenotype. Using IL-12<sup>YFP</sup> reporter mice (Fig. 6B) and scRNAseq on migratory DCs (Fig.S6A), we showed that migratory DC1 expressed much higher levels of IL-12 (78.3%) than migratory DC2 (15.9%). Therefore, we conclude that XCR1<sup>+</sup> migratory DCs had undergone some level of activation supporting their ability to prime T cells. We next assessed the ability of both types of migratory DCs to cross-present tumor-associated antigens to CD8<sup>+</sup> T cells through MHC-I. To do so, we performed a staining on tdLN DCs from KP or KP-OVA tumors with an antibody detecting H2-K<sup>b</sup>-SIINFEKL (OVA immunodominant epitope) complexes arising from the cross-presentation of KP-associated OVA protein<sup>51</sup>. We found that both XCR1<sup>+</sup> and CD11b<sup>+</sup> migratory DCs cross-presented tumor-associated OVA antigen, although XCR1<sup>+</sup> DC1s did it more efficiently than CD11b<sup>+</sup> DC2s (319.8 vs 132.8 MFI H2K<sup>b</sup>-OVA) (Fig. 6C). Of note, no signal was detected on resident DCs. Functionally, we evaluated the cross-presentation ability of migratory or resident DCs sorted from KP-OVA tdLNs by co-cultivating them with Cell trace violet (CTV)-loaded OVA-specific OT-1 CD8<sup>+</sup> T cells. Migratory but not resident DCs were able to induce the proliferation of OT-1 and upregulation of CD44 (66.4% vs 2.82% of CTV<sup>low</sup>CD44<sup>+</sup>) (Fig.S6B). We thus focused our study on migratory DC subsets only. FACS-sorted migratory XCR1<sup>+</sup> DC1s and CD11b<sup>+</sup> DC2s from KP-OVA-bearing tdLNs were co-cultured with CTV-loaded OT-1 for 2 days (Fig. 6D). We found that DC1 induced a vigorous proliferation of OT-1 that were almost entirely CD103-negative while they expressed homogenously the CD44 activation marker (Fig. 6E-F). By contrast, activation by CD11b<sup>+</sup> DC2s was milder but CD44<sup>+</sup> proliferating OT-1 expressed high levels of CD103. We wondered which factor could explain the differential ability of CD11b<sup>+</sup> DC2s to maintain CD103 expression. We showed that IL-12 was highly produced by migratory DC1 (Fig. 6B) and IL-12 silences TGF-β activated CD103 expression via TBET competition at SMAD binding elements within CD103 promoter<sup>52</sup>. Therefore, we tested the role of IL-12 *ex vivo* and found that addition of recombinant IL-12 blunted CD103 expression without affecting the proliferation of naïve OT-1 by KP-OVA-loaded CD11b<sup>+</sup> DC2s (Fig. 6E-F). By contrast, IL-12 blockade during DC1-dependent activation did not restore CD103 on proliferating T cells. We therefore hypothesized that another parameter, distinct from IL-12, was associated to cross-priming by DC1s and limited CD103 expression in activated T cells. We hypothesized that higher levels of MHCI-peptide complexes on DC1s (Fig. 6C) could intrinsically limit CD103 persistence on activated T cells. To test this, we exposed CD11b<sup>+</sup> DC2s sorted from tdLNs to increasing amounts of SIINFEKL synthetic peptide *ex vivo* in the presence of naïve OT1s. We found that peptide add-back was sufficient to impair CD103 expression in CD44<sup>+</sup>CTV<sup>low</sup> OT-1 T cells while it increased proliferative expansion, thereby mimicking T cell activation by XCR1<sup>+</sup> DC1s (Fig. 6G-H). We next addressed the role of TCR avidity for MHCI-peptide complexes in controlling CD103 persistence on activated T cells. To this end, we primed naïve OT1s with various altered peptide ligands acting as weaker agonists for the OT1 TCR<sup>53</sup>. We observed a decrease of OT-I activation with low affinity peptides (SIINFEKL > Q4 > T4 > G4), associated to an increased expression of CD103 on CD44<sup>+</sup> divided OT-I cells (Fig. 6I and S6C). Overall, we conclude that a mild TCR triggering and low levels of IL-12 are both required for the persistence of CD103 on T cells during their cross-priming by migratory DCs. However, CXCR6 expression is also a hallmark of early-activated pre-T<sub>RM</sub><sup>S</sup> in tdLN5 (Fig. 4). We found that IL-12 blockade *in vivo* blunted T cell activation while inhibiting CXCR6 expression in tdLN5 (Fig. 6J-K). Consistently, IL-12 also promoted CXCR6 expression during the priming of naïve OT1 *in vitro* (Fig. 6L-M). This shows that IL-12, despite its inhibitory effect on CD103, is required to acquire the full T<sub>RM</sub> phenotype. Given the paramount role of TGF-β signaling in the specification of T<sub>RM</sub><sup>54</sup>, we further tested the role of IL-12 in combination with TGF-β *in vitro*. We found that IL-12 inhibited TGF-β signaling supporting CD103 expression (Fig. 6M). Vice versa, TGF-β counteracted i) TCR-induced CD103 inhibition and ii) IL-12-induced CXCR6 expression (Fig. 6M). As a result, optimal generation of CD103<sup>+</sup>CXCR6<sup>+</sup> OT1s required both IL-12 and TGF-β and intermediate levels of antigen presentation ensuring mild TCR triggering (Fig. 6L-M).

Altogether, we conclude that i) both XCR1<sup>+</sup> and CD11b<sup>+</sup> migratory DCs, (but not resident DCs) cross-present KP-associated antigens to T cells in tdLN5. ii) XCR1<sup>+</sup> DC1s are the most efficient at antigen uptake, cross-presentation and in triggering CD8<sup>+</sup> T cell proliferative expansion concomitant with the loss of CD103 which is dependent on both efficient TCR triggering and IL-12 release. iii) IL-12 low, CD11b<sup>+</sup> DC2s are inefficient at uptake,
cross-presentation and in triggering CD8⁺ T cell proliferative expansion but the low efficiency of antigen cross-presentation by CD11b⁺ migratory DC2s is required for CD103 persistence on CD44⁺ activated T cells by delivering a milder TCR signalling as compared to XCR1⁺ DC1s. iv) despite its inhibitory effect on CD103 expression, IL-12 is crucially needed for CXCR6 expression.

**Cross-priming by migratory DC2s recapitulates the T<sub>RM</sub> transcriptional program.**

We next sought to analyse how the identity of migratory DCs subset controlled the transcriptional phenotype of CD8⁺ T cells during cross-priming. To this end, we performed bulk RNAseq on OT1 cells that did or did not upregulate CD103 after *ex vivo* crosspriming by migratory DC1 or DC2 sorted from tdLN of KP-OVA bearing mice (Fig. 7A). PCA analysis revealed a stronger segregation between DC1 and DC2-activated OT1 across PC1 (84% of the variance) compared to CD103 expression (Fig. 7B). We conclude that the identity of migratory DCs cross-priming T cells is the main factor driving their transcriptional phenotype. PC1 was positively driven by T<sub>RM</sub>-associated genes (*Itgae*, *Cd226* e.g.) and stemness genes (*Klf2*, *Sell*, *Slamf6*, *Il7r*, e.g.) and negatively driven by effector-related genes (*Il12rb1* and *Il12rb2*, *Tbx21*, *Gzmb*, *Eomes*, e.g.) and proliferation associated transcription factor *Myc*. T<sub>RM</sub>-associated signatures found in tdLNs pre-T<sub>RMs</sub> (by scRNASeq, DEG Cluster 8 *Cxcr6*⁺ or bulk RNA-Seq, CD103⁺ T<sub>Act</sub> > CD103⁻ T<sub>Act</sub>) or lung T<sub>RM</sub>-like TILs (bulk RNA-Seq, TIM3⁺ T<sub>RM</sub> > TIM3⁺ T<sub>Exh</sub>) associated primarily with CD103⁺ OT1 crossprimed by DC2s (CD103⁺ OT1<sub>DC2-Act</sub>, Fig. 7C). By contrast, signature of genes downregulated in pre-T<sub>RM</sub> (bulk RNA-Seq, CD103⁻ T<sub>Act</sub> > CD103⁺ T<sub>Act</sub>) was poorly expressed by CD103⁺ OT1<sub>DC2-Act</sub>. GSEA analysis of CD103⁺ OT1<sub>DC2-Act</sub> compared to all other OT1 populations, hereafter referred as Rest, further confirmed these results (Fig. 7D). CD103⁺ OT1<sub>DC2-Act</sub> were enriched in T<sub>RM</sub>-associated genes *Itgae*, *Cd226*, *Cxcr6* or *Inpp4b*, stemness-related genes *Il7r* and *Tcf7* and TGF-β receptor genes *Tgfbr1* and *Tgfbr2* (Fig. 6E). Conversely, CD103⁺ OT1<sub>DC2-Act</sub> expressed lower levels of effector-related genes *Gzmb*, *Klrk1*, *Eomes* or *Tbx21*, proliferation-associated transcription factor *Myc* and *Il12r* genes *Il12rb1* and *Il12rb2* (Fig. 7E). Consistently, GSEA scoring of a memory CD8 T cell signature revealed that CD103⁺ OT1<sub>DC2-Act</sub> had increased expression of memory-related genes (NES = 1.46, Fig. 7F). We also evaluated a signature of SMAD4 target genes, a central mediator of TGF-β signalling, and found that it was enriched in CD103⁺ OT1<sub>DC2-Act</sub> (NES = 1.32, Fig. 7F). Conversely, MTORC1 signaling (NES = -1.58) and MYC targets (NES = -1.57) signatures were strongly reduced in CD103⁺ OT1<sub>DC2-Act</sub>, consistent with reduced proliferation activity (Fig. 7G).

Taken together, these results indicate that migratory DC2s recapitulate the differentiation of naïve OT1s into pre-T<sub>RM</sub> similar to those found in tdLNs of tumor-bearing mice. The specification of T<sub>RM</sub> program within naïve T cells is enabled by a stronger activation of TGF-β signalling pathway by migratory DC2s as compared to migratory DC1s.

DISCUSSION

Infiltration of solid tumors with CD8⁺ TILs with a T<sub>RM</sub> phenotype is predictive of improved survival and better response to immunotherapies¹,³,⁵⁻⁹.

Besides, T<sub>RM</sub>-like TILs show signs of superior anti-tumor activity as compared to other T cell populations¹⁶,¹⁷,²⁰,²¹. Therefore, we have sought to address the mechanisms governing the acquisition of the T<sub>RM</sub> phenotype during T cell activation in a murine model of lung cancer. Using a combination of transcriptomic and flow cytometry approaches, we identified a population of T<sub>RM</sub>-like TILs specifically expressing canonical T<sub>RM</sub> markers and sharing the expression of exhaustion molecules with T<sub>EXH</sub>-like TILs. Fate mapping experiments show that CD103 expression during the early phases of T cell activation in tdLNs defines CD8⁺ T cells committed to generate T<sub>RM</sub>-like TILs. Previous studies similarly identified CD103 as a marker of T<sub>RM</sub>-commitment within naïve T cells in a model of skin vaccination²⁴. Using unsupervised analysis of activated T cells in the tdLN, we improved this phenotypic characterization and identified a rare population of CXCR6⁺CD103⁺ T<sub>RM</sub>-like cells. We further addressed the dendritic cell requirements for T<sub>RM</sub> phenotype specification. Induction of CXCR6⁺T<sub>RM</sub>-like precursor cells in tdLNs is dependent on both migratory XCR1⁺ DC1s and IRF4-dependent DC2s. Consistently, lung T<sub>RM</sub>-like TILs accrual requires both types of migratory DCs at the level of tdLN. By contrast, effector and exhausted CD8⁺ T cells infiltrating tumors solely rely on XCR1⁺ DC1s. Finally, we asked which factors provided by DCs subsets could control T<sub>RM</sub>-like TILs generation. We provide evidence that T<sub>RM</sub> specification in tdLNs:

i. requires sub-optimal TCR triggering by weak cross-presenter DC2s that display reduced densities of MHCI-peptide complexes.

ii. is inhibited by high amounts of IL-12 mainly produced by XCR1⁺ DC1s that inhibits TGF-b signalling and its CD103 downstream target.

iii. necessitates some levels of IL-12 as evidenced by the IL-12 function in upregulating CXCR6 during T cell cross-priming.

iv. relies on the proliferative expansion uniquely achieved by cross-priming DC1s.

T<sub>RM</sub> specification occurs in tdLNs and involves both XCR1<sup>+</sup> and IRF4-dependent migratory DCs.

The existence of precursors pre-committed to differentiate into T<sub>RM</sub> has been demonstrated within naïve CD8⁺ T cells epigenetically poised to express T<sub>RM</sub>-associated genes²⁴ and within blood circulating activated T cells after skin vaccination²⁶. Mani et al. showed that TGF-β activation by migratory DCs was required for T<sub>RM</sub> preconditioning at the level of naïve T cells in the LN. Whether this mechanism requires one or multiple DC subsets has not been addressed. Also, it is unknown which DC subset participate to the activation of T<sub>RM</sub> from T<sub>RM</sub>-poised naïve progenitors. Our
study identifies a subset or early activated CD8⁺ T cells expressing selectively a transcriptional signature of tumor-infiltrating T<sub>RM</sub> in tdLN. We
demonstrate that the activation of tdLN CD103⁺ CXCR6⁺ T cells rely on both migratory XCR1⁺ DC1s and IRF4-dependent DC2s. By contrast,
activation of CD103⁻ CD8⁺ T cells is largely independent on the presence of IRF4-dependent migratory DCs. Furthermore, we demonstrate by
adoptive transfer that genetically labelled CD103⁺ T cells from tdLNs uniquely give rise to lung T<sub>RM</sub>-like TILs. Therefore, we establish that the
specification of lung T<sub>RM</sub>-like TILs actually starts within lymph nodes by a process orchestrated by both migratory DCs subsets.

These findings might have a relevance in humans since CD1c⁺ DCs have been shown to participate to the activation of CD8⁺CD103⁺ T<sub>RM</sub>-like cells<sup>39,40</sup>. Of note, the contribution of IRF4-dependent DCs to the generation of memory but not effector T cell responses had been previously noted in the influenza infection model<sup>38</sup> and to the maintenance of anti-infectious T<sub>RM</sub> at mucosal sites in HSV infection<sup>27</sup>. Altogether, our results further extend the major contribution of XCR1⁺ DCs in anti-tumor CD8 T cell immunity to T<sub>RM</sub><sup>29,30,34,48,49</sup>. Our findings are in line with pioneer studies highlighting the crucial role of XCR1⁺ DC1s in the activation of vaccine-induced T<sub>RMS</sub><sup>37</sup>. However, it is important to underline that the role of IRF4-dependent DC2s had not been addressed in this context. In addition, we evidence a contribution of IRF4-dependent DCs to T<sub>RM</sub> generation at the level of tdLNs.

Low TCR signal strength, IL12 and TGF-β synergize to differentiate T~RM~

T<sub>RM</sub> development dependency on TGF-β has been well established in several studies<sup>24,25,27</sup>. However, both migratory DC subsets express TGF-β activating molecules at the transcriptomic level (e.g., *Itgav*)<sup>24</sup>. Therefore, IRF4-dependent migratory DC2s might contribute to T<sub>RM</sub> specification i) by providing a milder TCR signal strength because they cross-present tumor associated antigens inefficiently; ii) by not providing IL-12 in contrast to XCR1<sup>+</sup> DC1s; iii) by providing specific signals yet to be identified. Here, we provide evidence for i) and ii). We show that sub-optimal cross-presentation by DC2s enable CD8<sup>+</sup> T cells to maintain CD103 expression during T cell activation *in vitro*, and this, independently of other factors. These results are in line with previous studies highlighting a negative impact of strong TCR signalling on T<sub>RM</sub> differentiation in vivo in the context of viral infections<sup>58,59</sup>. More recently, Shakiba et al. have shown that low affinity tumor-associated antigens prime T cells expressing higher levels of CD103 while presenting less features of dysfunctional/exhausted T cells as compared to T cells primed with high affinity antigens<sup>60</sup>. Finally, both mild TCR signalling<sup>61</sup> and migratory DC2s contribute to the priming of central memory CD8<sup>+</sup> T cells<sup>62</sup>. In addition to optimal cross-priming efficiency, XCR1<sup>+</sup> migratory DC1s also provide high levels of IL-12 which acts as an inhibitory signal erasing CD103 expression induced by IRF4-dependent migratory DC2s. These findings are in line with the regulatory role of TBET, downstream of IL-12 signalling at SMAD3 binding sites in the CD103 locus<sup>52,63</sup>. Bergsbaken et al. have noticed that IL-12 promotes CD103<sup>+</sup> but not TGF-β dependent CD103<sup>+</sup> T<sub>RM</sub> by a STAT4-dependent mechanism<sup>64,65</sup>. Our results clearly establish that TGF-β-dependent program is induced more efficiently by migratory DC2s than migratory, IL-12-producing DC1s. TGF-β transpresentation might play a role in this process, together with the regulatory role of IL-12 on TGF-β signalling (that can be visualized by IL-12 ability to counteract TGF-β-induced CD103).

Functional features associated to the T<sub>RM</sub> phenotype in cancer

T<sub>RM</sub> have been extensively studied in the context of infections or vaccination when memory is settled and maintained after antigen clearance. In this study, we have not addressed the functional ability of T<sub>RM</sub>-like cells to recirculate or generate memory in the absence of antigen. Recent studies addressing the functional ability of T<sub>RM</sub>-like cells to recirculate in a mouse model of E0771 breast cancer suggest that T<sub>RM</sub> phenotype does not necessarily correlate with tumor residence or correspond to neo-generated T<sub>RM</sub>-like cells from circulating precursors<sup>15</sup>. However, T<sub>RM</sub>-like cells in this model do not express CD103 which may be a major contributor of residence within the tumor through direct interaction with epithelial E-Cadherin which is not expressed in the E0771 cells investigated in this study<sup>66,67</sup>. Evaluating this possibility would require additional experiments.

From a functional perspective, T<sub>RM</sub>-like could represent a pool of responsive cells, able to generate effector cells during challenge or
immunotherapies<sup>3,9,20</sup>. This view is in line with the developmental plasticity of T<sub>RM</sub> upon antigenic restimulation that had been established in
infection-induced T<sub>RMS</sub><sup>18,19</sup>. Deeper functional studies are required to understand the determinants of the prognosis value of T<sub>RM</sub>-like phenotype in
cancer and how their functionality could be activated.

In conclusion, our study highlights the fine-tuning of anti-tumor CD8⁺ T cell diversity by a broad repertoire of migratory DCs subsets in tdLNs. We show that the crosspriming of CD8⁺ T cells reaching a dysfunctional/exhausted phenotype within tumors is uniquely dependent on DC1s and entirely independent on migratory DC2s. By contrast, induction of T<sub>RM</sub>-like cells requires both DC1 and DC2 subsets. These findings challenge the relevance of the “division of labor” across DCs subsets ascribing discrete, specific and exclusive immune functions to specific DCs subsets. Instead, we evidence a high level of cooperativity relevant for the induction of memory precursors in tumor-draining lymph nodes. In sum, our findings support the view that instruction of residency program and proliferative expansion rely on complementary yet distinct DCs subsets.

These findings have important implications for the design of effective immunotherapies harnessing multiple types of CD8+ T cell immunity, *id est*
effector vs tissue-resident memory cells. One correlates of the current findings that remain to be tested, is that optimal priming of diverse T cell
phenotypes might rely on antigen delivery to multiple DCs subsets.

# METHODS

## Study design

The aim of this study was to understand the dendritic cells requirements for T<sub>RM</sub> specification in lung cancer. To that end, we intravenously injected KP lung tumors into several mouse models in which specific dendritic cell populations can be manipulated. We thoroughly characterized polyclonal and antigen-specific CD8 T cell populations to model antigen OVA using a combination of transcriptomics (bulk RNA-seq, scRNA-seq, CITE-Seq) and flow cytometry approaches. To address the role of dendritic cells in the lymph nodes, we designed a series of adoptive cell transfer and *ex vivo* OT1-dendritic cell coculture experiments.

## Mice

Mice were housed at the INSERM U1149 CRI, Medicine school site Bichat or at the Paris Institut Pasteur animal house facilities. Wild type C57BL/6J and CD45.1 mice were purchased from Janvier and kept in our facility. XCR1<sup>cre</sup> and Rosa26-lox-stop-lox-DTA (B6.129P2 Gt(ROSA)26Sortm1(DTA)Lky/J)<sup>68</sup> mice were kindly provided by Dr. Marc Dalod (Center of Immunology Marseille-Luminy, Marseille). XCR1<sup>DTA</sup> mice were generated as described<sup>46</sup>. OT-I RAG2<sup>-/-</sup> CD45.1 mice were kindly provided by Dr. Sébastien Amigorena (Curie institute, Paris). Flt3L<sup>-/-</sup> mice were kindly provided by Dr. Guillaume Darrasse-Jèze (UMR-S 979, Paris). CD11c<sup>cre</sup> mice (B6.Cg-Tg(Itgax-cre)1-1Reiz/J;<sup>69</sup>), IRF4<sup>flox</sup> mice (B6.129S1-Irf4tm1Rdf/J;<sup>70</sup>), and CCR2<sup>-/-</sup> mice (Ccr2tm1/fc;<sup>71</sup>) were kindly gifted by Dr. Emmanuel Gautier (UMR-S U1166, Paris). Hobit-tdTomato-DTR [B6-Tg (Zfp683-tdTomato-P2A-Cre-P2A-DTR);<sup>18</sup>] mice were kindly provided by Dr. Klaas Van Gisbergen, (Champalimaud Fundation, Lisbon). The reporter/deleter cassette disrupts the Hobit allele, in consequence, heterozygous Hobit tdTomato-DTR mice were used in the experiments. KRAS<sup>LSL-G12D/+</sup>,<sup>p53fl/fl</sup> mice<sup>72</sup> were kindly provided by Dr. Kairbaan Hodilvala-Dilke (Bart Institute Queen Mary University, London). CD103<sup>cre-ERT2</sup> (Itgae-creER<sup>T2</sup>) and Rosa<sup>LSL-tdTomato</sup> (B6.Cg-Gt(ROSA)26Sor<sup>tm14(CAG-tdTomato)Hze/J</sup>) mice were kindly provided by Dr. Tessa Bergsbaken (Rutgers, New Brunswick)<sup>44</sup>. IL-12<sup>YFP</sup> (C.129S4(B6)-Il12btm1.1Lky/J;<sup>73</sup>) mice were kindly provided by Dr. Mikaël Pittet. The study was approved by the local ethics committee comité d'éthique Paris Nord no. 121 and the Ministère de l'enseignement supérieur, de la recherche et de l'innovation under the authorization number APAFIS#15373. Animal care and treatment were conducted with national and international laws and policies (European Economic Community Council Directive 86/609; OJL 358; December 12, 1987). All experiments were performed in accordance with the Federation of European Laboratory Animal Science Association (FELASA) guidelines institutional guidelines and the French law.

## Tumor cell lines

The KP line has been isolated from primary lung tumors of C57BL/6 KP mice (*KRAS<sup>LSL-G12D/+</sup>,<sup>p53fl/fl</sup>)<sup>74</sup>. The line was kindly provided by Dr. Federica Benvenuti (ICGEB, Trieste), and has been used previously<sup>35,75</sup>. KP-OVA were generated by retroviral transduction of KP cells with a pBabe-OVA-IRES-Cherry vector. KP-ZsGreen were generated by lentiviral transduction of KP cells with a pLVX-IRES-ZsGreen vector. Tumor cell lines were cultured in RPMI 1640 medium, Glutamax (Thermo Fisher) supplemented with 10% fetal bovine serum (FBS) (Thermo Fisher), penicillin-streptomycin (Thermo Fisher) and 55µM β-mercaptoethanol (Thermo Fisher) (complete RPMI) and maintained at 37°C and 5% CO2.

## Tumor models

For the grafted tumor model, the KP, KP-OVA and KP-ZsGreentumor cell lines were grown in RPMI-Glutamax with 10% FCS, 55 µM 2-mercaptoethanol, Penicillin streptomycine and used for experiments when in exponential growth phase. The cells were detached using Trypsine/EDTA 0.25%, washed two times in PBS and counted in trypan blue. 8.10<sup>5</sup> tumor cells were intravenously injected in 100 mL RPMI without supplement.

For the autochthonous KP model, C57BL/6 KP mice (*KRAS<sup>LSL-G12D/+</sup>,<sup>p53fl/fl</sup>) at 8 weeks of age, were intranasally inoculated with 2.5 x 10<sup>7</sup> infectious particles of a replication-deficient adenoviral vector with Cytomegalovirus promoter driving the expression of the Cre recombinase protein in order to sporadically induce mutations in lung cells, and promote lung tumor development as previously described<sup>62</sup>. Mice were sacrificed 16 weeks after the adenovirus inoculation.

## In vivo treatments

For the FTY treatment, mice received intraperitoneal injections of 1 mg/kg FTY720 (fingolimod) (Sigma-Aldrich) in 150 µl of non-deionised H<sub>2</sub>O (Versol) every 3 days from day 1 after tumor injection. For IL-12p40 blocking, mice received intraperitoneal injections of 200µg anti-IL-12p40 blocking antibody (Biolegend) in 200µl of PBS every 3 days from day 0 after tumor injection.

## Mouse tissues processing
Mouse lungs were harvested and transferred to 3ml digestion buffer (Hank's Balanced Salt Solution (HBSS) with calcium and magnesium (Thermo Fisher) and with 75 µg/mL of Liberase TL (Roche) and 0.02mg/ml DNase I (Thermo Fisher)). Lungs were dissociated using gentleMACS Octo Dissociator (Miltenyi) (program m_lung_01), incubated at 37°C for 45 minutes and dissociated again on the gentleMACS Octo Dissociator (Miltenyi) (program m_lung_02). The cell suspension was passed through a 70 µm cell strainer (Corning) and red blood cells were lysed using ACK lysing buffer (Thermo Fisher). The mediastinal lymph nodes were smashed in FACS buffer on a 70 µm cell strainer. The absolute number of live immune cells in each tissue cell suspension was assessed using AccuCheck Counting Beads (Thermo Fisher) along with anti-CD45 and DAPI staining on BD FACS Fortessa 20 (BD Biosciences). For OT-I CD8⁺T cell preparation, LNs from OT-I CD45.1 RAG mice were passed through 70 µm cell strainers. The LN suspensions were stained with anti-CD8-APCCy7 and counted by FACS using counting beads (AccuCheck beads, Invitrogen).

## Flow cytometry analysis

After tissue processing and cell counting, Fc-receptor were blocked using FcBlock (2.4G2, BD) for 15min at 4°C. For dead cell identification, the cells were stained with 7-AAD (Biolegend) for extracellular staining only or Zombie dye (Biolegend) for intracellular staining in PBS. Cells were then stained with fluorophore-conjugated antibodies in FACS buffer (See antibody list in the Key resource table), PBS 3% FCS (Gibco) 2mM EDTA (Gibco), during 30 minutes at 4°C. When needed, cell suspensions were subsequently fixed and stained in for nuclear protein (30min fixation and 30min intracellular staining) using fixation/permeabilization kit (eBiosciences transcription factor staining buffer) according to the manufacturer's instructions. Labelling with H2Kᵇ-SIINFEKL tetramers (MBL) was performed at room temperature for 30 min. Data acquisition was performed using an LSR-Fortessa X20 (BD) and analysis were done using FlowJo software (TreeStar).

## Ex vivo T cell restimulation assay

After tissue processing and cell counting, 1 million total CD45⁺ cells were incubated for 5 hours at 37°C in a restimulation cocktail composed of 50ng/ml PMA (Sigma), 1µg/ml Ionomycin (Sigma), 2µg/ml Golgi Plug (BD) and 2µg/ml Golgi stop (BD) in complete RPMI medium. Cells were then processed for flow cytometry analysis as described before.

## Bulk RNA-sequencing

After tissue processing and cell count, cell suspensions were washed in cold FACS buffer (PBS + 3% BSA + 2mM EDTA), Fc-receptors were blocked 15min at 4°C, using purified anti-CD16/32 (2.4G2) and, then, stained with fluorophore conjugated antibodies for 30 minutes at 4°C. CD8⁺T cell subsets from tumor-bearing lungs and tdLN were isolated using an Aria III (BD) and a MELODY (BD) cell sorter, respectively, and directly collected on lysing TCL buffer (QIAGEN) containing 0.1% of beta-mercaptoethanol before storage at -80°C. RNA was extracted and isolated using the Single Cell RNA purification kit (Norgen, Cat#51800) according to the manufacturer's instructions. After extraction, total RNA was analyzed using Agilent RNA 6000 Pico Kit on the Agilent 2100 Bioanalyzer System. RNA quality was estimated based on capillary electrophoresis profiles using the RNA Integrity Number (RIN). RNA sequencing libraries were prepared using the SMARTer Stranded Total RNA-Seq Kit v2 - Pico Input Mammalian (Takara). The input quantity of total RNA was comprised between 1 and 22ng. This protocol includes a first step of RNA fragmentation, using a proprietary fragmentation mix at 94°C. The time of incubation was set up for each sample, based on the RNA quality, and according to the manufacturer's recommendations. After fragmentation, indexed cDNA synthesis was performed. Then the ribodepletion step was performed, using probes specific to mammalian rRNA. PCR amplification was finally achieved to amplify the indexed cDNA libraries, with a number of cycles set up according to the input quantity of tRNA. Library quantification and quality assessment was performed using Qubit fluorometric assay (Invitrogen) with dsDNA HS (High Sensitivity) Assay Kit and LabChip GX Touch using a High Sensitivity DNA chip (Perkin Elmer). Libraries were then equimolarly pooled and quantified by qPCR using the KAPA library quantification kit (Roche). Sequencing was carried out on the NovaSeq 6000 (Illumina), targeting between 10 and 15M reads per sample and using paired-end 2 x 100 bp.

## Gene set enrichment analysis

To statistically evaluate the enrichment of previously reported gene signatures and DEG calculated from pairwise comparison in this study (Gene Sets), we used pairwise comparisons using the gene set enrichment analysis (GSEA)⁷⁶ method from the Massachussets Institute of Technology (https://www.broadinstitute.org/gsea). Statistical analysis was performed by evaluation of nominal p value and false discovery rate (q value) based on 1,000 random permutations. Results were considered significant when the p value was below 0.05 and when the q value was below 0.25 (false discovery rate below 25%) accordingly to the recommendation from the software developers.

## scRNA-seq analysis

For cell sorting experiments, tumor-bearing lungs and tdLN were collected and processed as previously described. The strategy used for the sort is depicted in the figures. The droplet-based approach of 10X Genomics platform was used to perform scRNA-seq. For each scRNA-seq sample, cell suspension from three individual mice were pooled and sorted in PBS containing 0.04%BSA. 10 000 cells were loaded on a Chromium Controller using the Chromium Next GEM Single Cell 3 Reagent Kits v3.1 according to manufacturer instructions.

Raw sequencing reads were processed using the 10x Genomics software Cellranger. To obtain a cell count matrix, reads were mapped to the mouse GRCm38.84 reference genome. scRNA-seq analysis was performed using Seurat v4. For each dataset, cells with low genes per cell or with a
high percentage of mitochondrial genes were removed from downstream analyses. Following data QC we obtained 4421 cells from the lungs KP CD8⁺ T cells dataset, 1404 cells for the tdLN KP WT CD8⁺ T cells dataset, 3340 cells for the tdLN KP CD11c<sup>RF4</sup> CD8⁺ T cells dataset, 2076 cells for the tdLN KP WT CD11c<sup>+</sup>MHCII<sup>+</sup> cells dataset and 3150 cells for the tdLN KP CD11c<sup>RF4</sup> CD11c<sup>+</sup>MHCII<sup>+</sup> cells dataset. RNA and ADT expression were normalized separately using the default Seurat LogNormalize and Centered Log Ratio (CLR) approaches, respectively. Top 2000 most variable genes were then determined by applying a VST (Variance Stabilizing Transformation). Datasets were analyzed separately or were integrated together before analysis. For integration, top 2000 most variable genes across datasets were used as anchors with the LogNormalize method. Dimensionality reduction was performed using PCA and the top informative principle components were determined after visualization with an elbow plot and dimensional reduction heatmaps, and used for the non-linear dimensionality reduction technique UMAP. Louvain clustering of the data was performed across a range of resolution parameters visualized using a clustree. Cluster of cells with low number of genes and in which no T lymphocyte cell identifying genes could be detected were not considered in the analysis. Subsequent analyses were performed using Seurat default parameters.

## Adoptive transfers

Mediastinal lymph nodes from donor mice (CD45.2⁺ tumor-bearing or CD45.1⁺ OTI x Rag1⁻/⁻ tumor-free mice, respectively) were mechanically dissociated on a 70µm cell strainers in sterile FACS buffer. After two washes in PBS, the LN cell suspensions were counted as previously described and resuspended in 100µL of RPMI without supplement and intravenously injected in recipient mice (CD45.1⁺ or CD45.2⁺ tumor-bearing mice, respectively), according to the experimental designs described in figures 2L, S3E and 5E.

## Ex vivo Mouse T cell priming assay

### OT-1 cell preparation:

OT-I CD8⁺ T cells were isolated from lymph nodes of CD45.1⁺ OTI x Rag1⁻/⁻ mice and labeled for proliferation assay with 2µM of CellTrace Violet (CTV, Invitrogen) at 37°C for 15 minutes, washed and counted before culture with DC subsets.

### Dendritic cells isolation from LNs:

For the isolation of mediastinal lymph node DCs from KP- or KP-OVA bearing mice, minced mediastinal tumor-draining LNs were digested in 500µl HBSS with calcium and magnesium (Thermo Fisher) with 75 µg/mL of Liberase TL (Roche) and 0.02mg/ml DNase I (Thermo Fisher) and incubated at 37°C for 20 minute under agitation. Cell suspensions were passed through a 70µm cell strainers. Cell suspensions were then blocked in FcBlock and stained with CD11c-biotin followed by SAV-beads (Miltenyi). Cell suspension was applied on a LS column (Miltenyi) according to the manufacturer's instructions. The CD11c-enriched fraction retained in the column was then stained for CD11c, MHCII, CD19, XCR1 and CD11b. Dendritic cells subsets were FACS-sorted on a Melody (BD) according to the gating strategy depicted on the Fig.s.

### DCs and T cell co-culture:

2500 DCs were plated in V-bottom 96 well plates and incubated with 25000 CTV-loaded OT-1 in RPMI medium (10% FCS + 1% Pencillin/Streptomycin + 1mM Sodium Pyruvate 55µM 2-mercaptoethanol and 10mM HEPES). When indicated, various doses of the SIINFEKL OVA peptide or mutated peptides (Q4, T4, G4) were added to the cultures at the indicated concentration. For some experiments, recombinant mouse TGF-β (20µg/mL) (Biolegend), recombinant mouse IL-12p70 (20µg/mL) (Biolegend) or anti-IL-12p40 blocking antibody (20µg/mL) (Biolegend) were added to the well.

### T cell activation analysis by flow cytometry.

After 48h or 96h of co-culture as indicated in the figures, T cells were stained for CD45.1, CD8, CD44, CD62L, PD-1 and CD103 to analyze their activation and polarization status. CTV dilution was analyzed to assess T cell proliferation.

## Quantification and Statistical Analysis

Statistical analysis was performed using Prism 10 (GraphPad Software Inc., USA). Each dot displayed on the graphs corresponds to one biological replicate and error bars represent standard deviations. When two experimental groups were compared, two-tailed unpaired or paired Student's t test was used. When three or more groups were compared, statistically significant differences between means were determined using the one-way analysis of variance (ANOVA) method. Tukey's multiple comparisons test was applied when comparing multiple conditions. A p-value of less than 0.05 was considered as significant, indicated with the following signs: \*p < 0.05, \*\*p < 0.01, \*\*\*p < 0.001, \*\*\*\*p < 0.0001.

# Declarations

## Acknowledgments

We thank M. Pittet for providing IL-12<sup>YFP</sup> mice. We thank the flow cytometry and the
animal facility platforms from Centre de Recherche sur l'Inflammation (CRI), Faculté de Médecine Bichat and from Institut Pasteur. We thank the NGS platforms from Institut Curie U932 and from Institut Cochin. We thank Institut National de la Santé et de la Recherche Médicale U1149 and U1016 units, Centre National de la Recherche UMR3738 unit, Institut Pasteur.

## Funding

Centre National de la Recherche Scientifique CNRS (PG)

PhD Fellowship from Université de Paris (NV)

PhD Fellowship from Fondation pour la Recherche Médicale (NV)

Postdoctoral fellowship from Fondation pour la Recherche sur le Cancer ARC (PB)

Cancer Research UK

Institut National du Cancer INCA (PL-BIO22-147)

Fondation pour la Recherche sur le Cancer ARC (PJA2021060003913)

Fondation pour la Recherche Médicale (EQU202203014687)

## Author contributions

Conceptualization: NV, PB, PG

Methodology: NV, PB, PG

Investigation: NV, PB, AO, MS, LG, RS, YG, FLRDC, AS, MV, AR, SB, KP, JB

Software: NV, SB, YG

Resources: GDJ, ELG, MD, TB, KVG, KH, LS, JH, FB, PG

Funding acquisition: ET, JH, PG

Supervision: LS, JH, FB, PG

Writing: NV, PB, PG

## Ethics declarations

Competing interests: Authors declare that they have no competing interests.

## Data availability

Bulk and single-cell RNA-Seq datasets are accessible here: https://figshare.com/s/6a9c76588d496aaaa768. All original data are available from the corresponding author upon request.

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Figures
<figure><img src="image_3.png" /><figcaption>Figure 1</figcaption></figure>

T<sub>RM</sub>-like CD8<sup>+</sup> T cells infiltrate lung tumors.

(A-B) Representative flow cytometry plots and quantifications of CD69<sup>+</sup>CD103<sup>+</sup> CD8<sup>+</sup> T<sub>RM</sub> (A) and exhausted PD1<sup>+</sup>TIM3<sup>+</sup> CD8<sup>+</sup> T cells (B) in the lungs of tumor-free and KP tumor-bearing mice 14 days post-tumor cells injection (n = 4 tumor-free and n = 8 KP mice, unpaired t-tests).

(C) Venn diagram showing the overlap between CD69<sup>+</sup>CD103<sup>+</sup> and PD1<sup>+</sup>TIM3<sup>+</sup> CD8<sup>+</sup> T cells in the lungs of KP-tumor bearing mice 14 days post-tumor cells injection (n = 10 mice).

(D-G) scRNAseq analysis of sorted total lung CD8<sup>+</sup> T cells from KP-bearing mice 14 days post-tumor cells injection (see also Fig.S1C).
(D) UMAP dimensionality reduction embedding the different clusters.

(E) DotPlot showing the RNA expression of core marker genes across clusters.

(F) Violin Plots showing the scoring of indicated gene signatures across Cd44<sup>+</sup>Sell<sup>-</sup> clusters<sup>4,11,16</sup>.

(G) Distribution of Cd44<sup>+</sup>Sell<sup>-</sup> clusters across CITE-Seq gated CD44<sup>+</sup>CD62L<sup>-</sup>PD1<sup>+</sup>CD69<sup>+</sup>CD103<sup>+</sup> T<sub>RM</sub>, CD44<sup>+</sup>CD62L<sup>-</sup>PD1<sup>+</sup>Not(CD69<sup>+</sup>CD103<sup>+</sup>) T<sub>Exh</sub> and CD44<sup>+</sup>CD62L<sup>-</sup>PD1<sup>-</sup> T<sub>Eff</sub>.

(H) Representative flow cytometry gating strategy used to identify CD8<sup>+</sup> T cell populations infiltrating lung KP tumors.

(I) Quantification of the proportions of CD62L<sup>-</sup>CD44<sup>+</sup> CD8<sup>+</sup> T cell populations infiltrating lung KP tumors (n = 10 mice).

(J-K) Bulk RNA-sequencing analysis of sorted CD8<sup>+</sup>T cell populations as defined in Figure 1H.

(J) Signature scoring of gene modules related to stemness, circulation, activation-cytotoxicity, exhaustion and tissue-residency as shown in Figure S1L.

(K) Principal-component analysis (PCA). Top high and low loading genes are indicated for PC1 and PC2.

(L) Relative MFI protein expression of indicated marker genes across CD8<sup>+</sup> T cell populations as determined by flow cytometry in Figure 1H.

(M) Hobit-tdTomato MFI expression across lung CD8<sup>+</sup> T cell populations quantified in Hobit-tdTomato reporter mice<sup>18</sup> bearing KP tumors (n = 5 mice, paired one-way anova).

(N) Representative histogram and quantifications of CD45.2-labelled cells following intravenous injection of a CD45.2-fluorescent antibody 5min before sacrifice (n = 5 mice, paired one-way anova).

(O) Representative flow cytometry plots showing the gating of tetramer-OVA<sup>+</sup> CD8<sup>+</sup> T cells infiltrating KP-OVA but not KP lung tumors.

(P) Representative flow cytometry gating strategy showing the phenotype of tetramer-OVA<sup>+</sup> (dark) or tetramer-OVA<sup>-</sup> cells (grey) infiltrating KP-OVA lung tumors.

(Q) Quantification of the proportions of tetramer-OVA<sup>+</sup> or tetramer-OVA<sup>-</sup> CD8<sup>+</sup> T cell populations infiltrating lung KP-OVA tumors (n = 11 mice, paired two-way anova).

(R) CD8<sup>+</sup> T cell populations were isolated from the lungs of KP-OVA bearing mice at day 14 post-injection and restimulated ex vivo with 1µM OVA-specific SIINFEKL peptide for 5-hours. The percentage of double-positive IFNg<sup>+</sup>TNFa<sup>+</sup> are quantified (n = 7 mice, paired one-way anova).
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<figure><img src="image_17.png" /><figcaption>Figure 2</figcaption></figure>

(M) Representative flow cytometry plots and quantification of post-transfer CD44<sup>+</sup>CD62L<sup>-</sup> T<sub>RM</sub>-like TILs differentiated from donor CD45.2<sup>+</sup> tdTomato<sup>-</sup> or tdTomato<sup>+</sup> CD8<sup>+</sup> T cells (n = 5 mice, paired t-test).

Tumor-draining lymph nodes contain a fraction of CD103<sup>+</sup> activated CD8<sup>+</sup> T cells poised to generate T<sub>RM</sub>-like TILs.

(A) Experimental design for T cell trapping in the LN. Mice were injected i.v. with KP tumors. Mice were treated with or FTY720 to block lymphocyte egress from all lymphoid tissues every 2-3 days from day 1 or from day 7 post-KP-injection.
(B) Quantification of $T_{RM}$ after FTY720 treatment at day 14 post-KP-injection (n = 9 vehicle, n = 4 FTY720 mice day 1 to 14 and n = 9 FTY720 day 7 to 14 mice, unpaired one-way anova).

(C) Representative flow cytometry plots and quantification of CD103⁺ and CD103⁻ $T_{Act}$ in the LN of tumor-free and KP-tumor bearing mice (n = 3 naïve and n = 8 KP mice, unpaired t-test).

(D) Representative flow cytometry plots showing the gating of tetramer-OVA⁺ CD8⁺ T cells infiltrating KP-OVA but not KP lung tumors.

(E) Representative flow cytometry gating strategy showing the phenotype of tetramer-OVA⁺ (dark) or tetramer-OVA⁻ cells (grey) in the tdLN of KP-OVA tumor bearing mice.

(F) Quantification of the proportions of tetramer-OVA⁺ or tetramer-OVA⁻ CD8⁺ $T_{Act}$ populations in the tdLN of KP-OVA tumor bearing mice (n = 4 mice, paired two-way anova).

(G) Volcano plot representing differentially expressed genes between CD103⁺ $T_{Act}$ and CD103⁻ $T_{Act}$. Genes with Log2(fold change, FC) > ±2 and a false discovery rate (FDR)-adjusted p value of less than 0.05 were considered significant.

(H-I) GSEA of pairwise comparisons of CD103⁺ $T_{Act}$ vs CD103⁻ $T_{Act}$ using genes from residency and circulating signatures⁴ (H) or differentially expressed genes between lung TIM3⁺ $T_{RM}$ and TIM3⁺ $T_{Exh}$ (I).

(J-K) Flow cytometry quantification of $T_{effector}$ (J) and $T_{RM}$ (K) core markers in CD103⁻ $T_{Act}$ and CD103⁺ $T_{Act}$ (n = 4-7 mice, paired t-tests).

(L-M) Adoptive transfer of total tdLN from CD103<sup>ERcre</sup> × ROSA<sup>LSL-tdTomato</sup> mice.

(L) Experimental design. Donor CD45.2⁺ CD103<sup>ERcre</sup> × ROSA<sup>LSL-tdTomato</sup> and host WT CD45.1⁺ mice were injected with KP cells. 8 days later, tomato labelling was induced in donor mice by intraperitoneal injection of tamoxifen. At day 9, donor tdLNs were transferred intravenously in host mice (i.e., each total donor tdLN was transferred into one recipient mice). Lungs from host mice were analyzed 5 days post-transfer to assess the progeny of tdTomato-labelled transferred cells.
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<figure><img src="image_24.png" /><figcaption>Figure 3</figcaption></figure>

Both XCR1⁺ and IRF4-dependent DCs contribute to the differentiation of CD103⁺ T<sub>Act</sub> in tdLN.

(A) Representative flow cytometry plot for the gating of CD11c<sup>high</sup>MHCII<sup>int</sup> resident vs CD11c<sup>int</sup>MHCII<sup>high</sup> migratory dendritic cells in tdLNs of KP tumor-bearing mice.

(B) Representative flow cytometry plots for the gating of migratory and resident DC1 and DC2 and quantification in tumor-free or KP tumor-bearing mice (n = 5 tumor-free and n = 5 KP mice, unpaired t-tests)

(C-E) scRNAseq analysis of total CD11c⁺MHCII⁺ cells from tdLN of KP-bearing mice 14 days post-tumor cells injection (see also Figure S3A).
(C) UMAP dimensionality reduction embedding the different clusters.

(D) Dot Plot showing the expression of core marker genes across clusters.

(E) Violin Plots showing the CITE-Seq protein expression of core DC1 (XCR1) or DC2 (SIRPa) markers across dendritic cell clusters.

(F) Quantification of resident DC1, resident DC2, migratory DC1 and migratory DC2s in WT, XCR1<sup>DTA</sup> and CD11c<sup>RF4</sup> mice bearing KP tumors (n = 13 WT, n = 4 XCR1<sup>DTA</sup> and n = 7 CD11c<sup>RF4</sup> mice, one-way anova).

(G-H) Proportion of each tdLN scRNAseq dendritic cell clusters in WT or CD11c<sup>RF4</sup> samples (G) or, vice versa, of WT or CD11c<sup>RF4</sup> samples in each dendritic cell cluster (H).

(I) Representative flow cytometry plots and quantification of CD103<sup>+</sup> and CD103<sup>-</sup> tetramer-OVA<sup>+</sup> T<sub>Act</sub> in the LN of WT, XCR1<sup>DTA</sup> and CD11c<sup>RF4</sup> mice bearing KP-OVA tumors (n = 4 WT, n = 4 XCR1<sup>DTA</sup> and n = 4 CD11c<sup>RF4</sup> mice, one-way anova). Black tetramer-OVA<sup>+</sup> cells overlay grey tetramer-OVA<sup>-</sup> cells.

(J) Representative flow cytometry plots and quantifications of transferred tdLN CD103<sup>+</sup> OT1 as described in Figure S3E. Black CD45.1<sup>+</sup> OT1 overlay grey endogenous CD45.2<sup>+</sup> CD8<sup>+</sup> T cells.
<figure><img src="image_25.png" /><figcaption>Figure 4</figcaption></figure>

CD103⁺ activated T cells in tdLN contain a rare population of CXCR6⁺T<sub>RM</sub>-like cells.

(A-E) scRNAseq of 80%T<sub>Act</sub> and 20% T<sub>CM</sub>/T<sub>Naive</sub> sorted from the tdLN of 14 days KP-bearing mice (gating strategy in Figure S4A).

(A) UMAP dimensionality reduction embedding the different clusters.

(B) Dot Plot showing the expression of core marker genes across clusters.

(C) Violin Plots showing the scoring of indicated gene signatures across activated clusters<sup>4,11,16</sup>.
(D) Distribution of $T_{Act}$ clusters across CITE-Seq gated CD103$^+$ $T_{Act}$ and CD103$^+$ $T_{Act}$.

(E) Projection of lung Cd44$^+$Seli scRNA-seq clusters 1, 4, 7, 8 and 9 on tdLN $T_{Act}$ clusters 0,3,5 and 8.

(F) Representative flow cytometry gating strategy to identify $T_{Act}$ populations and associated quantification (n = 12 mice).

(G) Representative flow cytometry histograms and quantifications of SLAMF6 and Hobit-tdTomato expression across tdLN $T_{Act}$ subsets (n = 5 Hobit-tdTomato mice, paired one-way ANOVA test).

(H) Representative flow cytometry gating strategy showing the phenotype of tetramer-OVA$^+$ (dark) or tetramer-OVA$^-$ cells (grey) in the tdLN of KP-OVA tumor bearing mice.

(I) Quantification of the proportions of tetramer-OVA$^+$ or tetramer-OVA$^-$ CD8$^+$ T cell populations in the tdLN of KP-OVA tumor bearing mice (n = 4 mice, paired two-way anova).

(J-L) Representative flow cytometry plots (J) and quantifications of total $T_{Act}$ (K) or $T_{Act}$ subsets (L) in WT, $XCR1^{DTA}$ or $CD11c^{RF4}$ mice bearing KP-tumors (n = 12 WT, n = 8 $XCR1^{DTA}$ and n = 6 $CD11c^{RF4}$ mice, one-way ANOVA tests).
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<figure><img src="image_32.png" /><figcaption>Figure 5

Efficient generation of T<sub>RM</sub>-like TILs involves both XCR1 and IRF4-dependent DCs at the level of tumor-draining lymph nodes.</figcaption></figure>

(A-B) Representative flow cytometry plots (A) and quantifications (B) of lung CD8<sup>+</sup> T cell populations in WT, XCR1<sup>DTA</sup> or CD11c<sup>IRF4</sup> mice bearing KP-tumors (n = 22 WT, n = 10 XCR1<sup>DTA</sup> and n = 22 CD11c<sup>IRF4</sup> mice, one-way ANOVA tests).

(C-D) Representative flow cytometry plots (C) and quantifications (D) of lung tetramer-OVA<sup>+</sup> CD8<sup>+</sup> T cell populations in WT, XCR1<sup>DTA</sup> or CD11c<sup>IRF4</sup> mice bearing KP-OVA tumors (n = 4 mice per group, one-way ANOVA tests).
(E) Experimental design for the adoptive transfer of total tdLN. Donor CD45.2⁺ mice (WT, *XCR1*<sup>DTA</sup> or *CD11c*<sup>RF4</sup>) and host CD45.1⁺ mice were injected with KP cells. 7 days later, total donor tdLN were transferred intravenously in host mice. Lungs from host mice were analyzed 7 days post-transfer.

(F-G) Representative flow cytometry plots (H) and quantifications (I) of donor CD45.2⁺ total CD8⁺T cells and donor CD45.2⁺ T<sub>RM</sub> in the lungs of host CD45.1⁺ mice bearing KP tumors 7 days post-transfer of WT, *XCR1*<sup>DTA</sup> or *CD11c*<sup>RF4</sup> tdLN (n = 6 WT, n = 4 *XCR1*<sup>DTA</sup> and n = 6 *CD11c*<sup>RF4</sup> donor mice, one-way ANOVA test).

<figure><img src="image_33.png" /><figcaption>Figure 6</figcaption></figure>

Low TCR triggering by migratory crosspriming DC2s favors CD103 expression while migratory DC1-derived IL-12 supports CXCR6 expression.
(A) Representative flow cytometry plot and quantification of ZsGreen⁺ resident and migratory DC1 and DC2 in tdLN of mice bearing KP-ZsGreen tumors (full line) (n = 5 mice, one-way ANOVA tests). Dotted lines represent control KP-injected mice for each subset.

(B) Representative flow cytometry plot and quantification of IL-12-YFP⁺ resident and migratory DC1 and DC2 in tdLN of IL-12<sup>YFP</sup> mice bearing KP tumors (n = 5 mice, one-way ANOVA tests).

(C) Representative flow cytometry plot and quantification of H2K<sup>b</sup>-OVA expression on resident and migratory DC1 and DC2 in tdLN of mice bearing KP-OVA tumors (full line). H2Kb-OVA MFI were normalized with KP-injected mice (dotted line).

(D) Experimental design for the *ex vivo* cocultures. Migratory DC subsets were FACS-sorted from tdLN of mice bearing KP-OVA tumors at day 9 and cocultured with CTV-loaded naïve OT-I cells for 2 days.

(E-F) Representative flow cytometry plots (E) and quantifications (F) of CTV-loaded naïve OT-I cells cultured for 2 days with flow cytometry-sorted migratory cDC1 or migratory DC2 from tdLN of mice bearing KP-OVA tumors in presence or not of recombinant IL-12p70 or anti-IL-12p40 neutralizing antibody.

(G-H) Representative flow cytometry plots (G) and quantifications (H) of CTV-loaded OT-I cells cultured for 2 days with flow cytometry-sorted migratory DC2 from tdLN of mice bearing KP tumors in presence of increasing SIINFEKL peptide concentration (1pM, 10pM, 10²pM and 10⁴pM) (n = 4 mice, paired one-way anova tests).

(I) Naïve OT-I cells were cultured for 4 days with SIINFEKL peptide and low affinity peptides SIIQFEKL (Q4), SIITFEKL (T4) and SIIGFEKL (G4) at 10²pM. CD44⁺ activated OT1 and CD103 expression were quantified (n = 3 replicates, paired one-way anova tests). See also Figure S6C.

(J) Experimental design for the *in vivo* IL-12 blockade. Mice were injected i.v. with KP tumors and treated with anti-IL-12p40 neutralizing antibody every 3 days from day 0 to 14.

(K) Quantifications of the total number of tdLN $T_{Act}$ and CXCR6 expression in CD103⁺ $T_{Act}$ (n = 7 control and n = 5 anti-IL12 treated mice, unpaired t-tests).

(L-M) Representative flow cytometry plots (L) and quantifications (M) of CTV-loaded OT-I cells cultured for 4 days in the presence of increasing SIINFEKL peptide concentrations (1pM, 10pM, 10²pM, 10³pM and 10⁴pM) and cytokines TGF-β, IL-12 or both (n = 3 replicates). CD103 and CXCR6 expression were analyzed.
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<figure><img src="image_42.png" /><figcaption>Figure 7</figcaption></figure>

Crosspriming by migratory DC2s recapitulates the T<sub>RM</sub> transcriptional program.

(A) CTV-loaded naïve OT-I cells were cultured for 2 days with flow cytometry-sorted migratory DC1 or migratory DC2 from tdLN of mice bearing KP-OVA tumors. CD103<sup>+</sup> and CD103<sup>-</sup> divided OT1 activated by DC1 or DC2 were FACS-sorted and bulk-RNA sequencing was performed.

(B) Principal-component analysis (PCA). Top high and low loading genes are indicated for PC1 and PC2.

(C) Scoring of previously defined gene signatures for tdLN CD103<sup>+</sup> T<sub>Act</sub> (bulk RNA-seq), tdLN Cluster 8 Cxcr6<sup>+</sup> (scRNA-seq), lung T<sub>RM</sub>-like TILs (bulk RNA-Seq) and tdLN CD103<sup>-</sup> T<sub>Act</sub> (bulk RNA-seq).
(D) GSEA of pairwise comparisons of CD103⁺ OT1<sub>DC2-Act</sub> vs all other OT1 populations (termed as Rest) for gene signatures of tdLN CD103⁺ T<sub>Act</sub> (bulk RNA-seq), tdLN Cluster 8 *Cxcr6⁺* (scRNA-seq), lung T<sub>RM</sub>-like TILs (bulk RNA-Seq) and tdLN CD103⁻ T<sub>Act</sub> (bulk RNA-seq).

(E) Volcano plot representing differentially expressed genes (DEGs) between CD103⁺ OT1<sub>DC2-Act</sub> and all other OT1 populations (Rest). Genes with a Log2(fold change, FC) > ±2 and a false discovery rate (FDR)-adjusted p-value of less than 0.05 were considered significant.

(F-G) GSEA of pairwise comparisons of CD103⁺ OT1<sub>DC2-Act</sub> vs all other OT1 populations (Rest) for gene signatures of memory CD8 T cells<sup>55</sup> and SMAD4 targets<sup>56</sup>(F) or Hallmark MTORC1 signaling and MYC targets<sup>57</sup>(G) extracted from the MSigDB website.

**Supplementary Files**

This is a list of supplementary files associated with this preprint. Click to download.

* SuppFig1TRMlikeCD8Tcellsinfiltrateltumors.jpg

* SuppFig2TumordraininglymphnodescontainafractionofCD103activatedCD8TcellspoisedtogenerateTRMlikeTILs.jpg

* SuppFig3BothXCR1andIRF4dependentDCscontributetothedifferentiationofCD103TActintdLN.jpg

* SuppFig4CD103activatedTcellsintdLNcontainararepopulationofCXCR6TRMlikecells.jpg

* SuppFig5EfficientgenerationofTRMlikeTILsinvolvesbothXCR1andIRF4dependentDCsattheleveloftumordraininglymphnodes.jpg

* SuppFig6LowTCRtriggeringbymigratorycrossprimingDC2sfavorsCD103expressionwhilemigratoryDC1derivedIL12supportsCXCR6expression.jpg